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A Clinical Study on Gestational Diabetes Mellitus and
Pregnancy Induced Hypertension
THESIS
Submitted to
The Tamilnadu Dr. M.G.R Medical University, Chennai
For the award of degree of
DOCTOR OF PHILOSOPHY In the
Faculty of Pharmacy Submitted by
Mr. V. Sivakumar, M.Pharm.,
Under the guidance of
Dr. A. RAJASEKARAN, M.Pharm., Ph.D.,
March 2014
KMCH COLLEGE OF PHARMACY KOVAI ESTATE, KALAPATTI ROAD
COIMBATORE-641048
Contents Contents Page
List of Abbreviation List of Tables List of Graphs 1. Introduction …………………………………………………………………………………………………….. 1 2. Aims and Objectives…………………………………………………………………………………………. 5
2.1. Aims ……………………………………………………………………………………………………………. 5 2.2. Objectives ………………………………………………………………………………………………...... 5
2.2.1. Gestational diabetes mellitus…………………………………………………………… 5 2.2.2. Pregnancy induced hypertension……………………………………………………… 6 2.2.3. Gestational diabetes mellitus and Pregnancy induced hypertension… 6 2.2.4. Association………………………………………………………………………………………. 7
3. Literature Review……………………………………………………………………………………………… 8 3.1. Definition…………………………………………………………………………………………………….. 9 3.2. Pathogenesis……………………………………………………………………………………………….. 11 3.3. Prevalence…………………………………………………………………………………………………… 15 3.4. Risk factors………………………………………………………………………………………………….. 19 3.5. Screening and Diagnosis………………………………………………………………………………. 21 3.6. Complications of GDM and PIH……………………………………………………………………. 23 3.7. Management of GDM and PIH……………………………………………………………………… 25
3.7.1. Dietary therapy of GDM…………………………………………………………………… 26 3.7.2. Physical therapy of GDM………………………………………………………………….. 27 3.7.3. Pharmacotherapy of GDM……………………………………………………………….. 27 3.7.4. Pharmacotherapy of PIH………………………………………………………………….. 28
3.8. Association of PIH………………………………………………………………………………………… 29 3.9. Pharmacist and Patient education……………………………………………………………….. 30
4. Scope of the study……………………………………………………………………………………………. 32 4.1. Plan of the work…………………………………………………………………………………………… 33
5. Materials and Methods…………………………………………………………………………………….. 34 5.1. Study overview……………………………………………………………………………………………. 34 5.2. Gestational diabetes mellitus………………………………………………………………………. 35
5.2.1. General outcome……………………………………………………………………………… 35 5.2.2. Risk factors………………………………………………………………………………………. 35 5.2.3. Complications………………………………………………………………………………….. 35
5.3. Pregnancy induced hypertension…………………………………………………………………. 37 5.3.1. General outcome……………………………………………………………………………… 37 5.3.2. Risk factors………………………………………………………………………………………. 37 5.3.3. Complications………………………………………………………………………………….. 38
5.4. Gestational diabetes mellitus and Pregnancy induced hypertension……………. 39 5.4.1. General outcome……………………………………………………………………………… 39 5.4.2. Risk factors………………………………………………………………………………………. 39 5.4.3. Complications…………………………………………………………………………………… 39
5.5. Association………………………………………………………………………………………………….. 40
5.5.1. Assessment of association of complications GDM and PIH by risk factors………………………………………………………………………………………………
40
5.5.2. Assessment of association of complications GDM and PIH by pregnancy outcome………………………………………………………………………….
40
5.6. Definition and cutoff values for the Maternal and Fetal analysis…………………. 41 5.7. Statistical analysis……………………………………………………………………………………….. 43
6. Results……………………………………………………………………………………………………………… 44 6.1. Gestational diabetes mellitus………………………………………………………………………. 46 6.2. Pregnancy induced hypertension…………………………………………………………………. 55 6.3. Gestational diabetes mellitus and Pregnancy induced hypertension…………... 62 6.4. Analysis……………………………………………………………………………………………………….. 70
6.4.A. Individual analysis……………………………………………………………………………. 73 6.4.A.1. GDM…………………………………………………………………………………... 73
6.4.A.1.a. Diet vs. Insulin………………………………………………….. 73 6.4.A.1.b. 1st vs. 2nd vs. 3rd trimester………………………………… 76 6.4.A.1.c. Early vs. Late onset…………………………………………. 80 6.4.A.1.d. FBS ≤ 95 mg/dl vs. FBS ≥ 95 mg/dl…………………. 84
6.4.A.2. PIH…………………………………………………………………………………….. 89 6.4.A.2.a.Treatment comparison…………………………………….. 89 6.4.A.2.b.Disease severity comparison……………………………. 92
6.4.B. Comparison analysis………………………………………………………………………… 98 6.4.B.1. Risk factors………………………………………………………………………… 96
6.4.B.1.a. Risk factors and their values are not equally distributed between the groups……………………….
97
6.4.B.1.b. An increase in number of risk factors and interactions of one on another showed variation in the development of complications……………………………………………………
104
6.4.B.1.c. The increasing number and values of riskfactors causing earlier development of complications……………………………………………………
108
6.4.B.2. Complications………………………………………………………………….... 121 6.4.B.2.1. Maternal complications……………………………………. 121 6.4.B.2.2. Neonatal complications……………………………………. 122
6.4.B.3. Associations………………………………………………………………………. 127 6.4.B.3.1. Common risk factors……………………………………….. 129 6.4.B.3.2. Pregnancy outcome…………………………………………. 129
6.5. Development of prediction tool…………………………………………………………………… 131 6.5.1. Prediction tool an introduction………………………………………………………… 131 6.5.2. Limitations of tool……………………………………………………………………………. 132 6.5.3. How to use the prediction tool………………………………………………………… 133
7. Discussion…………………………………………………………………………………………………………. 138 7.1. Prevalence of GDM……………………………………………………………………………………… 136 7.2. Risk factors and complications of GDM……………………………………………………….. 136 7.3. Risk factors and complications of GDM……………………………………………………….. 139
7.4. Discussion for analysis…………………………………………………………………………………. 141 7.4.1. Gestational diabetes mellitus…………………………………………………………… 141
7.4.1.1. The duration of GDM is not significantly affecting the outcome of pregnancy……………………………………………………….
141
7.4.1.2. Types of treatment to GDM shown no significant difference in the outcome of pregnancy…………………………….
142
7.4.1.3. Control of glycemic level with in the normal range has given better pregnancy outcome……………………………………….
143
7.4.2. Pregnancy induced hypertension ……………………………………………………. 144 7.4.2.1. No significant difference in terms of pregnancy outcome
between different anti-hypertensive drugs used in the treatment of PIH…………………………………………………………………
144
7.4.2.2. Pregnancy outcomes were not differed much with the severities of PIH, same time no special risk factors can be identified corresponding to particular severity…………………..
145
7.4.3. Associations……………………………………………………………………………………… 146 8. Conclusion………………………………………………………………………………………………………… 148 9. Impact of the study…………………………………………………………………………………………… 152 Bibliography Appendix 1 Human Ethics Committee permission letter Appendix 2 List of Publications Appendix 3 Plagiarism report Appendix 4 Data collection form Errata
1. Introduction
Gestational diabetes mellitus (GDM) and Pregnancy induced hypertension (PIH) are the most
common complications throughout the world that affect 1-14%1 and 2-10%2 of all pregnancies
respectively. Both these complications arise during pregnancy and resolve after delivery.
GDM is a condition of elevated blood glucose level generally detected during pregnancy and
become normal soon-after delivery, resulting with immediate and long-term effects to both
mother and child.
The prevalence of diabetes is increasing enormously day by day. What is not as well recognized is
that a similar trend occurring to GDM. The incidence of GDM has increased worldwide by 35%
from 1991 to 20003. It is presently predicted, that GDM affects 7% of all pregnancies, which means
there are about 2,00,000 of GDM recorded each year. It occurs in almost 1 in 20 pregnant
women4.
The prevalence of GDM ranges from 1 to 14% of all pregnancies, and this variation is due to
various diagnostic methods applied in different etinic5. One survey taken in India has shown that
the prevalence of GDM was increasing from 2.1% in 1982 to 16.55% in 2002. The prevalence rate
of GDM in reproductive age women is similar to the rate of impaired glucose tolerance in the
general population. Over the next 2-3 decades 80 million women in the reproductive age will be
affected by diabetes in the world. Twenty million women expected to be affected in India.
Ethnically Indian women are considered more risks to develop diabetes and the relative risk of
developing diabetes mellitus in Indian women are 11.3 times more compared to western countries
women6. The prevalence is high across the Asian countries and studies about perinatal
consequences of these diseases are important from these countries7.
Screening is usually carried out around 24 – 28 weeks of gestational age. But GDM can manifest at
any stage of pregnancy. The factors that can influence the pregnant women to develop GDM in all
trimesters include age, BMI, positive family history of diabetes, previous history of GDM,
multiparity and irregular menstrual history8.
Indeed the hyperglycemia resolves in postpartum it causes cesarean delivery, preterm delivery
Macrosomia, hyperbilirubinemia, fetal hypoglycemia, shoulder dystocia and respiratory distress
syndrome. GDM affects mother as well as their child, at the age of 5 years, offspring of GDM
mothers are larger and have transformed glucose metabolism compared to offspring of non GDM
mothers9. The prevalence of childhood type-2 diabetes for past 30 years is attributable to
increasing exposure to maternal diabetes during pregnancy10. Women with GDM are at increased
risk and it may lead to have preeclampsia11 and cardiovascular complications12. In long term, GDM
women are more prone (20 – 50%) to develop type 2 diabetes mellitus in five years after
delivery13.
Diet and exercise are important elements in the treatment of GDM. Insulin and certain oral
hypoglycemic drugs can be used, separately or combined, to achieve normoglycemia14,15. Oral
anti-diabetic drugs are not recommended to treat GDM since these drugs are causing potential
teratogenicity and cross the placenta resulting with neonatal hyperinsulinism and
hypoglycemia4,16.
Hypertension in pregnancy, whether chronic or recently diagnosed is always a matter of concern
as they are associated with various pregnancy outcome. PIH is a condition of elevated blood
pressure and proteinuria during pregnancy and become normal after pregnancy. PIH is a generic
classification of hypertension disorders occurring during pregnancy that includes Gestational
hypertension (GH), Preeclampsia (PE) and eclampsia17.
GH is a hypertension without development of significant proteinuria (less than 0.3g/l), after 20th
week of gestation or during labour and/or within 48 h of delivery. Preeclampsia is the
development of GH and significant proteinuria after 20th weeks of gestation or during labour and
/or within 48 h of delivery. Eclampsia is the development of convulsions during or postpartum
associated with high blood pressure and proteinuria18.
Approximately 12 – 22% of pregnancies affected with hypertension and cause 17.6% of maternal
death in United States19.The prevalence of PIH in Europe was 3.1% to 9.6%20. Overall PIH affects
up to 10% of all pregnancies worldwide (desk Prev.Europ-1). Nulliparity, increasing maternal age,
multiple births, chronic hypertension, obesity, diabetes previous preeclampsia, family history, a
new partner and/or ≥ 10 years since last pregnancy, presence of antiphospholipid antibody, renal
diseases are the important risk factors to develop hypertension in pregnancy21,22,23,24,25.
Indeed the PIH resolves postpartum it causes various maternal and fetal morbidity and mortality.
(Seizure, stroke, intra uterine growth retardation (IUGR), preterm delivery, hepatic and renal
failure and death)26. Fetal mortality and low birth weight is high among the hypertensive related
pregnancies27. Preeclamptic women have high risk for cardiovascular diseases, and their offspring
may be at increased risk for cardiovascular diseases in adulthood28.
The aim of treatment is to control the blood pressure there by preventing further complication to
both mother and fetus29. A wide variety of antihypertensive drugs are used to treat PIH, the
rationale behind the antihypertensive treatment is to control the blood pressure thereby reduce
the hypertensive related problems and thereby improving fetal growth30. Methyldopa, calcium
channel blockers like nifedipine, amlodipine and beta blockers like labetalol are the
antihypertensive drugs frequently used in the treatment of PIH during pregnancy. Methyldopa and
beta-blockers are the drugs of choice for treating mild to moderate hypertension31.
The presence of PIH become high and reaches up to 20% among the pregnancy women having
diabetes mellitus32,33. Diabetes increases the risk of preeclampsia from two to three folds in
pregnant women34,35. It was perceived from 1960s, that the Preeclamptic women are at increased
risk for developing hypertension and cardiovascular diseases in later life36. The same was observed
with GDM women in their later life. The implication of this is that the women with GDM are at
increased risk of future diabetes as are their children.
The coexistence of GDM and PIH seems to be high frequency of complications in both stages,
immediate and long-term37. There were common risk factors and complications for both diseases
and both diseases seek treatment in order to achieve better pregnancy outcome. Many questions
are still arising in the usage of hypoglycemic drugs, antihypertensive drugs in the treatment of
GDM as well as PIH. There was lack and demand of prospective trials to confirm the optimal target
BP level for good pregnancy outcome in PIH treatment38.
The relationship of GDM and PIH is not well understood39. Many studies are suggesting that there
is an association between these two diseases40,41,42,43,44 and some other studies suggesting no
association45,46,47. However there was less studies in India about these diseases.
The future prospect is alarming and it is time to check the incidence of these two complications. A
better understanding of these complications and their relationship may suggest effective
strategies for natal care to women.
This study would give better understanding on risk factors, management, complications, relative
measures and relationship between GDM and PIH.
2. Aims and Objectives
The basic idea of the study is to understand and compare the two commonly encountered complications of women, GDM and PIH.
2.1. Aims
1) Understanding the relationship of GDM and PIH by comparing these complications.
2) Development of strategy to identify the women to particular risks by assessing the risk factors
2.2. Objectives
2.2.1. Gestational diabetes mellitus [GDM]
2.2.1.1. General outcome 1) Assessment of maternal and fetal characters of gestational diabetes mellitus.
2.2.1.2. Risk factors
1) Assessment of risk factors for the development of GDM.
2) Is there any difference in the risk factors of women those who developed GDM early and those who developed GDM late?
3) Whether Increase in number of risk factors causing earlier development of GDM?
4) Whether increasing values of risk factors causing earlier development of GDM?
2.2.1.3. Complications
1) Assessment of complication of GDM.
2) Whether the duration of GDM has any influence on the outcome of pregnancy.
3) Assessment of difference in the pregnancy outcome of GDM women who received controlled diet alone and who received diet along with Insulin as a treatment.
4) Assessment of difference in the pregnancy outcome of GDM women who controlled fasting blood glucose level on or below 95 mg/dl and who controlled above 95 mg/dl?
2.2.2. Pregnancy induced hypertension [PIH]
2.2.2.1. General Outcome
1) Assessment of maternal and fetal characteristics of Pregnancy induced hypertension
2.2.2.2. Risk factors
1) Assessment of risk factors for the development of PIH.
2) Whether increase in number of risk factors causing earlier development of PIH?
3) Whether increasing values of risk factors causing earlier development of PIH?
4) Are the risk factors causing variation in the severity of PIH?
2.2.2.3. Complications
1) Assessment of complications of PIH.
2) Assessment of difference between the pregnancy outcome of PIH women who received drug and who do not received drug for their treatment.
3) Is pregnancy outcome varies with severity of PIH?
2.2.3. Gestational diabetes mellitus and Pregnancy induced hypertension [GDM+PIH]
2.2.3.1. General analysis
1) Assessment of maternal and fetal characteristics of women diagnosed with both complications GDM and PIH.
2.2.3.2. Risk factors
1) Assessment of risk factors for the development of PIH and GDM
2.2.3.3. Complications
1) Assessment of complications of women diagnosed with PIH and GDM.
2.3.4. Association
2.3.4.1. Assessment of association of complications; GDM and PIH by risk factors
1) What are the common risk factors between GDM and PIH
2) Is there any association in the development of GDM and PIH?
2.3.4.2. Assessment of association of complications; GDM and PIH by pregnancy outcome
1) What are the common problems in the pregnancy outcome of GDM and PIH?
2) Is there any association in the outcome of pregnancy between GDM and PIH?
3. Literature Review
Pregnancy is a maturational crisis that can be stressful but rewarding as the woman prepares for a
new level of caring and responsibility. Moves from being self-contained and independent to being
committed to a lifelong concern for another human being48,49. The following are various traditional
cultural beliefs50,51,52,53,54,55,56.
Hispanic – members of Hispanic community have their origins in Spain, Cuba, Central and South
America, Mexico and other Spanish speaking countries.
‘Pregnancy is desired soon after marriage Prenatal care is sought late’
African American – Members of the African American culture have their origins in Africa
‘Pregnancy is thought to be state of ‘wellness’ Which is often reason for delay in seeking prenatal care; Pregnancy may be viewed by men as sign of virility’
Asian – The term Asian commonly refers to groups from China, Korea, the Philippines, Japan and South East Asia, particularly Thailand, Indochina and Vietnam
‘Pregnancy is considered time when mother has Happiness in her body’ and it is seen as natural process’
Caucasian/European-Americans –
‘Pregnancy is viewed as condition that requires medical attention to ensure health’
Native American –
‘Pregnancy is considered as normal natural process
Pregnancy spans 9 calendar months, 10 lunar months, or approximately 40 weeks, pregnancy is
divided into three month periods called trimesters. The first trimester lasts from weeks 1 through
13; the second weeks 14 through26; the third, weeks 27 through term gestation (38 to 40
weeks).Among the various health problems arising in pregnancy, one serious health problem is
GDM57.
3.1. Definition
Gestational diabetes is one of the types of diabetes mellitus which is recognized only during
pregnancy. Gestational diabetes mellitus suffers the body as like the other type of diabetes
mellitus do, resulted with increased blood glucose level. In 1824 Dr. Heinrich Gottleib Bennewithz,
from University of Berlin, reported a definition of the symptoms which are unchanged today
“urine differing in quality and quantity from the normal….Accompanied by unquenchable thirst
and eventual wasting” he summarized his observation from pregnancy, that the diabetes was a
symptom of the pregnancy or due to the pregnancy58.
The original concept of GDM goes back at least as early as 1946, when Miller reported a perinatal
mortality rate of 8% in infants delivered to mothers who subsequently developed diabetes in
middle age59.Dr. J.P. Hoet was first recognized and described the association of obstetrical risk and
diabetes. This French description was translated to English and published in Diabetes in 1954 by
Dr. F.D.W. Lukens. Hoet had used the term “Meta Gestational diabetes58,60,61.After various studies,
in 1979, in Chicago, the First International Gestational Diabetes Workshop Conference provided a
definition of Gestational diabetes mellitus;
‘Carbohydrate intolerance of varying severity with onset or first recognition during pregnancy’.
One of the concepts in late 1940s was the degrees of hyperglycemia is a risk factor to diabetes in
pregnancy. This led to the term “Prediabetes in pregnancy” and to the concepts of temporary and
latent diabetes. In 1964, the typical study of O’Sullivan highlighted the criteria for diabetes during
pregnancy. In 1967 Jorgen Pedersen was first used the term “Gestational diabetes”61,62.
Hypertension in pregnancy is a group of conditions associated with elevated blood pressure during
pregnancy, with or without proteinuria and in some cases convulsions were the clinical
manifestation occurs usually late in pregnancy and regress after delivery63. Hypertensive disorders
on pregnancy (HDP) refers to a broad spectrum of conditions from preexisting hypertension and
mild (pregnancy-induced) Gestational hypertension (GH) to severe gestational hypertension,
eclampsia, the hemolysis, elevated liver enzymes, low platelets (HELLP) syndrome and multi organ
failure. The most serious maternal and fetal consequence occurs due to Preeclampsia (PE) and
eclampsia64.
During the early weeks of normal pregnancy the blood pressure decline due to a general relaxation
of muscles within the blood vessels. From around the middle of pregnancy it increases gradually to
reach the pre-pregnancy levels at term. Physical activity, period of day and body position and
mental status are the factors also influencing the BP during pregnancy65.
Historically it didn’t take time to realize that there were certain conditions unique to pregnancy,
and what got the attention was death which seemed to be an accepted hazard of trying to
reproduce. Hippocrates in the 5th century noted the signs drowsiness, head pain and convulsions
during pregnancy. And since his time preeclampsia ‘the disease of theories’ has eluded the
physicians. The presence of a circulating toxin of fetal origin was postulated as the cause of
toxemia of pregnancy. This condition was known to the ancient Greeks, who named it eclampsia
which means a sudden flashing or on slaught. By 1619 Varandaeus coined the term eclampsia in a
treatise in gynecology. Before all these the term eclampsia was used only to refer to the visual
phenomena which accompanied the neurologic aspects of the malady. In the late 19th century, it
was recognized that increased BP and proteinuria occurs before seizures. Later the association of
these signs and syndrome of PE was realized66.
The classification of PIH is still confusion because of the limited knowledge on the etiology and due
to the continuous nature of the signs and symptoms used for the diagnosis. The classification of
severe disease is reserved for the development of additional maternal and fetal complications
relating to various organ systems. The differentiation of mild and severe disease is not definable or
predictable, except in retrospect, as mild disease can rapidly progress to eclampsia and may occur
in its severest form in postpartum period67.The International statistical classification of diseases
and related health problems 10th revision (ICD-10) classifies pregnancy induced hypertension as
gestational hypertension/mild preeclampsia without significant proteinuria Moderate
preeclampsia with proteinuria (013) Severe preeclampsia with proteinuria (014) Eclampsia with
convulsions (015).
PIH is defined as hypertension with or without proteinuria emerging after 20 weeks gestation, but
resolving up to 12 weeks postpartum68,69. PIH is also defined as new onset proteinuria (≥300
mg/24 hours) in hypertensive women who exhibit no proteinuria before 20 weeks gestation. GH is
diagnosed in women whose blood pressure reaches ≥140/90 mmHg for the first time during
pregnancy (after 20 weeks gestation), but without proteinuria. Preeclampsia (PE) is elevated blood
pressure (blood pressure ≥140/90 mmHg) accompanied with proteinuria exceeding 300 mg/24 h
emerges for the first time after 20 weeks gestation, but both symptoms normalize by 12 weeks
postpartum. Eclampsia (E) Eclampsia is defined as the onset of convulsions in a woman with PIH;
the same cannot be attributed to other reasons. This generalized seizure may appear during the
gestation, during the labor and even after the labor.
The severity of PIH is assessed by the extent of symptoms. Both blood pressure and proteinuria
are dependable indicators of severity. Mild PIH Blood pressure is ≥140/90 mm/Hg but <160/110
mm/Hg after 20 weeks gestation, and proteinuria is ≥300 mg/24 hours without exceeding 2.0 g/24
h or 3+ by dipstick method69,70,71,72. Severe PIH Blood pressure is ≥160/110 mm/Hg, and
proteinuria exceeds 2.0 g/24 h or 3+ by dipstick method73. PIH that emerges earlier than 32 weeks
gestation is referred to as early onset (EO) type, and PIH that emerges after 32 weeks gestation is
referred to as late onset (LO) type74,75.
3.2. Pathogenesis
Pathogenesis of GDM has been postulated and well recognized in the Third-workshop-conference
on GDM. Until then it was not known how the GDM developing in pregnanancy76. The exact cause
of this is unknown and may be due to genetic factors, as well as the hormones produced by the
placenta, progesterone, estrogen, human placental lactogen (HPL), and human chorionic
somatotropin (HCS). Even though, insulin production is increased, its effect is diminished, which is
indicative of insulin resistance with hyperinsulinemia and poor insulin response. The insufficient
insulin produced by the mother allows glucose to circulate in the blood stream and be passed on
to the fetus77.
Decreased maternal pregravid insulin sensitivity (insulin resistance) coupled with an inadequate
insulin response are the pathophysiological mechanisms underlying the development of GDM.
Insulin regulated carbohydrate, lipid and protein metabolism are affected and increases nutrient
availability to the fetus, possibly resulted with fetal overgrowth and overweight78.
Autoimmunity and heredity: Danish, Finnish, and US studies found that similar frequencies of HLA-
DR2, DR3 and antigens in normal and GDM pregnant women and little dominance of markers (islet
cell antibodies (ICAs) insulin auto antibodies (IAAs) and glutamyl acetate decarboxylase (GAD), are
the antibodies causing self-destruction of beta cells of GDM women. After this result the
autoimmune concept of GDM were ruled out79,80,81.
Insulin secretion and sensitivity: Proinsulin levels in individuals with fasting in the third trimester of
pregnancy are approximately double fold higher in GDM women than normal pregnant women
(MY-30). A number of clinical studies indicated that pregnancy is an insulin resistant state. GDM
women show a discrete reduction in the ability of beta subunit of insulin receptor to undergo
tyrosine phosphorylation. Further it reduces the 25% less glucose transport in GDM women82,83.
Insulin resistance generally begins in the second trimester and progresses during the remaining
period of pregnancy. Approximately 80% of Insulin sensitivity is reduced during the pregnancy.
Placenta secreting hormones, progesterone, lactogen, cortisol, prolactin, and growth hormone,
are key contributors to the insulin-resistant state gotten in pregnancy.
Women with GDM have a greater severity of insulin resistance compared to the insulin resistance
seen in non-GDM pregnancies. The reduction in this 1stphase insulin release is a marker for β-cell
dysfunction. In addition, the women with GDM had a 67% reduction in their β-cell compensation
compared with normal pregnant control subjects84.
Two forms of insulin resistance present in GDM women. The first one happened as a result of
normal physiology during pregnancy. This may be due to multiple factors, and are exerted at the
level of substrate -1 of the insulin receptor in β-subunit.
Figure 1 Pathophysiology of GDM
Physical
PCOS
Obesity
Race\Ethnicity
Pre-Conception
Insulin Resistance
Increased Demand on Beta Cells for Insulin Secretion
Hyperinsulinemia
Increased Maternal Weight Gain
Neonatal Macrosomia
Pre-eclampsia
Pregnancy Induced Hypertension
Insulin Resistance of Pregnancy
Pregnancy Increases Requirement for insulin Secretion
Reduction in Beta cell Reserve
Later Development of Type 2 Diabetes Mellitus
Fail to Overcome Insulin resistance
Glucose Intolerance
Gestational Diabetes
of skeletal muscle. Added to this the increased level of free intracytoplasmic p85α subunit of
phosphatidylinositol 3-kinase seems to be complicated. This type of alterations in insulin signaling
would give to reduced insulin-mediated glucose uptake in body cells.
The second form of insulin resistance in GDM is due to the susceptibility of women, means that
the diabetes happened even before the pregnancy and now it is exacerbated because of the
various physiological changes occurs in pregnancy. The uptake of glucose by cells is due to the
tyrosine phosphorylation, which gives signals to cells to recognize the glucose. This tyrosine
phosphorylation also considered as an important factors deciding insulin resistance84.
PE is characterized by vasospasm, pathologic vascular lesions in multiple organs, high platelet
activation along with platelet consumption and coagulation process in microvasculature. The
pathogenesis of PE has not yet been fully established, however in recent years, some hypotheses
have been proposed.
In normal pregnancy, the development of mutual immunologic tolerance between maternal tissue
and fetal (paternal) allograft is thought to lead to important morphologic and biochemical changes
in the-systemic and uteroplacental circulation. The endovascular trophoblast destroys the
muscular layer and autonomic innervations of the spiral arteries. Meanwhile, endothelium
increases the synthesis of prostacyclin and nitric oxide, vascular relaxing factors. These changes
result in vasodilation of the uterine circulation.
In preeclampsia, immunologic maladaptation might lead to a disturbance of trophoblast invasion
in the spiral arteries. The insufficient invasion and in growth of the trophoblast inhibits vessel
dilation, reducing maternal blood supply to the intervillous space and thus reducing perfusion or
causing hypoxia. It is believed that poorly perfused trophoblast elaborates an unknown substance
that is toxic to endothelial cells, causing endothelial dysfunction and damage and ultimately
leading to the clinical syndrome of preeclampsia. The most commonly suspected endothelial toxin
is oxygen free radicals. Injured endothelial cells release endothelin, a potent vasoconstrictor, and
produce less nitric oxide. These changes, coupled with endothelial damage, cause progressive
vasoconstriction and platelet aggregation. Damaged vascular endothelium expresses antigens
which induce endothelial cell antibodies. Binding of these antivascular antibodies and immune
complexes to resting endothelial cell monolayer might be involved in altered prostacyclin
secretion, increased platelet adherence, activation of the complement cascade, and disruption of
the monolayer. Coagulation will be triggered, and thrombin will be generated locally, contributing
to platelet aggregation. With endothelial damage and attenuation of the normal vasodilation of
pregnancy, a decrease in glomerular filtration rate and renal blood flow and enhanced sensitivity
to angiotensin are observed. These events may lead to hypertension, edema, and proteinuria85.
Susceptibility to preeclampsia is dependent upon a single receding gene. Endothelins are potent
vasoconstrictors; possibly have a role in the development of PIH. Plasma endothelin-1 has been
reported to be increased in normotensive laboring and non-laboring women and even higher
levels have been reported in Preeclamptic women. Wang and colleagues reported that
normotensive pregnancies are characterized by progressive increases in the ratios of
prostacyclin/thromboxane and vitamin E/lipid peroxides86.
3.3. Prevalence
The prevalence of GDM diverges with different ethnic within a country87.It affects 1 to 14% of
pregnancies depending on the ethnic and diagnostic methods88. It was estimated that 366 million
people will be affected with diabetes globally in 2011. The prediction to rise is 552 million people
by 2030 with half of these living in Asia89.
Ethnicity is a particularly important factor determining incidence of GDM. Very high risk group
includes – Australian indigenous, Polynesian and South Asian groups. Moderate high risk includes
– Middle eastern and other Asian groups90,91.
Table 1Global prevalence of GDM across different countries.
Country Year Prevalence
Australia92 2010 9.5
Bahrain93 2001-2002 13.5
Belgium94 2002-2004 1.0
Canada95 2010 17.8
China96 2008 6.8
Finland97 2009 8.9
France98 2006 12.1
Hong Kong99 2006 10.4
Ireland100 2006-2007 10
Japan101 2008-2010 1.6
Korea102 1993-1997 2.4
Malaysia103 2006 11.4
Qatar104 2010-2011 16.3
Saudi Arabia105 2000 12.5
Sweden106 1998-2002 2.28
Thailand107 2001-2002 3.0
UnitedArab Emirates108 2007 20.6
US109 2002 4.1
The prevalence of GDM in India varies with different parts of the country. High to low rates of
GDM have been documented. Depending upon the diagnostic methods used the prevalence varied
from 3.8% to 21%110. From the random survey performed in various cities in India, 2002 to 2003,
recorded the prevalence of GDM was 16.2% in Chennai, 15% in Thiruvanathapuram, 21% in
Alwaye, 12% in Bangalore, 18.8% in Erode and 17.5% in Ludhiana111.In Chennai, Tamilnadu, the
prevalence was recorded with 16.5% in 2004112.The trend was 2.1% in 1982, which was increased
to 7.62% in 1991, which further increased to 16.55% in 2002113. One other study in Tamilnadu was
found that the prevalence of GDM was high in urban population, 17.8% in urban, 13.8% in semi-
urban and 9.9% in rural areas114.In Belgaum, Karnataka, the prevalence was found to be 16% for
the period of 2008 to 2010115.In Maharashtra the prevalence was found to be 7.7%116. In Rohtak,
Haryana, the prevalence was found to be 7.1%117. In Kashmir, the prevalence was found to be
3.8%118. In Rajasthan, the prevalence was found to be 6.6%119. In Hydrabad, Andhraprdesh, the
prevalence was found to be 8.43%120.
Hypertension in women of child bearing age has become a challenging medical problem with its
increasing prevalence121.Preeclampsia affects 2% to 10% of pregnancies worldwide. WHO
estimates developing countries are seven times higher, compared to developed countries, in
incidence of preeclampsia122.Recently it was reported that in USA, the pregnancy associated
maternal deaths are majorly caused by hypertensive disorders, which is accounts for 12.3%123.
InLatin-America the number one cause of maternal death is preeclampsia124.
The average prevalence of preeclampsia from 1980 to 2010 in United States was 3.4%125. In
Australia it was found to be 3.3% for the period of 2000 to 2008126. In Nigeria the prevalence
ranges from 2% to 16.7%127. In Tanzania, South Africa, and Ethiopia and in Egypt it ranges from
1.8% to 7.1%128,129. Canada and Western Europe ranges from 2% to 5%130,131. In Iran the
prevalence of preeclampsia was 2.32%132. The prevalence was found to be 7.5% in Brazil133 and
3.3% in Turkey134.
In India the prevalence was 8% to 10%.135. The incidence was recorded with 3.2% in Orissa136,
and4.18% in Mumbai137. The prevalence of PIH in other states of India as follows.
Table 2: Prevalenceof Pre-eclampsia by region and state, India, 2005-06138.
India/States Pre-eclampsia
Urban Rural Total N (%) N (%) N (%) India 5738 54.0 16323 56.2 22,061 55.6 Northern region Delhi 403 50.2 30 43.5 433 49.7 Haryana 88 37.3 201 31.8 289 33.3 Himachal Pradesh 36 47.4 313 46.9 349 46.9 Jammu and Kashmir 113 58.5 402 58.2 515 58.3 Punjab 197 56.4 306 52.8 503 54.1 Rajasthan 207 67.2 496 45.3 703 50.1 Uttaranchal 145 67.1 467 71.2 612 70.2 Central region Chhattisgarh 127 59.3 501 50.9 628 52.4 Madhya Pradesh 327 59.8 1027 59.8 1354 59.8 Uttar Pradesh 529 51.4 2110 53.8 2639 53.3 Eastern region Bihar 150 75.4 1143 77.8 1293 77.5 Jharkhand 150 64.1 748 77.4 898 74.8 Orissa 106 52.2 679 58.9 785 57.9 West Bengal 297 63.7 1015 63.4 1312 63.5 Northeastern region Arunachal Pradesh 121 75.6 275 63.4 396 66.7 Assam 85 52.5 641 58.1 726 57.4 Manipur 161 36.7 426 41.3 587 39.9 Meghalaya 99 68.8 399 59.4 498 61.0 Mizoram 203 70.5 201 63.6 404 66.9 Nagaland 167 50.0 535 49.0 702 49.2 Sikkim 54 59.3 306 67.4 360 66.1 Tripura 73 89.0 383 87.2 456 87.5 Western region Goa 253 56.9 209 59.7 462 58.1 Gujarat 298 69.5 407 61.8 705 64.8 Maharashtra 531 46.1 435 33.6 966 39.5 Southern region Andhra Pradesh 208 36.7 426 36.3 634 36.4 Karnataka 231 38.0 355 36.9 586 37.3 Kerala 207 78.4 431 76.4 638 77.1 Tamil Nadu 290 47.4 346 48.7 636 48.1
3.4. Risk factors
A number of risk factors are associated with the development of GDM. The factors include
glucosuria, age over 30 years, family history of diabetes mellitus, previous history of GDM,
previous history of glucose intolerance, Previous macrosomic baby, treatment for infertility,
polyhydromnios, frequent UTI, frequent monliasis, previous history of still birth, unexplained
neonatal death, prematurity, pre-eclampsia in multipara139. Women with a record of gestational
diabetes have also better risk of developing gestational diabetes in succeeding pregnancies. The
delivery of a macrocosmic infant or a suspected glucose intolerance test in a previous pregnancy is
also risk factors for gestational diabetes140.
The risk of GDM becomes significantly and progressively increased from the age of 25 years
onwards. In clinical practice, maternal age of ≥25 years should be adopted instead of ≥35 years or
40 years as a risk factor for the development of GDM141.
The biological characteristics such as elderly maternal age, a high maternal BMI, and multiparity
are significant risk factors to develop GDM. A previous history of Caesarean delivery or
macrosomia was similarly associated. But the histories of previous early pregnancy or perinatal
loss, or congenital anomalies were not associated with GDM142.
History of irregular menstrual cycle was found to be an independent risk factor for the
development of GDM. It should be consider in the process of screening for GDM143.
The blood hemoglobin level of a woman also shows influence on the development of GDM. The
HB concentration more than 13% shows an increased risk for GDM144.
Systolic pressure more than 110 mmHg at or before 12 weeks of pregnancy also has an increased
risk of GDM145.
Physically inactive, smoking habits, food habits and drugs that affect glucose metabolism are also
other risk factors146.Some researchers speculated that PE is a disease of the upper class, others
more recently believe it is a disease of the poor status, and still others think all social classes are at
equal risk147.
PE is considered as important cause to perinatal problems. The following are the risk factors
causing PE: Genetic factors: family history, immune response genes, antioxidant enzymes and the
hypertension genes. Immunological factors: Unprotected sexual intercourse, parity, previous
abortion and paternal change, assisted reproductive technology, antiphospholipid antibodies.
Physiological factors: age, pre pregnancy BMI, multiple gestations, polyhydromnios,
hydropsfetalis, ethnicity. Environmental factors: smoking, high altitude, physical activity and job
stress during pregnancy148.
Among these, nulliparity, previous preeclampsia, high maternal weight, hypertension, diabetes
and twin pregnancies are the significant risk factors to cause PIH147.
A case control study done by Odegard et al on 12,804 pregnant women to examine the risk factors
and clinical manifestation of PE found out the increased risk for PE to nulliparous, high BP, over
maternal weight and with previous PE149. Women with PE in a previous pregnancy had a strongly
increased risk of PE in the current pregnancy compared to women to parous women with no
previous PE149. Pregnancies with multiple gestations have a higher incidence of PIH than do those
with singleton gestation. Pregnant woman with twin gestation has three times the risk of
developing PIH than does a woman with a singleton pregnancy. The incidence of eclampsia is also
three times higher in twin pregnancies than in singleton pregnancies148.
High maternal weight was positively associated with the risk of PE were the risk was confined to
mild to moderate PE and was not present for severe disease. This observation was different from
that which was reported by stone et al who found that maternal obesity may also increase the risk
of developing severe PE149. The association between prepregnancy BMI, pregnancy weight gain
and risk for PIH was recognized. It was also observed that a greater weight gain during pregnancy
increases PIH risk. A significant weight gain of 12.2 kg in the first two trimesters was found in
women who had PE and not among those who had GH150.
Nulliparous women were at increased risk of PE compared to primiparous women. The strength of
the association increased slightly with disease severity. Working during pregnancy doubled the risk
for PE. Working during pregnancy has been implicated as a risk factor for preeclampsia in a variety
of studies147.
It has been reported that a man who fathered a preeclamptic pregnancy in one woman had an
increased risk of fathering a preeclamptic pregnancy in other women, although statistically
significant, the increased paternal recurrence risk was small151.
GDM has been frequently reported as a complication of PE. Common risk factors such as elevated
body mass index and advanced age has been noted for these two conditions152. A large population
based study on the association between GDM and PIH found a significant increased risk of GH,
mild PE, severe PE among women with GDM and the risk of developing this disorder was 1.5 times
greater among women with GDM153.
3.5. Screening and Diagnosis
Ever since the introduction of the concept of GDM, there has been controversy about the
importance of this condition and the appropriateness of screening for it154. Assessment of risk
factors is the usual method to identify the GDM, unfortunately this type of methods identify about
50% of women with GDM87,155.
The oral glucose tolerance test (OGTT) is the method mostly used to diagnose GDM. Based on
ADA, the diagnostic criteria is 100gm oral glucose tolerance test in 3- h and GDM is diagnosed if
two or more plasma glucose levels meet or exceed the following thresholds: FBS of 95 mg/dl, 1-h
glucose level of 180 mg/dl, 2-h glucose level of 155 mg/dl, or 3-hglucose level of 140 mg/dl156.
The World Health Organization (WHO) diagnostic criteria are based on a 2-h 75-g OGTT.
Gestational diabetes mellitus is diagnosed by WHO criteria if either the fasting glucose is > 126
mg/dl or the 2-h glucose is > 140 mg/dl. If they found negative for initial screening, they should be
rescreened again between 24 and 28 weeks of gestation157.
Table 3: Diagnostic criteria according to different organizations
Plasma glucose (mg/dl)
Organization OGTT glucose load Fasting 1-h 2-h 3-h
ADA* 100g 95 180 155 140
ACOG* 100g 105 190 165 145
WHO# 75g 126 - 140 -
IADPSG# 75g 92 180 153 -
* Diagnosis of Gestational diabetes mellitus if two or more glucose values equal to or exceeding
the threshold values, OGTT: oral glucose tolerance test, ADA: American diabetes association,
ACOG: American council of obstetricians and gynecologists, WHO: World health organization,
IADPSG: International association of diabetes and pregnancy groups.
GDM occurs only in pregnancy; usually the diagnosis of GDM will be done by glucose tolerance
test. The suitable method for identifying GDM is still controversial158. The screening of GDM is
carried out at 24th to 28thweeks of pregnancy. During pregnancy, placenta produce many
hormones which are prevent the insulin from its action and give rise to insulin resistance, and even
more hormone secretion and resistance in the second and third trimesters since placenta grows
larger through trimester. The need of extra insulin, up to three times normal, may not be
produced by the maternal pancreas. At this situation, very low amount of glucose reached inside
the cells and plenty stays back in blood itself. This is the condition called GDM and usually occurs
around 20th and 24th week of gestation and can be recognized during 24th to 28thweek of
gestation159.
3.6. Complications of GDM and PIH
The presence of GDM has been associated with several adverse outcomes, to both mother and
baby160,161. The complications are significant and often potential to both mother and child.
Most women who have diabetes give birth to healthy babies, especially when they keep their
blood sugar under control, eat a healthy diet, get regular and moderate physical activity and
maintain a healthy weight. In some cases, though the condition can affect the pregnancy. Keeping
glucose levels under control may prevent certain problems related to GDM162.
Some of the problems associated with GDM are as follows158,162,163,164.
Maternal – miscarriages, polyhyrdromnios, preterm labor, infection, preeclampsia, growth
acceleration, cesarean, birth trauma, puerperal sepsis, failing lactation and perinatal death.
Fetal –macrosomia, hypoglycemia, jaundice, kernicterus, polycythemia, respiratory distress
syndrome, hypocalcemia, hypomagnesimia, hyperbilirubinemia, birth injury, neonatal death.
The GDM are very prone to develop preeclampsia particularly with the women diagnosed earlier
to 24th week of gestation165. Carr et al166 found that GDM women are more risk to develop
cardiovascular disease at young age if they have family history of diabetes mellitus. GDM mothers
have high risk to develop type – 2 diabetes mellitus. Hence, the early detection of risk factors
which are adjustablemay delay or prevent the disease development, thereby improving their
quality of life. Ghattu V. Krishnaveni et al167carried out a study on gestational diabetes to find out
the rate of diabetes in the 5 years follow-up among South Indian women and concluded that the
incidence of diabetes was significantly high with women who had previous GDM.
Poorly controlled maternal type-1 diabetes and fetal macrosomia were associated with lipoprotein
abnormalities in infants and this has implications for later metabolic diseases168. GDM increases
cardio metabolic risks of offspring, and the hyperinsulinemia in uterus state is found to be
independent forecaster to childhood glucose intolerance169. Anders Aberg et al170 in their study on
congenital malformations among infants whose mothers had gestational diabetes or preexisting
diabetes found a total malformation rate of 9.5% while the rate of gestational diabetes was found
to be 5.7%.
Egeland et al171 carried out a study to determine effects GDM on women and their girl children for
future metabolic and cardiovascular risks. Gestational diabetes mellitus (GDM) pregnancies led to
increased conversion to glucose intolerance in mothers, minimal in daughters. The girl children of
GDM women are more prone to develop central adiposity and insulin resistance. Control over the
blood glucose level and BMI may prevent the obesity and glucose intolerance in offspring’s of
GDM women.
The various maternal impacts of PIH are HELLP, glomerular endotheliosis, hemorrhage, ischemia
and edema of cerebral hemispheres that leads to seizures, frontal headaches, occipital headaches,
hemiplegia, visual disturbances, cardiomyopathy and pulmonary oedema172.
Cardiovascular dysfunction with reduced cardiac output and vascular resistance were occurring
largely in preeclamptic women. The PE women and their off springs were also having high risk to
develop cardiovascular disease during their adulthood173.
Stroke is a feared, but fortunately infrequent complication of severe PE or eclampsia. Cerebral
hemorrhage has been reported to be the most common cause of death in patients with
eclampsia174. One of the chief aims in the use of antihypertensive drugs in the management of
severe preeclampsia and eclampsia is to reduce the risk of (fatal cerebral) hemorrhages175. The
death happened in eclampsia is importantly because of cerebral hemorrhage176. A study on 31
patients with PE or eclampsia from 1980 to 2003 reported that hemorrhage in cerebral area is a
vital cause of maternal morbidity and mortality in severe PE174. The HELLP syndrome is a variant of
severe PE causes maternal mortality of 0% to 24%, and perinatal mortality is between 6.6% and
60%. HELLP syndrome is reported to occur in 20% of women with severe PE and in 10% of women
with eclampsia177.
Incidence, etiology, and course of pulmonary edema in all obstetric patients were studied
prospectively among 29,621 subjects for 3.5 years. It was found out that pulmonary edema
developed in 18 cases (0.06%), and it was considered of cardiogenic origin178.
Fetal morbidity and mortality rates are directly related to the severity of hypertension. Adverse
perinatal outcomes of mild and severe PE explained that women who developed severe GH had
higher rates of both spontaneous and indicated preterm deliveries at <37 weeks of gestation and
had more infants that were small for gestational age (SGA).Women with severe PE were more
than two folds increased risk to have preterm delivery and fourfold increased chance to have fetus
of <10th percentile birth weight for gestational age179.
In a population-based retrospective cohort study of 16,936 pregnant women in China the mean
birth weights of babies born to mothers with GH, PE, and severe PE were compared with birth
weights of infants born to mothers with normal blood pressure. There were no differences in
mean birth weight between women with GH and women with normal BP180.
A study also noted that preterm PE was associated with lighter, shorter, and leaner newborns,
whereas late PE had increased rates of both larger and smaller newborns180. Proteinuria in
pregnancies complicated by hypertension was associated with increased rates of stillbirth and
delivery of low-birth-weight infants181. The risk of SGA in a pregnancy with PIH increased with the
severity of PIH180. Severe GH was associated with a high rate of low birth-weight infants and lower
gestational age at delivery when compared to mild GH or mild PE182.
3.7. Management of GDM and PIH
Treating GDM, means taking steps to keep blood glucose levels in a target range. Treatment will
include self-testing of blood glucose, nutritional assessment and counseling with appropriate meal
plan, physical activity, and insulin if needed. Medical nutrition therapy and physical activity are the
primary intervention or management strategies for gestational diabetes mellitus183. The main aim
of the management of GDM is preventing the perinatal morbidity and mortality, which can be
achieved through normalizing blood glucose level as well as other metabolites like lipids and
amino acids to normal range87.
Most of the GDM women were controlling blood glucose by prescribed diet and exercise but for
20-50% of women with GDM medication is needed to control their diabetes. In either case
monitoring blood sugar is a key part of the treatment program76.
The GDM women strictly controlled the glucose level by treatment showed significantly lower
problems to child birth. Therapy includes the following 3 steps, dietary therapy, physical therapy
and pharmacological therapy.
3.7.1. Dietary therapy of GDM
A healthy diet is important for every woman. Eating the correct and right amount of diet were the
best way to normalize the sugar level in blood. The first line management of women with
gestational diabetes mellitus consists of medical nutrition therapy with adjunctive exercise for at
least 30 min per day. Patients who fail to maintain glycaemia targets through diet and exercise
therapy receive insulin injections or other anti-hyperglycemic medications184.
The aim of medical nutritional therapy are to provide adequate nutrition for the mother and
fetus, provide sufficient calories for appropriate maternal weight gain, maintain normoglycemia,
and avoid ketosis. Women who are in first trimester do not require any increased energy. Normal
weighted women who are in second and third trimester require additional 300 kcal/day. A
minimum of 1700 to 1800 kilocalories are needed to prevent ketosis. Carbohydrate foods should
be distributed throughout the day. Small to moderate-sized meals has to be taken three to four
times a day. Limiting carbohydrates to 40% of the total daily caloric intake has been shown to
decreased postprandial glucose values185.
The level of weight gain indicates sufficiency of nutritional food for mother. Mother’s tissue
growth, which supports the baby growth, and body growth are the reasons of weight gain during
pregnancy which includes added blood, increased size of breast, fat store, the placenta, baby, and
the increased amniotic fluid volume57.
3.7.2. Physical therapy of GDM
Physical activity can be helpful in lowering blood glucose levels and reducing stress. It also
increases the insulin sensitivity. In addition, regular exercise help in the management of back pain,
muscle-cramps, swelling, disturbances in sleep and constipation. Physical activity prepares the
body for delivery, improve the insulin sensitivity, and improve the glucose uptake and glycogen
synthesis. Around 40% of women need physical therapy along with dietary therapy in order to
meet the pleasant delivery186.
3.7.3. Pharmacotherapy of GDM
Use of oral hypoglycemic agents to treat GDM has not been recommended because of concerns
about potential teratogenicity and transport of glucose across the placenta resulting in
hyperinsulinism, causing prolonged neonatal hypoglycemia.
First generation hypoglycemic agents like chlorpropamide, tolbutamide, have been shown to cross
the placenta187. Glyburide does not cross the placenta and stimulate fetal hyperinsulinism if
started after the first trimester of pregnancy188.Langer et al189 found that glyburide was as
effective as insulin for the treatment of GDM. Eighty percent of GDM patients were found to be
achieved the target levels of glucose with glyburide; most of the patients required 10 mg of
glyburide on daily basis. But FDA was not approved the glyburide for the treatment of GDM and
yet to have to prove the safety of drugs in large population.
Rowan et al190 on 363 GDM patient who received metformin, found that, there were no difference
in pregnancy outcomes between the patient who treated with insulin and metformin.
A randomized controlled trail by Langer et al191has found that there is no difference in large for
gestational age, macrosomia, neonatal hypoglycemia, admission to neonatal intensive care, or
fetal anomalies between GDM women who were treated with insulin and Glyburide.
In a prospective study conducted by Rai et al192metformin was found to be cheap and effective
alternate to insulin in GDM women. Management of GDM by oral hypoglycemic agent found to be
safe and there are no differences in glycemic control or pregnancy outcomes compared to
insulin167.
In GDM insulin therapy traditionally has been started when blood glucose levels exceed 105gms/dl
in the fasting state and 120 mg/dl, two hours after meals. In aggressive treatment the fasting state
value of 95 mg/dl is taken193.Insulin therapy to GDM constantly reduces the fetal morbidities and
mortalities. Maternal glucose level is the deciding factors to choose the insulin as a
treatment194,195. The following steps were using in the insulin therapy for GDM.
A. Dose of 30/70 insulin: start with 4 units in the morning then based on the requirements add
up the dose of 2 units up to 10 units. The total need of insulin can be divided like 2/3rd in the
morning and 1/3rd in the evening. Insulin 50/50 can be considered if PPBS is high.
B. For the GDM developed in third trimester: MNT is the initial therapy then addition of
premixed insulin can be considered. Dose of insulin can be initiated with 8 units in the
morning.
3.7.4. Pharmacotherapy of PIH
The pharmacologic treatment of hypertensive disorders is a medical and obstetric challenge197.
During pregnancy the aim of antihypertensive treatment is avoidance of cerebrovascular
complications and that drug should give effective vasodilation29. It should not cause fetal
bradycardia or teratogenicity. Therefore ACE inhibitors, thiazides diuretics and beta blockers
should be avoided197.
Methyldopa, labetalol and calcium channel antagonists are frequently used in the treatment of
PIH. Methyldopa and beta-blockers are used in the mild to moderate PIH. Prazosin and hydralazine
are used in the moderate and severe PIH. For emergency PIH Hydralazine, urapidil and labetalol
were used. The PIH developed during the 1st trimester of pregnancy, methyldopa will be the drug
of choice for the treatment198.
Magee et al in their study on oral beta-blockers for mild to moderate hypertension in pregnancy
suggested that long-acting oral antihypertensive drugs, beta-blockers causes Intra uterine growth
retardation (IUGR) and reduced birth weights199.
Alpha methyldopa is the drug of choice for long-term control in PIH pregnancy. There are
restricted indications for Nifedipine29. But a study on the safety of calcium channel blockers
concluded that there were no major teratogenicity risk199. According to meta-analyses and
Cochrane reviews reported the fetal complications with hydralazine29.
3.8. Association of GDM and PIH
To date, most epidemiologic studies exploring the relationship of gestational diabetes with
preeclampsia have considered GDM as a risk factor for preeclampsia200,201. Though both diseases
arise because of placental substances, the association between these diseases was also evaluated
by some of the studies. Women with GDM have1.5 folds increased risk for developing
hypertension disorders in pregnancy202. Several studies are suggesting the common
pathophysiology, including insulin resistance, chronic inflammation and endothelial
dysfunction200,203,204,205,206.
Acohort study analyzed the risk factors for PE and GH with 10,666 pregnant women in Sweden and
found; the risk for development of preeclampsia is high with GDM mother207. Study by Ingrid
Ostland et al208, with 430,852 women, suggests that there is an independent and significant
association between GDM and preeclampsia. In GDM patients the high blood pressure early in
pregnancy, even prior to gestational diabetes diagnosis, were associated with the subsequent
development of preeclampsia209. In a retrospective cohort study of more than 111,000
pregnancies found that women with GDM were 2.5 times more likely to experience preeclampsia
than without diabetes210.One other large, population-based study conducted in Latin America with
878,680 pregnancies demonstrated an association between GDM and preeclampsia211. Vambergue
et al212from France studied in 15 maternity units found an association between PIH and GDM.
Since some of the risk factors are common for both disease the coexistence of both disease may
worsen the pregnancy outcome. Increased maternal age, nulliparity, and multiple gestation
pregnancies could be identified as common risk factors for both diseases213. one study with 24,290
singleton pregnancies, reported that carbohydrate intolerance of varying severity are increased
risk factors for developing PIH and the same time both conditions share the common etiology214.
Preeclampsia has been frequently reported as a complication of GDM215. But the relationships
between these two conditions were not well established.
Short term cohort studies reports that there was no correlation between insulin resistance and
hypertension but post pregnancy studies reports the association of insulin resistance with both
inflammatory deregulation and vascular dysfunction216.
The inadequate perinatal care also is a reason to develop preeclampsia in GDM women. The better
perinatal care may reduce the occurrence of preeclampsia in GDM women by 30 percent217,218.
One other studies suggests that the aggressive early treatment of GDM might reduce the risk of
preeclampsia219,220. The glucose control in pregnancy may reduce the rate of preeclampsia even in
severe GDM condition221.
The coexistence of both diseases increases the risk of complicated pregnancy as well as future risk
for cardiovascular diseases and type 2 diabetes mellitus. Women complicated with preeclampsia
or GDM had an increased risk for developing diabetes later in life, especially those having GDM222.
Many studies were reported the linkage of GDM and preeclampsia to type 2 diabetes in later
life223,224,225,226,227. In Norwegian hospital-based clinical study, with in the 16 years of GDM
pregnancy 60% of women developed diabetes228.
Comparison of the risk factors for pre-eclampsia and gestational diabetes may provide vision into
the etiologic and mechanisms related to these conditions. Several studies focused on GDM as a
risk factor for pre-eclampsia, but not directly compared the risk factors of these complications.
There was no documentation on which risk factors are similar and to what way they are related.
3.9. Pharmacist and Patient education
Pharmacists have an important role in the management of GDM. The importance of screening for
GDM and the management of GDM are the area where pharmacist can educate the patients. GDM
women have the huge chance to develop type 2 diabetes mellitus later in their life; hence a
pharmacist should educate them on the need of life style modification and continue follow-up for
checking blood glucose level195.
The main role of pharmacist in GDM management is patient education. Education for GDM
women can includes dietary counseling, life style modification, insulin administration, and self-
glucose monitoring. Pharmacist should educate the patients on the symptoms of hypoglycemia
and also the management of hypoglycemia. Pharmacist should also educate the women about the
importance of exercise, diet and treatment196.
4. Scope of the study
GDM and PIH are the serious complications that occur during pregnancy which affects both the
mother and fetus. The coexistence of these seems to cause high complications in both immediate
and long-term. But the relationships of these pregnancy problems were not well established.
The future prospect is alarming and it is the time to check the incidence of these two
complications. A better understanding of these complications and their relationship may suggest
effective strategies for natal care to women.
Development of easy assessing methods, to understand these complications, like self-monitoring
of glucose, will be helpful to women and their family in the assessment of their risk level and
future prospects to control these complications.
This study would give better understanding on risk factors, management, complications, relative
measures and relationship between GDM and PIH.
4.1. Plan of the work
Figure 2: Plan of work
Explanations for terms used in the figure 2.
Early vs Late- analysis of risk factors and outcome of GDM diagnosed early and late of gestation.
Trimester – analysis of risk factors and outcome of GDM developed in three trimesters.
Treatment – analysis of outcome of pregnancy by diet vs insulin
Blood glucose – analysis of pregnancy outcome against Fasting blood glucose level
Severity – analysis of risk factors and outcome of PIH based on severity of PIH
Treatment – analysis of pregnancy outcome of PIH by anti-hypertensive drugs
5. Materials and Methods
Eligible pregnant women
(n=517)
GDM (Primary Diagnosis)
PIH (Primary Diagnosis)
(n=330)
(n=187)
GDM alone
GDM+PIH
PIH alone
(n=277)
(n=68)
(n=172)
GDM analysis
PIH analysis
Early vs late
Risk factors analysis
Severity
Trimester
Treatment
Treatment
Blood Glucose
Pregnancy outcome analysis
Developing strategies
Conclusion
5.1. Study overview
This is an observational study; the pregnant women who diagnosed and treated for Gestational
diabetes mellitus [GDM] and or Pregnancy induced hypertension [PIH] were included in the study
for the period of 10 years from January 2003 to December 2012.
The study was carried out at Kovai Medical Center and Hospital(KMCH), Coimbatore, Tamilnadu,
India, a 750 bedded multispecialty hospital. Study was approved by Institutional ethics committee.
(Ref.No. EC/AP/102/09-2009, Date - 12-08-2009)
A pregnant woman diagnosed by physician as GDM and or PIH is the basic criteria to include in the
study. Diabetes mellitus, hypertension, renal disorder, autoimmune disease woman were not
included in the study.
Totally 517 women were met the criteria and included for the study. Out of 517, 345 women were
diagnosed as GDM, 240 women were diagnosed as PIH and 68 women were diagnosed as both
GDM and PIH. Women who complicated with GDM alone are 277 and 172 women were
complicated with PIH alone.
Antenatal, perinatal and neonatal data were collected from the patients, family members, and
patient medical records and from hospital database. Maternal data includes demographic details,
family history, past medical history, obstetric history and ultra sound scanning report, laboratory
investigations and current diagnosis. Neonatal details included sex, weight, height, length, blood
group, head circumference, apgar scores, blood sugar level and bilirubin level. Data were collected
retrospectively for a period of 6 years from January 2003 to December 2008 and prospectively for
4 years from January 2009 to December 2012.
The study is divided into three sections in order to deal with the individual diagnosis. Selection
and number of study population varied with the objective of particular section.
5.2. Gestational diabetes mellitus
5.2.1. General outcome
1) Assessment of maternal and fetal characters of gestational diabetes mellitus.
Study population: - For the analysis of general characters of GDM, all the women who diagnosed
with GDM and all the GDM women who developed PIH as a complication of GDM were included in
the study. Totally 330 eligible women were taken to the analysis.
5.2.2. Risk factors
1) Assessment of risk factors for the development of GDM.
2) Is there any difference in the risk factors of women those who developed GDM early and those who developed GDM late?
3) Whether Increase in number of risk factors causing earlier development of GDM?
4) Whether increasing values of risk factors causing earlier development of GDM?
Study population: - for the analysis of all above; the GDM women and women has the
complication of both GDM and PIH, later one is developed after GDM, were included into the
study. But women who developed GDM after the PIH were not taken into the analysis, since the
risk factors may vary for primary development of complication. Totally 330 GDM women (277
GDM alone women and 53 PIH developed GDM women) were taken into the analysis.
5.2.3. Complications
1) Assessment of complication of GDM.
2) Whether the duration of GDM has any influence on the outcome of pregnancy.
3) Is there any difference between the pregnancy outcome of GDM women who treated with diet alone and along with Insulin?
4) Is there any outcome difference between the GDM women those who controlled fasting blood glucose level on or below 95mg/dl and who controlled above 95mg/dl?
5) Is there any outcome difference between early and late developed GDM?
Study population: - for the analysis of general complications, women diagnosed with GDM alone
were included in the study. Women who developed GDM along with PIH were not included in the
study, since PIH also can cause GDM like problems to pregnancy. Totally 277 GDM alone women
were taken into the analysis.
For the analysis of duration of GDM and its effect on pregnancy; women diagnosed with GDM
alone were included into the analysis (n=277). The GDM women who developed PIH were also
included while analyzing the PIH as a complication of GDM (n=330, 277 GDM alone women and 53
PIH developed GDM women). Women were categorized into three groups based on onset of GDM
through trimester of pregnancy. The groups are as follows
First Trimester Group (Group 1) – Women diagnosed with GDM through week 14.
Second trimester Group (Group 2) – Women diagnosed with GDM from week 15 to week 28.
Third trimester Group (Group 3)–Women diagnosed with GDM from week 29 through labor and
delivery, which varies considerably but average at week 40.
For the analysis of GDM treatment and its outcome; GDM only diagnosed women were taken into
the study. The eligible women were divided into two groups, one is women who received diet
alone treatment, and another is women who received insulin along with dietary treatment.
(Regular or NPH or both of the insulin were used in the individual for treatment). Totally 277 GDM
alone women were included into the analysis.
For the analysis impact of fasting blood glucose level on pregnancy outcome; women diagnosed
with GDM alone were included into the analysis. Since PIH also can cause GDM like problems to
pregnancy, GDM women who developed PIH were not included in the analysis. Mean FBS value is
considered to categorize the women into two groups. Women who controlled mean average FBS
level below 95 mg/dl is one group and another group is women who controlled mean average FBS
level on or above the 95 mg/dl. Total of 277 GDM alone women were included for grouping and
analysis. The mean FBS value is calculated from the value taken on the day next to diagnosis of
GDM to the value taken last or before the delivery.
For the analysis of outcome difference between early and late developed GDM; the GDM alone
(n=277) were included into the analysis. Since PIH also can cause GDM like problems to pregnancy,
GDM women who developed PIH were not included in the analysis.
Following are the risk factors and complications taken for the analysis
Risk factors Complications
Age Weight Body Mass Index [BMI] Previous history of GDM Family history of GDM Gravidity Parity HB Irregular menstrual cycle
PIH Cesarean section Pre term delivery Apgar score ≤7 at 1st min Apgar score ≤7 at 5th min Low birth weight (LBW) Macrosomia Large for gestational age (LGA) Small for gestational age (SGA) Hypoglycemia Hyperbilirubinemia
5.3. Pregnancy induced hypertension
5.3.1. General outcome
1) Assessment of maternal and fetal outcome of Pregnancy induced hypertension
Study population: - for the analysis of general maternal and fetal characters, all the women
diagnosed with PIH were taken into the analysis, and from the both complicating women, those
developed PIH first were considered for the analysis. Totally 187 PIH women were taken into the
analysis.
5.3.2. Risk factors
1) Assessment of risk factors for the development of PIH.
2) Assessment of risk factors for the development of PIH.
3) Whether increase in number of risk factors causing earlier development of PIH?
4) Whether increasing values of risk factors causing earlier development of PIH?
5) Are the risk factors causing variation in the severity of PIH?
Study population: - for the analysis of all above; women diagnosed with PIH and women have the
complication of both PIH and GDM, later one is developed after PIH, were included in the analysis.
But women who developed the PIH after GDM were not taken into the analysis, since the risk
factors may vary for primary development of complication. Totally 187 PIH women (172 PIH alone
Women and 15 GDM developed PIH women) were taken into the analysis.
5.3.3. Complications
1) Assessment of complications of PIH.
2) Assessment of difference between the pregnancy outcome of PIH women those who treated
with drug and those not treated with drug
Study population: - for the analysis of general complications, women diagnosed with PIH alone
were included in the study. Women who developed PIH along with GDM were not included in the
study, since GDM also can cause PIH like problems to pregnancy. Totally 172 PIH alone women
were included in the analysis.
For the analysis of treatment outcome of PIH; women diagnosed with PIH alone were included in
the study. Since GDM complications may interfere with outcome results, women diagnosed with
PIH and GDM were not included in the analysis. The PIH alone women were categorized according
to the drug they received for their treatment. The groups are as follows
Group 0 – women received none of the drug
Group 1 – women received Nifidepine
Group 2 – women received Methyldopa
Group 3 – women received Nifidepine and Methyldopa
Out of total 172 eligible women, 161 PIH women were included in the study. 7 women who
received atenolol and 2 women who received ecosprin were excluded from the analysis, 2 women
found with fetal death were also excluded from the analysis.
Following risk factors and complications were taken into analysis.
Risk factors Complications
Age Weight Body Mass Index [BMI] Previous history of PIH Family history of PIH Gravidity Parity HB Irregular menstrual cycle
Cesarean section Eclampsia Pre term delivery Apgar score ≤7 at 1st min Apgar score ≤7 at 5th min Low birth weight (LBW) IUGR Large for gestational age (LGA) Small for gestational age (SGA) Hypoglycemia Hyperbilirubinemia
5.4. Gestational diabetes mellitus and Pregnancy induced hypertension
5.4.1. General analysis
1) Assessment of maternal and fetal characteristics of women diagnosed with both complication GDM and PIH
Study population: - all the women diagnosed with PIH and GDM were included into the study.
Totally 68 women diagnosed with GDM and PIH were included in the study.
5.4.2. Risk factors
1) Assessment of risk factors for the development of both GDM and PIH together
Study population: - for the analysis of risk factors, women diagnosed with both GDM and PIH were
included in the study. Totally 68 eligible women were taken into the analysis.
5.4.3. Complications
1) Assessment of complications of women diagnosed with both PIH and GDM together.
Study population: - for the analysis of complications; women diagnosed with both GDM and PIH
were included in the study. Women diagnosed with PIH or GDM alone were excluded. Totally 68
eligible women were taken into the analysis.
Following risk factors and complications were taken into analysis.
Risk factors Complications
Age Weight Body Mass Index [BMI] Previous history of GDM and PIH Family history of GDM & PIH Gravidity Parity HB Irregular menstrual cycle
PIH Cesarean section Eclampsia Pre term delivery Apgar score ≤7 at 1st min Apgar score ≤7 at 5th min Low birth weight (LBW) Macrosomia IUGR Large for gestational age (LGA) Small for gestational age (SGA) Hypoglycemia Hyperbilirubinemia
5.5. Association
5.5.1. Assessment of association of complications GDM and PIH by risk factors
3) What are the common risk factors between GDM and PIH
4) Is there any association in the development of GDM and PIH?
5.5.2. Assessment of association of complications GDM and PIH by pregnancy outcome
3) What are the common problems in the pregnancy outcome of GDM and PIH?
4) Is there any association in the outcome of pregnancy between GDM and PIH?
Study population – for the analysis of association between GDM and PIH; women diagnosed with
GSM alone (n=277), women diagnosed with PIH alone (n=172) and women diagnosed with both
GDM and PIH (n=68) were taken into the analysis.
5.6. Definition and cutoff values for the Maternal and Fetal Analysis
1. Age – The cutoff value is 25 years(≥ 25 years of age is considered high risk)
2. BMI – The cutoff value 25 kg/m2 (≥25 is considered as high risk)
3. Previous history of GDM – woman has already experienced the GDM during her previous
pregnancy
4. Gravidity – number of pregnancy
a. Primigravida – first pregnancy
b. Multigravida – has been pregnant once (from second to all pregnancy)
5. Parity– number of delivery
a. Nulliparity – women has not given birth previously (regardless of outcome)
b. Primiparity –has given birth once
c. Multiparity – has given birth more than once
6. Family history of DM – parent of women has diabetes mellitus either mother or father
a. Paternal history – father of women has diabetes mellitus
b. Maternal history – mother of women has diabetes mellitus
7. HB – Hemoglobin more than 13 mg/dl consider as high risk group for GDM
8. Proteinuria – presence of protein in the urine more than 0.3 g/l
9. Gestational hypertension – pregnant women diagnosed after 20th week of gestation or during
labor or within 48 h of delivery with 20% increased BP but no proteinuria
10. Preeclampsia – pregnant women diagnosed after 20th week of gestation or during labor or
within 48 h of delivery with 20% increased BP and proteinuria
11. Eclampsia – pregnant women diagnosed after 20th week of gestation or during labor or within
48 h of delivery with 20% increased BP and proteinuria with seizure
12. Trimester – division of pregnancy into three months
13. The cut of values for FBS and PPBS level of GDM women are 95 mg/dl and155mg/dl (2 h post
meal) according to ADA (above this value consider as above normal)
14. Preterm delivery - the delivery before 37th week of gestation.
15. Macrosomia - the birth weight of 4000 grams or greater.
16. Hyperbilirubinemia- increase of total bilirubin level in the blood more than 12 mg/dl.
17. Neonatal hypoglycemia - capillary heel blood glucose levels of 40 mg/dl or less.
18. Maternal weight gain – is the amount of weight gained by the mother during the pregnancy
period. According to Institute of medicine and nutrition the normal maternal weight gain
during pregnancy is 11.5 – 16 kg.
19. Large for gestational age (LGA) – baby birth weight lies above the 90thpercentile of weight for
that gestational age.
20. Appropriate for gestational age (AGA) – baby birth weight lies above the 10th percentile for
that gestational age and below the 90th percentile of weight for that gestational age.
21. Small for gestational age (SGA) – baby birth weight, length or head circumference lies below
the 10th percentile of weight for that gestational age.
22. IUGR – Intrauterine growth restriction; baby birth weight is below the tenth percentile of the
average for the gestational age.
23. HELLP syndrome – hemolysis, elevated liver enzyme and low platelet count
24. Early and late GDM – universal screening for GDM is between 24 – 28 weeks. The GDM
diagnosed before 28th week of gestation is considered as ‘early GDM’ and which is after 28th
week of gestation is considered as ‘late GDM’.
25. Apgar score – is determined by evaluating the new born baby in five simple criteria on a scale
from zero to two, then summing up the five values thus obtained. The resulting apgar score
ranges from 0 to 10. Apgar score of 8 or above indicates it’s a good healthy baby. Apgar score
may be made at 1st and 5th minutes after delivery.
26. Caesarean section – is a surgical procedure in which one or more incisions are made through
mother’s abdomen (laparotomy) and uterus (hysterotomy) to deliver one or more babies or
rarely to remove dead fetus.
5.7. Statistical analysis
SPSS package version 20.0 for windows was used to do the statistical analysis. Paired‘t’ test was
used to find out the control of blood glucose level and blood pressure level before and after
treatment. Bivariate correlation (2-tailed) analysis was done to find out the correlation between
the risk factors and complications; GDM and PIH. One way ANOVA was done to find out the
significance for risk factors / outcome, between the risk factors on development of GDM and PIH,
between early and late diagnosis of GDM, between 1st, 2nd and 3rd trimester developed GDM,
between diet and insulin treatment, between the FBS level, between the severity of PIH, and
between the treatments of PIH. Non parametric Mann-Whitney U test was done to assess the risk
factors and complications between the GDM and PIH. Nonparametric Krushkal-Wallis one way
ANOVA test was used to find the relationship of risk factors and complications between GDM, PIH
and both. Regression – Curve Estimation was done to find the significance, for increasing numbers
of risk factors and effects on development of complications, increasing values of risk factors and
effects on development of complications. Multinomial Logistic Regression analysis was done to
develop the modal for prediction of complications against risk factors.
6. Results
Total of 15623 pregnant women were given birth for the period of 10 years from January 2003 to
December 2012, of which 517 women were complicated with GDM and or with PIH. The
prevalence of GDM was 2.20% (n=345) and PIH was 1.53% (n=240). Overall percentage of
coexisting of both of these complications was 0.43% (n=68).
Out of 517 complicated women, 277 women were diagnosed only with GDM and 172 women
were diagnosed only with PIH. Sixty eight (68) women were developed both GDM and PIH, of
which 53 women were developed PIH after the GDM complication and 15 women were developed
GDM after the PIH complication. Totally 517 women given birth to 537 babies. Twin pregnancy
accounted for 22 women. All neonates were normally in good except for 2 fetal deaths occurred in
PIH pregnancy. Totally 290 babies were born to GDM women and 177 babies were born to PIH
women and 70 babies were born to both complicated women. Of which 537 babies, 316 (59%)
were male babies 221 (41%) were female babies.
The prevalence rates of both complications were reduced from 2003 to 2012. The prevalence of
GDM was 3.28% in 2003 which was reduced to 2.11% in 2012 and the prevalence of PIH was 2.87%
in 2003 to 1.16% in 2012. The incidence of GDM was increases from 24 cases to 60 cases. The
same trend was found in PIH also, from 21 cases to 33 cases. – Table 4 & Graph 1.
Table – 4: Prevalence and number of cases of GDM and PIH: 2003-2012
S.no Years Number of deliveries per year
Number of GDM
cases
Number of PIH cases
Prevalence (%) PIH
Prevalence (%)
GDM 1 2003 730 24 21 2.87 3.28 2 2004 745 30 35 4.69 4.02 3 2005 867 28 24 2.76 3.22
4 2006 1075 29 19 1.76 2.69
5 2007 1273 28 22 1.72 2.19 6 2008 1554 37 22 1.41 2.38
7 2009 1897 27 21 1.1 1.42 8 2010 2187 36 21 1.0 1.64
9 2011 2452 46 25 1.01 1.87
10 2012 2843 60 33 1.16 2.11
Graph – 1: Expressing the prevalence of GDM and PIH: year vs. percentage
3.28 4.02 3.22
2.69
2.19 2.38
1.42 1.64
1.87 2.11 2.87
4.69
2.76
1.76 1.72 1.41
1.1 1 1.01 1.16
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
GDM
PIHPrevalence
Perc
enta
ge --
>
Year -->
6.1. Gestational diabetes mellitus.
Women primarily diagnosed as GDM were taken in to analysis (n=330). Maternal and fetal
characteristics were shown in – Table 5, 5A, 5B, 5C, 5D, 5E, 5F, 5G, 5H, 5I, 5J, & Graph 2, 2A, 2B,
2C, 2D, 2E, 2F, 2G, 2H.
The mean age was 27.75 ± 3.90 years. Most of the women fall between the age group of 25 to 29
years of age, which accounts for 49%. Around 6% of women were more than 35 years of old. The
mean BMI was 27.71 ± 3.61 kg/m2 of which 51% was found with obese and 20% was found to be
ideal body weight. The average weight at the time of confirmation of pregnancy was 68.05 ± 9.12
kg. The average mean weight gain was 11.77 ± 3.59 kg.
The patient history revealed that 58% of population has family history of diabetes. Paternal history
of diabetes (39%) was more compared to 31% of maternal history of diabetes. Eight percent of
population had previous history of GDM and 6% had previous history of PIH where as 93% of
population doesn’t have any previous history.
Thirty six percentage women had one previous delivery and 4% had more than one previous
delivery, where as 60% had no previous delivery. Gravidity data shows 52% of women had at least
one previous pregnancy and this is the first pregnancy for 48% of women.
Confirmation of GDM differed from woman to woman; the average week of diagnosis was 27.17 ±
8.23 week. Fifty seven percent of GDM diagnosed after the 28th week of gestation and 31% of
GDM found between 14 to 28th week of gestation where as 12% of GDM diagnosed before the 14th
week of gestation.
Women were treated with diet and as well as insulin. Regular insulin (24%), Intermediate insulin
(NPH)(42%) and sometime both insulin (15%) were used to treat. 2000 kcal to 3800 Kcal of food
were given as the diet treatment. 80% of women were received insulin and 20% of women were
received only diet treatment.
For all the GDM women glucose level was monitored regularly and was controlled well. - Table 5B,
Graph 2. The last four values of mean fasting and post prandial glucose levels were 96.67 ± 14.46
mg/dl and 140.16 ± 28.94 mg/dl respectively. The mean baseline values of, which are taken at the
time of GDM diagnosed, fasting blood sugar and post prandial blood sugar were 100.55 ± 21.81
mg/dl and 144.73 ± 34.33 mg/dl respectively. After the treatment, the mean end values of, which
are taken prior to delivery, fasting and postprandial blood glucose were 95.99 ± 24.37 mg/dl and
138.15 ± 29.70 mg/dl respectively.
The average week of delivery was 35.87 ± 2.05 weeks. Fifteen delivery was twin babies and totally
345 babies were delivered. Cesarean delivery was more with 89% and 11% of delivery was through
vaginal. Among 345 babies 208 were male and 137 were female. Mostly all babies were normally
in good health. The mean birth weight of baby was 2.72 ± 1.32 kgs. Mean Apgar score at 1st min
was 7.69 ± 0.65 and 8.58 ± 0.52 for the same at 5th min. Fifty five percentages of babies were
found with hypoglycemia and 59% of babies were found with hyperbilirubinemia.
Table – 5: Maternal Characters of GDM [n=330]
Characters Number of woman Values [Mean ± SD] / %
Age 27.75 ± 3.90 Weight 68.05 ± 9.12 Height 156.95 ± 5.34 BMI 27.71 ± 3.61 Gravidity 1.91 ± 1.10 Primigravida 159 48.18 Multigravida 171 51.81 Parity 0.46 ± 0.63 Nulliparity 196 59.39 Primiparity 120 36.36 Multiparity 14 4.24 Previous GDM 25 7.57 Family History of DM 191 57.87 No family history of DM 96 29.09 Insulin 266 80.60 NPH Insulin 139 52.25 Regular Insulin 79 29.69 Both 48 18.05 diet 64 19.40 Cesarean delivery 295 89.40 Vaginal delivery 35 10.60 PIH 53 16.06 PIH diagnosis week 33.45 ± 2.79 Marital period 4.05 ± 3.28 MWG 11.77 ± 3.59 Week of GDM diagnosis 27.17 ± 8.23 Week of delivery 35.87 ± 2.05
Table – 5A: Neonatal Characteristics of GDM [n=330]
Characters Number of Babies Values [Mean ± SD] / % Baby 345 Male baby 208 63.03 Female baby 137 41.51 Weight 2.72 ± 1.32 Term baby 168 50.90 Preterm baby 177 53.63 Apgar score at 1st minute 7.69 ± 0.65 Apgar score at 5th minute 8.58 ± 0.52 Twin babies 15 5.41 LBW 111 32.17 NBW 234 67.82 SGA 14 4.05 LGA 41 11.88 AGA 290 84.05 Macrosomia 8 2.31 Apgar score <7 at 1st minute 119 34.49 Hypoglycemia 190 55.07 Hyperbilirubinemia 202 58.55
Table – 5B: Maternal blood glucose levels
Base value mg/dl End value mg/dl
FBS 100.55 ± 21.81 95.99 ± 24.37
PPBS 144.73 ± 34.33 138.15 ± 29.70
Graph – 2 Expressing of Blood Glucose level of GDM women
100.55
144.73
95.99
138.15
0
20
40
60
80
100
120
140
160
180
FBS PPBS
Bloo
d gl
ucos
e va
lue
mg/
dl
Base
End
Table – 5C: Distribution of Sample According to the Age
S .no Age Number of patients Percentage (%) 1 ≤ 24 69 20.90 2 25 – 29 162 49 3 30 – 34 79 23 4 ≥ 35 20 6.06
Graph – 2A: Expressing percentage of woman and their age range
Table – 5D: Distribution of Sample According to the BMI
S .no BMI (kg/m2) Number of patients Percentage (%) 1 18.59 to 24.99 66 20.00 2 25 to 29.99 169 51.21 3 ≥ 30 95 28.78
Graph – 2B: Expressing percentage of woman and their BMI range
20.9
49
23
6.06
0
10
20
30
40
50
60
≤ 24 25 – 29 30 – 34 ≥ 35
% o
f wom
en
Age range
% of women/ Age
20
51.21
28.78
0
10
20
30
40
50
60
18.59 - 24.99 25 - 29.99 ≥ 30
BMI
BMI of Woman
Perc
enta
ge
Table – 5E: Average diagnosis and delivery week
S .no Diagnosis Week
1 GDM 27.17 2 PIH 33.45 3 Delivery 35.87
Graph – 2C:
Table – 5F: Family history of diabetes mellitus
S .no Family History Percentage (%) 1 Family history of DM 57.87 2 No family history of DM 29.09
Graph – 2D: Expressing Family history of diabetes mellitus
27.17
33.45 35.87
0
5
10
15
20
25
30
35
40
Week of GDM diagnosis Week of PIH diagnosis Week of Delivery
Week of diagnosis & delivery
Aver
age
Wee
k
57.87
29.09
0
10
20
30
40
50
60
70
Family history of DM No Family history
Percentage of Family history
Perc
enta
ge
Table – 5G: Types of Treatment and types of Insuli n
S .no Treatment Percentage (%) 1 Insulin 80.60 2 NPH Insulin 52.25 3 Regular Insulin 29.70 4 Both Insulin 18.05 5 Diet 19.40
Graph – 2E: Expressing Type of treatment and Type of Insulin
Table – 5H: Mode of delivery S .no Delivery Percentage (%)
1 Cesarean 89.40 2 Normal 10.60
Graph – 2F: Expressing Mode of Delivery
80.6
19.4
52.25
29.7
18.05
0
10
20
30
40
50
60
70
80
90
Insulin NPH Insulin Regular Insulin Both Insulin Diet
Type of TreatmentType of Insulin
Perc
enta
ge
80.6
10.4
Cesarean
Normal
Percentage of Mode of Delivery
Table – 5I: Preterm and term delivery
S .no Delivery Percentage (%)
1 Preterm 51 2 Term 49
Graph – 2G: Expressing preterm and term delivery
Table – 5J: Distribution of baby according to Size
S .no Size of baby Percentage (%)
1 SGA 4.05 2 LGA 11.88 3 AGA 84.05 4 Macrosomia 2.31
Graph – 2H: Expression percentage of baby according to Size
term 49% preterm
51%
Type of delivery
4.05 11.88
84.05
2.31 0
10
20
30
40
50
60
70
80
90
SGA LGA AGA Macrosomia
Perc
enta
ge --
->
Size of Baby
6.2. Pregnancy induced hypertension
Women primarily diagnosed as PIH were taken in to analysis (n=187). Maternal and fetal
characteristics were shown in – Table 6, 6A, 6B, 6C, 6D, 6E, 6F, 6G & Graph 3,3A, 3B, 3C, 3D.
Out of the 187 PIH diagnosis 61 (33.62%) was gestational hypertension and 125 (66.84%) was
preeclampsia. Based on the severity of disease 61 (33.62%) had gestational hypertension, 38
(20.32%) had mild-preeclampsia, 67 (35.82%) had severe-preeclampsia and 20 (11.69%) had
eclampsia.
The mean age of women was 26.55 ± 4.55 years. Most of the women fall between the age group
of 22 to 25 years of age, which accounts for 40% of population. Five percentages of women were
more than 35 years of old. The mean BMI was 25.60 ± 4.57 kg/m2. Forty five percent of women
found with obese and 37% women were found to be ideal body weight.
The patient history revealed that 30.48% of population has family history of DM and 31% has
family history of HTN. Eleven percent of women had previous history of PIH and 2% women had
previous history of GDM where as 55% of women doesn’t have any previous history.
Regarding parity, 20% of women had one previous delivery and 6% of women had more than one
previous delivery, where as 74% women have no previous history of delivery. Gravidity data
showed 42% of women had at least one previous pregnancy and 58% of women had the first
pregnancy. The average weight at the time of confirmation of pregnancy was 63.51 ± 12.06 kg. The
average maternal weight gain was 13.40 ± 4.6 kg.
Confirmation of PIH differed from woman to woman; the average week for diagnosis of PIH was
31.76 ± 6.71 weeks. The diagnoses of PIH before and after the 20th week of gestation were found
to be 12% and 88% respectively.
Eighty two percent of women were treated by drugs for PIH complication and 18% of women were
not treated by any drugs. The drugs used for the treatment are methyldopa-250 mg, 500 mg
(28.35%), nifedipine- 5 mg, 10 mg (26.73%), atenolol- 50 mg and ecospirin- 75 mg. around 21% of
women received both the drugs methyldopa and nifedipine.
Blood pressure (BP) for all the PIH women was monitored regularly and it was controlled well. The
overall mean morning, mid-day and night time blood pressure levels were 133.62/88.98 ±
(15.44/9.02), 132.62/88.57 ± (16.32/9.88) and 133.77/89.03 ± (1.99/7.71) respectively.
The mean baseline blood pressure values of, which are taken at the time of PIH diagnosed,
morning, mid-day and night time were 133.44/88.74 ± (16.01/10.26), 134.66/90.20 ±
(20.20/11.37) and 132.44/88.37 ± (14.95/10.00) respectively. The mean end values were which are
taken prior to delivery, 134.06/89.72 ± (17.59/10.71), 134.35/88.75 ± (16.32/9.88) and
131.13/86.72 ± (14.21/10.17) respectively. Post-partum BP was taken immediately, 3 h and 7 h of
post-partum; the values are 133.44/88.85 ± (15.83/9.95), 131.14/85.77 ± (13.31/9.08) and
130.33/84.73 ± (12.52/6.47) respectively.
Total of 187 PIH women were given birth to 194 infants. The average week of delivery was 34.74 ±
3.70 weeks. Ninety five percent of women given birth through cesarean delivery whereas only 5%
of women delivered through vaginal. Of the 194 babies 7 were twin babies. Two fetal deaths were
reported and totally 192 live babies were delivered. About 108 male babies and 84 female babies
were born. Babies mean birth weight was 2.20 ± 0.75kgs. Mean Apgar score at 1st min was 7.77 ±
0.78 and 8.36 ± 0.59 for the same at 5th min. Preterm babies were accounted to 65.62%. Small for
gestational age babies (SGA) were 36.45% and 26% of IUGR was recorded.
Table – 6: Maternal Characteristics of PIH (n=187)
Characters Number of woman Values [Mean ± SD] / %
Age (year) 26.55 ± 4.55 Weight (kg) 63.51 ± 12.6 Height (cm) 157.36 ± 6.33 BMI (kg/m2) 25.60 ± 4.579 Gravidity 1.63 ± 0.97 Primigravida 109 58.28 Multigravida 78 41.71 Parity 0.35 ± 0.69 Nulliparity 138 73.79 Primiparity 37 19.78 Multiparity 12 6.41 Previous PIH 21 11.22 Family History of HTN 57 30.48 No family history of HTN 130 69.51 Marital period (year) 3.79 ± 3.09 MWG (kg) 13.40 ± 4.60 Week of PIH diagnosis 31.76 ± 6.74 Week of delivery 34.74 ± 3.70 Methyldopa 53 28.35 Nifedipine 50 26.73 Both (M.Dopa+Nifedipine) 39 20.85 None (No drug) 34 18.18 Cesarean delivery 177 94.65 Vaginal delivery 10 5.34
Table – 6A: Neonatal Characteristics of PIH [n=187]
Characters Number of Babies Values [Mean ± SD] / % Baby 192 Male baby 108 56.25 % Female baby 84 43.75 % Weight 2.20 ± 0.75 Term baby 66 34.37 % Preterm baby 126 65.62 5 Apgar score at 1st minute 7.77 ± 0.78 Apgar score at 5th minute 8.36 ± 0.59 Twin babies 7 3.74 % LBW 112 58.33 % NBW 80 41.67 % SGA 70 36.45 % LGA 8 8.69 % AGA 114 59.37 % IUGR 26 26 % Apgar score <7 at 1st minute 62 32.29 % HELLP 3 1.56 %
Table – 6B: Maternal Blood pressure level
Blood pressure Base line value (mmHg) systolic/diastolic ± (SD)
End value (mmHg) systolic/diastolic ± (SD)
BP – morning 133.44/88.74 (16.01/10.26) 134.06/89.72 (17.59/10.71)
BP – midday 134.66/90.20 (20.20/11.37) 134.35/88.75 (16.97/10.78)
BP – night 132.44/88.37 (14.95/10.00) 131.13/86.72 (14.21/10.17)
BP – delivery (postpartum) 134.67/87.85 (15.85/10.21) BP – delivery (3 h postpartum) 131.14/86.37 (14.27/9.71) BP – delivery (7 h postpartum) 130.33/84.86 (12.10/7.98)
Table – 6C: Distribution of Sample According to the Age
S .no Age Number of patients Percentage (%)
1 ≤ 24 69 20.90 2 25 – 34 103 55.38 3 ≥ 35 14 7.53
Graph – 3: Expressing percentage of woman and their age range
Table – 6D: Distribution of sample according to the BMI
S .no BMI (kg/m2) Number of patients Percentage (%)
1 <18.59 2 1.07%
2 18.59 to 24.99 96 51.61%
3 25 to 29.99 58 31.18%
4 ≥ 30 30 16.12%
Graph – 3A: Expressing percentage of woman and their BMI range
37.09%
55.38%
7.53%
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
≤ 24 25 – 34 ≥ 35
Percentage (%)
1.07%
51.61%
31.18%
16.12%
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
<18.59 18.59 to 24.99 25 to 29.99 ≥ 30
Percentage (%)
BMI of Women (PIH)
Age of women (PIH)
Table – 6E: Type of Gravidity S .no Gravidity Percentage
1 Primigravidity 60.96% 2 Multigravidity 39.04%
Graph – 3B: Expressing type of gravidity in percentage
Table – 6F: Type of Parity
S .no Parity Percentage
1 Primiparity 19.78% 2 Multiparity 6.41% 3 Nulliparity 73.79%
Graph – 3C: Expressing type of Parity in percentage
60.96%
39.04%
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
Primigravidity Multigravidity
Perc
enta
ge --
->
19.78%
6.41%
73.79%
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
Primiparity Multiparity Nulliparity
Perc
enta
ge --
->
Parity
Type of Gravidity (PIH)
Table – 6G: Family History of HTN
S .no Family History Percentage (%)
1 Family history of HTN 30.48%
2 No family history of HTN 69.52%
Graph – 3D: Expressing family history of HTN of PIH women in percentage
30.48%
69.52%
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
Family history of HTN No family history of HTN
Perc
enta
ge --
->
6.3. Gestational diabetes mellitus and Pregnancy induced hypertension
Women diagnosed with GDM and PIH were taken in to analysis (n=68). Maternal and fetal
characteristics were shown in – Table 7, 7A, 7B, 7C, 7D, 7E, 7F, 7G, 7H, 7I & Graph 4, 4A, 4B, 4C,
4D, 4E, 4F, 4G.
Total of 68 women found with GDM and PIH of which 53 women were developed GDM first then
PIH whereas 15 women were developed PIH first then GDM. The mean age of women was 29.60 ±
4.52 years. Most of the women fall between the age group of 28 to 32 years of age, which
accounts for 46%. Twenty four percent of women were more than 33 years of old. About 90% of
women’s age was more than 25 years. The mean BMI was 27.95 ± 3.88 kg/m2. Obese population
accounts for 79% and 20% were found to be ideal body weight.
The patient history revealed that 70.58% of women had family history of diabetes and 47% women
had family history of hypertension. Seventeen percent of women don’t have any family history of
diabetes or hypertension. Nine percent of women had previous history of GDM and 20.58% of
women had previous history of PIH where as 70.58% of women doesn’t have any history of GDM
or PIH.
Regarding parity, 59% of populations are nulliparous, 37% are primiparous and 4% were
multiparous. Gravidity data shows 59% of women had at least one previous pregnancy and for
41% of women this is the first pregnancy. The average weight at the time of confirmation of
pregnancy was 70.49 ± 10.43 kg. The average maternal weight gain was 10.48 ± 3.60 kg.
Confirmations of complications were differed from woman to woman; the average week for
diagnosis of GDM was 27.10 ± 7.46 weeks and for PIH diagnosis was 29.89 ± 8.32 weeks. GDM was
diagnosed first for 78% women whereas 22% of women were diagnosed PIH first.
GDM was managed with diet and insulin. Insulin was given to 75% of women and diet was used to
25% of women as a treatment. Regular insulin, Intermediate insulin (NPH) and sometime both
insulin were used to treat GDM women. All the dietary treated GDM were received 2000 kcal to
3800 Kcal of food the diet treatment. For the management of PIH Methyldopa (250 mg, 500 mg)
and Nifedipine (5 mg, 10 mg) were used. Thirty seven percent of women were received
Methyldopa, 20.58% of women were received Methyldopa and Nifedipine, 7.75% of were received
Nifedipine and 35.29% of women were received none of the drug for their PIH treatment.
The glucose level was monitored regularly and was controlled well. The last four values of mean
fasting and post prandial glucose levels were 100.83 ± 10.22 mg/dl and 144.10 ± 30.05 mg/dl
respectively. The mean baseline values of, which are taken at the time of GDM diagnosed, fasting
blood sugar and post prandial blood sugar are 101.76 ± 19.28 mg/dl and 135.57 ± 28.09 mg/dl
respectively. The mean end values of, which are taken prior to delivery, fasting and postprandial
blood glucose were 101.54 ± 16.83 mg/dl and 134.15 ± 24.99 mg/dl respectively. The mean
baseline BP taken in the morning was 134.60/89.19 ± (21.18/12.55) mm Hg and end value was
135.98/86.10 ± (16.67/12.16) mm Hg. The immediate post-partum BP was 137.85/89.14 ±
(16.48/7.82) mm Hg and the same was reduced to 129.64/85.05 ± (8.66/7.28) 7 h of post-
partum.
The average week of delivery was 34.60 ± 4.00 weeks. Totally 70 babies were delivered of which 2
deliveries were twin babies. About 40 male babies and 30 female babies were born. Babies mean
birth weight was 2.45 ± 0.81 kgs. Mean Apgar score at 1st min was 7.55 ± 0.67 and 8.38 ± 0.58 for
the same at 5th min. Preterm delivery was 61.76%. SGA was 17.64% and LGA was 11.76%. Fifteen
percent of IUGR was recorded. 45.58% of babies were found with hypoglycemia and 61.76% of
babies were found with hyperbilirubinemia.
Table – 7: Maternal characters of GDM + PIH [n=68]
Characters Number of woman Values [Mean ± SD]/ %
Age (year) 29.60 ± 4.52 Weight (kg) 70.49 ± 10.43 Height (cm) 158.65 ± 5.7 BMI (kg/m2) 27.95 ± 3.88 Gravidity 2.0 ± 1.13 Primigravida 28 41.17 % Multigravida 40 58.82 % Parity 0.45 ± 0.58 Nulliparity 40 58.82 % Primiparity 25 36.76 % Multiparity 3 5.88 % Previous GDM 6 8.82 % Previous HTN 14 20.58 % Family History of DM 48 70.58 % Family History of HTN 32 47.05 % No family history of DM/HTN 12 17.64 % Marital period (year) 5.80 ± 4.15 MWG (kg) 10.48 ± 3.6 Week of GDM diagnosis 27.10 ± 7.46 Week of PIH diagnosis 29.89 ± 8.32 Average Interval for diagnosis 5.79 ± 5.58 week Week of delivery 34.60 ± 4.00 Insulin 51 75 % diet 17 25 % Antihypertensive drugs 44 64.70 % Cesarean delivery 68 100 % Vaginal delivery 0 0 %
Table – 7A: Neonatal Characteristics of GDM and PIH [n=68]
Characters Number of Babies Values [Mean ± SD] / % Baby 70 Male baby 40 57.14 % Female baby 30 42.85 % Weight 2.45 ± 0.81 Term baby 26 38.23 % Preterm baby 42 61.76 % Apgar score at 1st minute 7.55 ± 0.67 Apgar score at 5th minute 8.33 ± 0.58 Twin babies 2 2.94 % LBW 32 47.05 % NBW 36 51.42 % SGA 12 17.64 % LGA 8 11.76 % AGA 50 73.52 % IUGR 10 14.70 % Macrosomia 2 2.94 % Apgar score <7 at 1st minute 62 32.29 % HELLP 3 1.56 % Hypoglycemia 31 45.58 % Hyperbilirubinemia 42 61.76 %
Table – 7B: Distribution of Sample According to the Age
S .no Age Number of patients Percentage (%)
1 ≤ 24 7 10.29%
2 25 – 34 50 73.52%
3 ≥ 35 11 16.17%
Graph – 4: Expressing distribution of age in percentage in GDM+PIH women
Table – 7C: Distribution of Sample According to the BMI
S .no BMI (kg/m2) Number of patients Percentage (%)
1 18.59 to 24.99 13 19.11%
2 25 to 29.99 34 50%
3 ≥ 30 21 30.88%
Graph – 4A: Expression of GDM+ PIH women by BMI (n=68)
10.29%
73.52%
16.17%
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
≤ 24 25 – 34 ≥ 35
Perc
enta
ge
% of Age
19.11%
50%
30.88%
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
18.59 to 24.99 25 to 29.99 ≥ 30
Perc
enta
ge
BMI
Table – 7D: Average diagnosis and delivery week
S .no Diagnosis Week 1 GDM 30.16 ± 5.18 2 PIH 33.71 ± 4.25 3 Delivery 34.60 ± 4.00
Graph – 4B: Distribution of diagnosis and delivery of GDM+ PIH women
Table – 7E: Family history of DM and HTN
S .no Family History Percentage (%)
1 Family history of DM 70.58%
2 Family history of HTN 47.05%
3 Family history of DM/HTN 80.88%
Graph – 4C: Positive Family history of GDM+ PIH women
30.16 33.71 34.6
0
5
10
15
20
25
30
35
40
45
GDM PIH Delivery
Wee
k
Week
DM 35%
HTN 24%
Both 41%
Family history in percentage
Table – 7F: Mode of delivery
S .no Delivery Percentage (%)
1 Cesarean 100%
2 Normal 0%
Graph – 4D: Expressing mode of delivery
Table – 7G: Distribution of sample according to parity
S .no Parity Percentage
1 Primiparity 36.76%
2 Multiparity 4.41%
3 Nulliparity 58.82%
Graph – 4E: Expressing Type of Parity
Cesarean, 100%
Cesarean
36.76%
4.41%
58.82%
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
Primiparity Multiparity Nulliparity
Perc
enta
ge --
->
Percentage
Table – 7H: Distribution of sample according to Gravidity
S .no Gravidity Percentage
1 Primigravidity 41.17%
2 Multigravidity 58.83%
Graph – 4F: Expressing Type of Gravidity
Table – 7I: Distribution of baby by gender
S .no Baby Number of babies
1 Male 40
2 Female 30
3 Twin MM 1
4 Twin MF 1
Graph – 4G: Expressing Number of babies by gender
41.17%
58.83%
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
Primigravidity Multigravidity
Perc
enta
ge --
->
Percentage
40
30
1 1 0
5
10
15
20
25
30
35
40
45
Male Female Twin MM Twin MF
Num
ber -
-->
Number of babies
6.4. Analysis
6.4.A. Individual analysis
6.4.A.1. Gestational diabetes mellitus
6.4.A.1.a. Diet vs. Insulin 6.4.A.1.b. 1st vs. 2nd vs. 3rd trimester 6.4.A.1.c. Early vs. Late onset 6.4.A.1.d FBS ≤ 95 mg/dl vs. FBS ≤ 95 mg/dl
6.4.A.2. Pregnancy induced Hypertension (PIH)
6.4.A.2.a. Treatment comparison 6.4.A.2.b. Severity comparison
6.4.B. Comparison analysis
6.4.B.1. Risk factors 6.4.B.2. Complications 6.4.B.3. Association
General characters of Maternal and neonatal were presented in - Table 8 and 8A.
Table – 8: Maternal characteristics of GDM, PIH and GDM + PIH women
values are expressed in percentage and mean ± SD
Characters GDM n=277) PIH (n=172) GDM & PIH (n=68)
Age (year) 27.45 ± 3.78 26.55 ± 4.55 29.60 ± 4.52 Weight (kg) 67.93 ± 9.26 63.51 ± 12.6 70.49 ± 10.43 BMI (kg/m2) 27.77 ± 3.94 25.60 ± 4.579 27.95 ± 3.88 Gravidity 1.91 ± 1.11 1.63 ± 0.97 2.0 ± 1.13 Primigravida 40.09 % 62.79 % 41.17 % Multigravida 50. 90 % 37.20 % 58.82 % Parity 0.46 ± 0.65 0.35 ± 0.69 0.45 ± 0.58 Nulliparity 60.28 % 73.83 % 58.82 % Primiparity 35.01 % 20.34 % 36.76 % Multiparity 13 % 5.81 % 5.88 % Previous GDM 7.94% 0.581% 8.82% Previous HTN 3.24% 11.22% 20.58% Family History of DM 57.03% 26.16% 8.82% Family History of HTN 30.68% 26.74% 20.58% Marital period (year) 3.79 ± 3.09 3.79 ± 3.09 5.80 ± 4.15 MWG (kg) 11.87 ± 3.65 13.40 ± 4.60 10.48 ± 3.6 Week of GDM diagnosis 27.01 ± 8.51 30.16 ± 5.18 Week of PIH diagnosis 31.76 ± 6.74 29.89 ± 8.32 Week of delivery 36.28 ± 1.99 34.74 ± 3.70 34.60 ± 4.00 Hb (gm/dl) 11.45 ± 1.24 11.54 ± 1.52 11.87 ± 1.03 Irregular Menstrual cycle 36.10 % 17.63 % 44.11 % Insulin 80.50% 75% Diet 19.49% 25% Methyldopa 28.355% Nifedipine 26.73% Methyldopa + Nifedipine 20.85% None (No drug) 18.18% Caesarean delivery 87.36% 94.65% 100% Vaginal delivery 12.63% 5.81 % 0%
Table – 8A: Neonatal characters of women of GDM, PIH and GDM+PIH
Characters Neonates of GDM alone (n=290)
Neonates of PIH alone (n= 177)
Neonates of GDM+PIH (n=68)
Male baby 60 % 57.62 % 57.14 % Female baby 40 % 43.50 % 42.85 % Weight 2.67 ± 0.65 2.22 ± 0.73 2.45 ± 0.81 Term baby 50.34 % 35.02 % 38.23 % Preterm baby 48.96 % 64.97 % 61.76 % Twin babies 4.69 % 4.06 % 2.94 % LBW 33.79 % 55.86 % 47.05 % NBW 66.2 % 43.5 % 51.42 % SGA 2.75 % 37.28 % 17.64 % LGA 12.06 % 2.82 % 11.76 % AGA 80.68 % 59.88 % 73.52 % IUGR 0 % 12.99 % 14.70 % Macrosomia 2.06 % 0.56 % 2.94 % Apgar score <7at 1st mint 24.13 % 28.81 % 32.29 % HELLP 0 % 1.12 % 1.56 % Hypoglycemia 55.51 % 0 45.58 % Hyperbilirubinemia 56.55 % 0 61.76 %
values are expressed in percentage and mean ± SD
6.4.A. Individual analysis 6.4.A.1. GDM 6.4.A.1.a. Diet vs. Insulin
GDM diagnosed women treated with diet alone and along with insulin also. To analyze the
maternal and fetal outcome of GDM treatment, GDM alone diagnosed (n=277) populations were
categorized into two groups as diet alone and along with insulin received groups. For the analysis
of PIH as a complication of GDM, the GDM women who developed PIH were also included to the
analysis (n=330).
Among 277 GDM cases 57 (20.57%) were received diet alone as a treatment and 223 (80.50%)
were received insulin along with diet as a treatment. The glucose level controlled well for both
groups. The base and end value of FBS for diet and insulin groups were 96.70 ± 17.03, 92.12 ±
28.16 and 101.26 ± 24.76, 94.95 ± 23.21 respectively. The base and end value of PPBS for diet and
insulin groups were 143.96 ± 30.50, 142.03 ± 31.36 and 146.73 ± 39.14, 136.10 ± 28.70
respectively.
Maternal and fetal outcome of these two groups doesn’t showed significant difference except for
cesarean delivery and preterm delivery. Types of treatment not have shown any difference in
pregnancy outcome. Cesarean deliveries were more with insulin group, nearly 93% of women
given birth through cesarean delivery. Only 19% were cesarean delivery from diet alone group.
Around 62% of babies were delivered as preterm in insulin group and 43% of babies were
delivered as preterm in diet alone group. Average week of diagnosis and delivery were 29.88 ±
6.25, 36.62 ± 1.95 and 26.31 ± 8.85, 35.78 ± 2.05 respectively for diet and insulin groups. Around
3% of macrosomic babies were found with insulin group whereas no babies were found with
macrosomia in diet alone group. Hypoglycemic and hyperbilirumic state of neonates were equally
distributed between the groups around 56% of neonates were found with hypoglycemia and
hyperbilirubinemia in both groups. In diet alone group 22% of women developed PIH and 18% of
women developed PIH in insulin group. Details were recorded in Table 9, 9A, 9B & Graph 5, 5A.
Table – 9: Details of GDM women treated with diet and Insulin.
Statistics value for ANOVA – P value expressed for significance. * P value is significant,
Diet(54) Insulin(223) P - value Age (year) 27.62 ± 4.06 27.40 ± 3.72 BMI (kg/m2) 26.86 ± 3.92 27.99 ± 3.52 week of diagnosis 29.88 ± 6.25 26.31 ± 8.85 week of delivery 36.62 ± 1.95 35.78 ± 2.05 weight of baby 2.69 ± 0.52 2.67 ± 0.68 MWG (kg) 12.09 ± 3.21 11.84 ± 3.74 FBS (mg/dl) Base 96.70 ± 17.03 101.26 ± 24.76 End 92.12 ± 28.16 94.95 ± 23.21 FBS L4 98.32 ± 20.79 96.52 ± 18.62 P = 0.534 PPBS Base 143.96 ± 30.50 146.73 ± 39.14 End 142.03 ± 31.36 136.10 ± 29.20 PPBS L4 140.33 ± 28.77 139.04 ± 28.70 P = 0.767 Caesarean delivery 10 (18.51%) 207 (92.82%) P = 0.000* Vaginal delivery 44 (81.48%) 16 (7.17%) Apgar score <7at1st min 20 (34.48%) 82 (35.34%) P = 0.971 Preterm delivery 25 (43.1%) 143 (61.63%) P = 0.016* Term delivery 33 (61.11%) 89 (39.91%) LBW (kg) 19 (32.75%) 73 (31.46%) P = 0.733 NBW (kg) 39 (72.22%) 159 (71.30%) SGA 1 (1.72%) 7 (3.01%) LGA 5 (8.62%) 30 (12.93%) P = 0.407 AGA 52 195 Macrosomia 0 6 (2.58%) P = 0.224 Hypoglycaemia 32 (55.17%) 129 (55.6%) P = 0.851 Hyperbilirubinemia 30 (51.62%) 134 (57.75%) P = 0.545
Table – 9A: Distribution of Mode of delivery between Diet and Insulin
Diet Insulin Statistics value Cesarean delivery 18.51 % 92.82 % P = 0.000
Graph – 5: Expressing of Mode of delivery between Diet and Insulin
Table – 9B: Distribution of Preterm delivery between Diet and Insulin Diet Insulin Statistics value Preterm 43.1 % 61.63 % P = 0.01
Graph – 5A: Distribution of Preterm deliveries between Diet and Insulin
Diet 17%
Insulin 83%
Cesarean Delivery
Diet 41%
Insulin 59%
Preterm
6.4.A. Individual analysis 6.4.A.1. GDM 6.4.A.1.b. 1st vs. 2nd vs. 3rd trimester
Usually GDM diagnosis at 24th to 28th week of gestation but during the gestation it can occur any
time. The duration of GDM is more with women who diagnosed GDM at 1st trimester of pregnancy
than women who diagnosed GDM at 2nd or 3rd trimester of pregnancy. This change in the length of
GDM may or may not influence the outcome of pregnancy. To analyze the impact of duration of
GDM on pregnancy outcome population (n=277) were categorized into three groups according to
the week of diagnosis through trimester basis. Women diagnosed GDM before the 14th week of
gestation grouped as 1st trimester group, and those diagnosed between 14th and 28th week of
gestation comes under 2nd trimester group, women diagnosed after the 28th week of gestation
through delivery were grouped as 3rd trimester group.
Among 277 GDM cases 36 (13%) were found at 1st trimester, 88 (32%) were found at 2nd trimester
and 153 (55%) were found at 3rd trimester of the pregnancy. The average week of diagnosis of
each group was 10.00 ± 2.87, 23.63 ± 4.10 and 33.05 ± 2.34 respectively. The average delivery
week of each group was 35.61 ± 1.85, 36.06 ± 1.99 and 36.00 ± 2.10 respectively. Maternal and
fetal data were shown in – Table 10, 10A, 10B, 10C, 10D & Graph 6, 6A, 6B, and 6C. Age,
Gravidity and Parity shows significant influence on the early development of GDM, other risk
factors doesn’t show significant influence on the early development of GDM. The average age of
1st trimester group women was 28.88 ± 4.25 years, which is high to compare 2nd (27.59 ± 3.77) and
3rd (27.02 ± 3.81) trimester groups’ women. The average number of risk factors for 1st trimester
group was 4.22 which were high to compare with 3.88 and 3.45 for 2nd and 3rd trimester groups
respectively.
The maternal and fetal outcome doesn’t show significant difference between these three groups
except for LGA and AGA. The duration or length of GDM doesn’t affect the outcome of
pregnancy. The 1st trimester group had more LGA babies (19.44%) than 2nd (5.49%) and 3rd
(14.54%) trimester groups. All babies were normally in good health, the average baby weight of
each group was 2.75 ± 0.54, 2.63 ± 0.60 and 2.70 ± 0.69 years respectively.
Table – 10 Details of women diagnosed GDM at 1st, 2nd and 3rd trimester
1st trim(36) 2nd trim(88) 3rd trim(153) Value
Age 28.88 ± 4.25 27.59 ± 3.77 27.02 ± 3.81 P = 0.024* BMI 27.78 ± 2.91 27.68 ± 3.82 27.74 ± 3.59 P = 0.997 Gravidity 2.38 ± 1.07 1.76 ± 1.10 1.88 ± 1.09 Primigravida 22.23 % 56.82 % 50.31 % P = 0.002* Multigravida 77.77 % 43.18 % 49.69 % P = 0.002* Parity 0.63 ± 0.48 0.43 ± 0.60 0.44 ± 0.71 Nulliparity 36.11 % 62.5 % 64.51 % P = 0.005* Primiparity 63.88 % 31.81 % 30.32 % P = 0.001* Family History DM 61.11 % 50 % 59.35 % P = 0.306 Irreg. Menstrual 33 % 39.77 % 34.64 % P = 0.680 FBS
Base 106.69 ± 34.44 98.96 ± 24.33 99.62 ± 21.47 End 102.36 ± 32.95 93.27 ± 18.91 93.03 ± 24.95 FBS L4mean 103.33 ± 31.00 95.63 ± 14.63 95.98 ± 12.08 P = 0.095 PPBS
Base 155.13 ± 31.00 145.37 ± 35.67 145.00 ± 37.64 End 136.52 ± 26.93 133.76 ± 25.37 139.46 ± 32.36 PPBS L4mean 136.25 ± 24.89 135.37 ± 22.67 142.01 ± 32.22 P = 0.674 Caesarean 31 (86.11%) 72 (81.11%) 141 (92.15%) P = 0.084 Vaginal 5 16 14 Term 14 37 70 P = 0.706 Preterm 22 (61.11%) 54 (59.34%) 95(58.28%) P = 0.515 LBW 8 (22.22%) 38 (41.75%) 52 (33.54%) P = 0.084 NBW 28 53 111 SGA 0 2 (2.19%) 6 (3.72%) P = 0.414 LGA 7 (19.44%) 5 (5.49%) 24 (14.54%) P = 0.046* AGA 29 84 135 P = 0.034* Macrosomia 0 1(1.09%) 5 (3.06%) P = 0.792 Apgar<7at 1st min 12 (33.33%) 35 (38.46%) 52 (31.05%) P = 0.527 HypoGlycemia 18 (50%) 50 (54.94%) 97 (60.24%) P = 0.277 HyperBilirubinemia 15 (41.66%) 57 (62.66%) 91 (56.52%) P = 0.059 Insulin 33 (91.66%) 74 (84.09%) 118 (74.12%) P = 0.074 Diet 3 14 37 Baby 36 91 163 twin 0 3 10
Statistics value for ANOVA – P value expressed for significance. * P value is significant,
Table – 10A: Distribution of Gravidity of all trimesters GDM women 1st trim(36) 2nd trim(88) 3rd trim(153) Value
Gravidity 2.38 ± 1.07 1.76 ± 1.10 1.88 ± 1.09 Primigravida 22.23 % 56.82 % 50.31 % P = 0.002* Multigravida 77.77 % 43.18 % 49.69 % P = 0.002*
Graph – 6: Expressing gravidity of all trimesters GDM women
Table – 10B: Distribution Parity of all trimesters GDM women
1st trim(36) 2nd trim(88) 3rd trim(153) Value
Parity 0.63 ± 0.48 0.43 ± 0.60 0.44 ± 0.71 Nulliparity 36.11 % 62.5 % 64.51 % P = 0.005* Primiparity 63.88 % 31.81 % 30.32 % P = 0.001*
Graph – 6A: Expressing parity of all trimesters GDM women
22.23
77.77
56.82
43.18 50.31 49.69
0
10
20
30
40
50
60
70
80
90
Primigravida Multigravida
Perc
enta
ge --
->
1st
2nd
3rd
36.11
63.88 62.5
31.81
64.51
30.32
0
10
20
30
40
50
60
70
Nulliparity Primiparity
Perc
enta
ge --
->
1st
2nd
3rd
% of women
Table – 10C: Average age of all trimesters GDM women
1st trim(36) 2nd trim(88) 3rd trim(153) Value
Age (year) 28.88 ± 4.25 27.59 ± 3.77 27.02 ± 3.81 P = 0.024*
Graph – 6B: Expressing average age of all trimesters GDM women
Table – 10D: Distribution of LGA, AGA babies of all trimesters GDM women
1st trim(36) 2nd trim(88) 3rd trim(153) Value
LGA 7 (19.44%) 5 (5.49%) 24 (14.54%) P = 0.046* AGA 29 (80.55%) 84 (95.45%) 135 (88.23%) P = 0.034*
Graph – 6C: Expressing percentage of LGA, AGA babies of all trimesters GDM women
28.88 27.59 27.02
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Average Age
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19.44
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88.23
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% of Babies
6.4.A. Individual analysis 6.4.A.1. GDM 6.4.A.1.c. Early vs. Late onset
The outcome of GDM pregnancy varies with early and late onset of GDM. Same way the
influencing factors also varies for early and late onset. This analysis was done in order to
understand the difference in risk-factors and outcomes between early and late onset of GDM.
Based on the week of diagnosis women were categorized into two groups. Women identified GDM
before 28th week of gestation considered as early onset and women identified GDM after 28th
week of gestation considered as late onset. For the comparison of risk-factors and outcome
women diagnosed with GDM alone (n=277) were taken to analysis.
Maternal and fetal characteristics of population were shown in – Table 11, 11A, 11B, 11C & Graph
7, 7A. Among 277 GDM cases 124 (45%) had the early onset and 153 (55%) had late onset.
Advancing age and primiparity shows significant influence on early development of GDM
whereas other risk-factors doesn’t show influence on early development. The average age of early
onset group was high (27.96 ± 3.68) compared to late onset group (27.02 ± 3.81). Forty two
percent of primiparity women had early onset of GDM and 31% of women had late onset of GDM.
The average parity of early onset women was 0.49 ± 0.57 and for late onset women was 0.44 ±
0.71.
Maternal and fetal outcome of these two groups don’t have significant difference except for
cesarean delivery and the insulin usage. The pregnancy outcome was same between early and
late developing GDM. Cesarean delivery was more with late onset of GDM (92%) compared to
early onset of GDM (83%). In early onset group around 86% of women received insulin for their
treatment whereas 76% of women received insulin in late onset group. Around 21% of women
from late onset group developed PIH whereas 17% of women from early onset group developed
PIH.
Table – 11: Details of women developed GDM early and late
Statistics value for ANOVA – P value expressed for significance.* P value is significant
Early(124) Late(153) P – value
Age (year) Risk level
27.96 ± 3.68 100 (80.64%)
27.02 ± 3.81 113 (73.85%)
P = 0.030*
BMI (kg/m2) Risk level
27.71 ± 3.57 100 (80.64%)
27.74 ± 3.59 121 (79.08%)
P = 0.933
Gravidity 1.94 ± 1.12 1.88 ± 1.09 P = 0.627 Primigravida 58 (46.77%) 78 (50.98%) P = 0.318 Multigravida 66 (53.22%) 75 (49.01%) P = 0.318 Parity 0.49 ± 0.57 0.44 ± 0.71 P = 0.140 Nulliparity 68 (54.83%) 99 (64.7%) P = 0.767 Primiparity 51 (42.12%) 47 (30.71%) P = 0.005* Multiparity 5 (4.03%) 7 (4.47%) Family History DM 66 (53.22%) 72 (47.05%) P = 0.308 Father DM 48 (38.7%) 54 (35.29%) P = 0.690 Mother DM 31 (25%) 50 (32.67%) P = 0.110 Previous GDM 8 (6.45%) 13 (8.49%) P = 0.523 HB 9 (7.25%) 13 (8.49%) P = 0.368 Irregular Menstrual cycle 47 (37.9%) 53 (34.64%) week of diagnosis 19.66 ± 7.69 33.05 ± 2.34 week of delivery 35.92 ± 1.97 35.99 ± 2.09 weight of baby 2.66 ± 0.58 2.69 ± 0.69 P = 0.173 MWG (kg) 12.09 ± 3.21 11.84 ± 3.74 Insulin used 107 (86.29%) 118 (76.12%) P = 0.025* PIH developed (n=330) 24 (16.55%) 39 (21.08%) Caesarean delivery 103 (83.06%) 141 (92.15%) P = 0.020* Vaginal delivery 21 (16.93%) 14 (9.15%) Apgar score <7at1st min 47 (37.9%) 52 (37.9%) P = 0.500 Preterm delivery 76 (61.29%) 95 (61.29%) P = 0.892 Term delivery 51 (41.12%) 70 (56.45%) LBW (kg) 46 (37.09%) 52 (37.09%) P = 0.591 NBW (kg) 81 (65.32%) 111 (72.54%) SGA 2 (1.61%) 6 (1.61%) LGA 12 (9.67%) 24 (9.67%) P = 0.140 AGA 113 (91.12%) 135 (88.23%) Macrosomia 1 (0.80%) 5 (0.8%) P = 0.162 Hypoglycaemia 68 (54.83%) 97 (54.83%) P = 0.150 Hyperbilirubinemia 72 (58.06%) 91 (58.06%) P = 0.813
Table – 11A: Distribution of blood glucose value of women developed GDM early and late
Statistics value for ANOVA – P value expressed for significance.* P value is significant
Table – 11B: Age and Primiparity of women developed GDM early and late
Graph – 7: Expressing percentage of Age, Primiparity of early and late GDM women
81
42
74
31
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60
70
80
90
Age >25 Primiparity
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early
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% of women
Early(124) Late(153) P – value FBS (mg/dl) Base 96.70 ± 17.03 101.26 ± 24.76 End 92.12 ± 28.16 94.95 ± 23.21 FBS L4 98.32 ± 20.79 96.52 ± 18.62 P = 0.534 PPBS Base 143.96 ± 30.50 146.73 ± 39.14 End 142.03 ± 31.36 136.10 ± 29.20 PPBS L4 140.33 ± 28.77 139.04 ± 28.70 P = 0.767
Early(124) Late(153) P – value Age (year) Risk level
27.96 ± 3.68 100 (80.64%)
27.02 ± 3.81 113 (73.85%)
P = 0.030*
Primiparity 51 (42.12%) 47 (30.71%) P = 0.005*
Table – 11C: Percentage of Cesarean and Insulin use in early and late GDM women
* P value is significant
Graph – 7A: Percentage of Cesarean, use of Insulin in early and late GDM women
83 86 92
76
0
10
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30
40
50
60
70
80
90
100
Cesarean Insulin treated
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early
late
% of women
Early(124) Late(153) P – value Insulin used 107 (86.29%) 118 (76.12%) P = 0.025* Caesarean delivery 103 (83.06%) 141 (92.15%) P = 0.020*
6.4.A. Individual analysis 6.4.A.1. GDM 6.4.A.1.d. FBS ≤ 95 mg/dl vs. FBS ≥ 95 mg/dl
Variation in blood glucose level of mother causes considerable changes in fetal health. Fetus
insulin stimulation will be more when he/she receives mother blood with excess glucose level,
which further cause hypoglycemic state of fetus and further complications as a consequences for
the same. This analysis was done to understand, what will be the outcome difference if blood
glucoses controlled under normal range and not. Women who controlled the FBS level ≤ 95 mg/dl
(144) were considered as control group and women who controlled the FBS level > 95 mg/dl (133)
were considered as non-control group.
Maternal and fetal characteristics were shown in – Table 12, 12A, 12B, 12C, 12D, 12E & Graph 8,
8A, 8B, 8C, 8D. There was significant difference in terms of pregnancy outcome between the
controlled and non-controlled groups. Strict control of blood glucose level under the normal
range gives significant improvement in the pregnancy outcome of GDM. The following
complications were significantly improved in control group, mode of delivery, preterm delivery,
term delivery, LBW, NBW, LGA and week of delivery.
The average end FBS values of control and non-control group were 82.95 ± 12.44 and 106.68 ±
27.69 mg/dl respectively. Cesarean section and preterm delivery were less in number with control
group. Around 83% of women given birth through cesarean delivery the same was 93% with non-
control group of GDM. BMI have significant role in maintenance of blood glucose, larger the BMI
requires more amount of insulin and further it may leads to insulin resistance. The average BMI of
non-controlled group women was 28.33 ± 8.59 kg/m2 which is higher than controlled group
women (27.23 ± 3.61). Around 63% of delivery was preterm delivery in no-controlled group
whereas 52% of preterm deliveries were recorded in controlled group. The average week of
delivery for controlled group was 36.30 ± 1.85, which less for non-controlled group (35.61 ± 2.16).
Term babies were more with controlled group which accounts for 51%. Only 38% were recorded
as term babies in non-controlled group. LBW babies were high (38%) with non-controlled group,
the same was accounts for 26% in controlled group. Double the amount of LGA recorded with non-
controlled group compared to controlled group, the values are 17% and 8% respectively.
Table – 12: Blood glucose level of women who controlled FBS ≤ 95 mg/dl and above 95 mg/dl.
Measurement ≤ 95(144) >95 (133) P – value FBS
Base value 90.86 ± 12.86 110.43 ± 27.82 End value 82.95 ± 12.44 106.68 ± 27.69
FBS Last 4 values mean 83.93 ± 7.68 110.87 ± 17.71 P = 0.000* PPBS Break Fast
Base value 137.32 ± 32.90 155.21 ± 40.05 End value 128.34 ± 24.41 146.87 ± 31.88
PPBS Last 4 values mean 129.80 ± 24.77 149.22 ± 29.41 P = 0.000* PPBS LUNCH
Base value 143.27 ± 33.05 160.84 ± 35.95 End value 136.84 ± 30.03 145.81 ± 24.27
PPBS Last 4 values mean 132.09 ± 21.76 148.50 ± 23.88 PPBS DINNER
Base value 143.94 ± 28.04 163.59 ± 36.39 End value 140.06 ± 25.76 152.57 ± 33.50
PPBS Last 4 values mean 131.46 ± 23.38 146.32 ± 26.03 Statistics value for ANOVA – P value expressed for significance. * P value is significant.
Graph – 8: Expressing Blood glucose level of women controlled FBS below and above 95 mg/dl
91 83 84
137 128 130
110 107 111
155 147 149
0
50
100
150
200
250
Base End L4 Base End L4
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se v
alue
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dl---
>
FBS <95
FBS >95
<95 mg/dl group (FBS) >95 mg/dl group (FBS)
Table – 12A: Details of women who controlled FBS ≤ 95 mg/dl and above 95 mg/dl
Character FBS ≤ 95 mg/dl (n=144)
FBS >95 mg/dl (n=133) P Value
Age (year) 27.07 ± 3.42 27.78 ± 4.08 P = 0.243 BMI (kg/m2) 27.23 ± 3.61 28.33 ± 8.59 P = 0.037* Week of diagnosis 27.20 ± 8.59 26.87 ± 8.47 P = 0.532 week of delivery 36.30 ± 1.85 35.61 ± 2.16 P = 0.004* MWG 11.87 ± 3.51 11.92 ± 3.77 Diet 32 (22.22%) 23 (17.29%) Insulin 112 (77.77%) 110 (82.70%) P = 0.305 Caesarean delivery 119 (82.63%) 123 (92.48%) P = 0.014* Vaginal delivery 25 (17.36%) 10 (7.51%) P = 0.014* Apgar<71t 49 (32.23%) 48 (34.78%) P = 0.720 Preterm 79 (51.97%) 87 (63.04%) P = 0.044* Term 73 (51%) 51 (38%) P = 0.021* LBW 39 (25.65%) 52 (37.68%) P = 0.034* NBW 113 (78.47%) 86 (64.66%) SGA 1 (0.65%) 7 (5.07%) P = 0.011* LGA 12 (7.89%) 23 (16.66%) P = 0.025* AGA 139 (96.52%) 108 (81.20%) P = 0.000* Macros 3 (1.97%) 3 (2.17%) P = 0.922 Hypoglycaemia 90 (59.21%) 71 (51.44%) P = 0.125 Hyperbilirubinemia 92 (60.52%) 72 (52.17%) P = 0.100 Baby 152 138 twin 8 5 Baby Weight 2.74 ± 0.57 2.64 ± 0.67 P = 0.079
Statistics value for ANOVA – P value expressed for significance. * P value is significant
Table – 12B: Distribution of BMI of women: FBS below and above the 95 mg/dl Character FBS ≤ 95 mg/dl FBS >95 mg/dl P Value BMI (kg/m2) 27.23 ± 3.61 28.33 ± 8.59 P = 0.037*
Graph – 8A: Expressing BMI of women: FBS below and above the 95 mg/dl
Table – 12C: Week of diagnosis and delivery of women: FBS below and above the 95 mg/dl Week (average) FBS ≤ 95 mg/dl FBS >95 mg/dl P Value Week of diagnosis 27.20 ± 8.59 26.87 ± 8.47 P = 0.532 week of delivery 36.30 ± 1.85 35.61 ± 2.16 P = 0.004*
Graph – 8B: Week of diagnosis & delivery of women: FBS below and above the 95 mg/dl
27.23 28.33
0
5
10
15
20
25
30
35
40
FBS <95 FBS >95
Average BMI value
BMI
kg/m
2
27.2
36.3
26.87
35.61
0
5
10
15
20
25
30
35
40
45
Diagnosis week Delivery week
Wee
k ---
>
FBS <95
FBS >95
Table – 12D: Term and preterm delivery of women: FBS below and above the 95 mg/dl Character FBS ≤ 95 mg/dl FBS >95 mg/dl P Value Preterm 79 (51.97%) 87 (63.04%) P = 0.044* Term 73 (51%) 51 (38%) P = 0.021*
Graph – 8C: Week of diagnosis & delivery of women: FBS below and above the 95 mg/dl
Table – 12E: Distribution of SGA, LGA babies of women: FBS below and above the 95 mg/dl
Character FBS ≤ 95 mg/dl (number/%) FBS >95 mg/dl (number/%) P Value SGA 1 (0.65%) 7 (5.07%) P = 0.011* LGA 12 (7.89%) 23 (16.66%) P = 0.025*
Graph – 8D: Expressing % of LGA, SGA babies of women, FBS below and above the 95 mg/dl
51 52
38
63
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30
40
50
60
70
Term Preterm
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FBS <95 FBS >95 % of delivery
0.65
7.89
5.07
16.66
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FBS <95
FBS >95% of Babies
6.4.A. Individual analysis 6.4.A.2. PIH 6.4.A.2.a. Treatment comparison
Uncontrolled blood pressure caused complications both in mother and fetus. Growth retardation
and fetal mortality are the serious complications in PIH pregnancy. The elevated BP also caused
the early and cesarean delivery. Antihypertensive drugs are used to control the BP within the
normal range which further reduces the PIH related complications. Various drugs are used to treat
the PIH; this analysis was done to find the treatment outcome differences between different types
of drugs used in the treatment of PIH.
The PIH diagnosed women (n=161) were categorized according to the drug that they received for
their treatment. The groups are Group 0 (n=30) – women who received none of the drug, Group 1
(n=50) – women who received Nifidepine, Group 2 (n=46) – women who received Methyldopa and
Group 3 (n=35) – women who received Nifidepine and Methyldopa.
Maternal and fetal outcome data were presented in – Table 13, 13A, 13B, 13C & Graph 9, 9A. For
the entire group BP was significantly reduced from base value to end value. All the drugs
significantly reduced the BP level from base to end. But there was no significant difference in the
reduction of BP between the drugs. The pre and post BP value of all the drugs were given in the –
Table 13A. No significant difference was found in terms of pregnancy outcome between these
drugs treatment except for eclampsia. Eclampsia was affected with 14% women in group 2
(women received both type of drugs) whereas no women was affected with eclampsia in group 0
(women received no drug). Cesarean delivery was high across the group, all the group 0 women
has given birth through cesarean delivery.
Table – 13: Distribution of complications of PIH women based on the drugs received
Complications Nifidepine (n=50)
Methyldopa (n=46)
Nife+M.dop (n=35)
No drug (n=30)
P Value
Cesarean delivery 94 91.3 94.28 100 P = 0.454 Vaginal delivery 6 8.69 5.71 0 P = 0.454 Term delivery 32 41.30 25.71 46.66 P = 0.265 Preterm delivery 69.26 60.41 75 56.25 P = 0.376 LBW 61.53 56.25 61.11 43.75 P = 0.457 NBW 40 45.65 40 60 P = 0.313 SGA 42 37.5 41.66 21.87 P = 0.234 LGA 2 4.16 5.55 0 AGA 40 60.86 54.28 83 P = 0.002* IUGR 20 14.58 11.11 6.25 P = 0.391 Apgar <7 at 1st mint 36 25 41.66 15.62 P = 0.101 HELLP 0 0 2 0 P = 0.428 Eclampsia 6 2.17 14.28 6.66 P = 0.049*
Statistics value for ANOVA. All values are expressed in percentage. * P value is significant, Nife+M.dopa – Nifidepine and Methyldopa
Table – 13A: Distribution of BP values of PIH women based on the drugs received
Measurement Nifidepine (n=50)
Methyldopa (n=46)
Nife+M.dop (n=35)
No drug (n=30)
Pre BP Systolic 147.38±15.15 140.57±13.29 137.10±9.59 133.16±15.29 Diastolic 93.31±11.95 90.38±7.86 90.07±6.56 85.26±9.64
Post BP Systolic 143.25±15.86 141.71±11.40 136.69±10.42 135.63±10.73 Diastolic 92.88±8.62 89.81±5.65 88.72±5.73 88.63±7.29
Postpartum BP Systolic 133.44±10.46 130.43±8.58 131.52±11.14 131.89±9.92 Diastolic 88.56±5.97 85.62±6.80 85.07±5.38 84.63±6.19
P = 0.001* P = 0.000* P = 0.000* P = 0.001* Statistics value for ANOVA. All values are expressed by mean±SD mmHg. * P value is significant
Table – 13B: Distribution of AGA babies of PIH women based on the drugs received Complications Nifidepine Methyldopa Nife+M.dop No drug P Value AGA (%) 40 60.86 54.28 83 P = 0.002*
Graph – 9: Expression of AGA babies of PIH women based on the drug received.
Table – 13C: Distribution of Eclampsia in PIH women based on the drugs received Complications Nifidepine Methyldopa Nife+M.dop No drug P Value Eclampsia (%) 6 2.17 14.28 6.66 P = 0.049*
Graph – 9A: Expression of eclampsia in PIH women based on the drug received
40
60.86 54.28
83
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30
40
50
60
70
80
90
Nifidepine Methyldopa Nifi+Dopa No drug
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AGA
6
2.17
14.28
6.66
0
2
4
6
8
10
12
14
16
Nifidepine Methyldopa Nifi+Dopa No drug
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% of Eclampsia
Eclampsia
6.4.A. Individual analysis 6.4.A.2. PIH 6.4.A.2.b. Disease severity comparison
The increase in severity changes the outcome of pregnancy. Disease Severity increases the rate of
morbidity and mortality. PIH further classified to various types according to the severity and
clinical features of disease. The severity of the diseases is also not predictable and no identifiable
causation factors. This analysis was done to understand the causing factors and changes in
pregnancy outcome by changes in severity of PIH. Women diagnosed as GH (n=54), Pre-eclampsia
– mild (PE-M, n=37), Pre-eclampsia – severe (PE-S, n=63) and eclampsia (n=18) were taken into
analysis (n=172).
Maternal characteristics were shown in – Table 14. The risk factors are not different and doesn’t
show any influence to develop particular type of disease. No significant risk factors were found to
be an important to develop one particular severity of PIH. The age was around 25 years across
the groups of women. Nulliparity women were more in all group compare to primiparity women.
Primigravida women were more in all severity comparing to multigravida.
Outcome results were present in – Table 14A, 14B, 14C, 14D, 14E & Graph 10, 10A, 10B, 10C. The
pregnancy outcome results showed significant difference between the severities of PIH. The
significant difference can be found in the outcome variables of preterm delivery, SGA, LBW and
baby weight. High percentage of preterm was (79%) found for eclampsia women, the same was
recorded low with GH women. SGA babies were more with severe-preeclampsia (50%) and
recorded low with mild-preeclampsia. LBW baby was more with eclampsia and preeclampsia-
severe followed by preeclampsia-mild and gestational hypertension. The average baby weight was
reduced against increasing severity. The average weight of baby was 2.01 ± 0.84 kg for eclampsia,
2.08 ± 0.96 kg for PE-S, 2.33 ± 0.86 kg for PE-M and 2.61 ± 0.62 kg for GH subjects. It was
understood, the increasing severity of PIH will worsen the outcome of pregnancy.
Table – 14: Characteristics of PIH women based on the severity of complication
GH (n=54)
PE-M (n=37)
PE-S (n=63)
ECLAMPSIA (n=18) P value
Average age 25.42 ± 3.18 26.62 ± 4.62 27.16 ± 4.80 24.22 ± 3.81 P = 0.109 BMI 24.92 ± 4.11 26.66 ± 4.97 25.94 ± 3.97 25.41 ± 5.03 P = 0.279 Gravidity 1.51 ± 0.81 1.51 ± 0.67 1.63 ± 1.05 1.66 ± 1.08 Parity 0.31 ± 0.66 0.29 ± 0.51 0.41 ± 0.81 0.33 ± 0.59 Diagnosis week 34.25 ± 4.74 28.51 ± 9.28 31.30 ± 6.25 31.38 ± 4.28 Primigravida 34 (62.96%) 23 (62.16%) 39 (69.0%) 12 (66.66%) P = 0.986 Multigravida 20 (37.03%) 14 (54.05%) 24 (38.09%) 6 (33.33%) P = 0.986 Nulliparity 40 (74.07%) 27 (72.97%) 47 (74.6%) 13 (72.22%) P = 0.996 Primiparity 13 (24.07%) 9 (24.32%) 9 (14.28%) 4 (22.22%) P = 0.517 Multiparity 1 (1.85%) 1 (2.70%) 7 (11.11%) 1 (5.55%) Previous PIH 8 (14.8%) 4 (10.81%) 4 (6.34%) 2 (11.11%) P = 0.526 Family.Hist.HT 13 (24.07%) 12 (32.43%) 17 (26.98%) 3 (16.66%) P = 0.631 Family.Hist.DM 19 (35.18%) 9 (24.32%) 14 (22.22%) 3 (16.66%) P = 0.300
GE – Gestational hypertension, PE-M – Pre-eclampsia mild, PE-S – Pre-eclampsia sever, Statistics value for ANOVA. Values are expressed in mean ± SD and %, * P value is significant Table – 14A: Pregnancy outcome of PIH women based on the severity of complication
GH (n=54)
PE-M (n=37)
PE-S (n=63)
ECLAMPSIA (n=18) P value
Caesarean 49 (90.74%) 36 (97.29%) 59 (93.65%) 7 (94.44%) P = 0.922 Vaginal 5 (9.26%) 1 (2.71%) 4 (6.35%) 11 (5.56%) Preterm 27 (49.09%) 24 (61.53%) 48 (75%) 15 (78.94%) P = 0.014* Term 27 (50.91%) 13 (39.47%) 15 (25%) 3 (21.06%) Delivery week 36.59 ± 1.85 34.97 ± 2.80 34.17 ± 3.68 33.47 ± 2.48 Apgar <7 1 min 11 (20%) 9 (23.07%) 22 (34.37%) 7 36.84%) P = 0.237 SGA 16 (29.09%) 10 (25.64%) 32 (50%) 9 (47.36%) P = 0.019* IUGR 6 (10.9%) 5 (12.82%) 11 (17.18%) 3 (15.78%) P = 0.788 Baby weight 2.61 ± 0.62 2.33 ± 0.86 2.08 ± 0.96 2.01 ± 0.84 P = 0.000* Twin babies 1 2 3 1 Foetal death 0 0 2 0 LBW 21 (38.18%) 23 (58.97%) 44 (68.75%) 13 (68.42%) P = 0.006*
Statistics value for ANOVA. Values are expressed in mean ± SD and %, * P value is significant
Table – 14B: Preterm delivery of PIH women based on the severity of complication
GH PE-M PE-S ECLAMPSIA P value Preterm 27 (49.09%) 24 (61.53%) 48 (75%) 15 (78.94%) P = 0.014*
Graph – 10: Expressing preterm deliveries of PIH women based on the severity of complication
Table – 14C: SGA babies of PIH women based on the severity of complication
GH PE-M PE-S ECLAMPSIA P value SGA 16 (29.09%) 10 (25.64%) 32 (50%) 9 (47.36%) P = 0.019*
Graph – 10A: Percentage of SGA babies of PIH women based on the severity of complication
49.09
61.53
75 78.94
0
10
20
30
40
50
60
70
80
90
GH PE-M PE-S ECLMP
Perc
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->
% of Preterm Preterm
29.09 25.64
50 47.36
0
10
20
30
40
50
60
GH PE-M PE-S ECLMP
Perc
enta
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->
% of SGA SGA
Table – 14D: Mean Baby weight of PIH women based on the severity of complication
GH PE-M PE-S ECLAMPSIA P value Baby weight 2.61 ± 0.62 2.33 ± 0.86 2.08 ± 0.96 2.01 ± 0.84 P = 0.000*
Graph – 10B: Mean baby weight of PIH women based on the severity of complication
Table – 14E: Distribution of LBW of PIH women based on the severity of complication
GH PE-M PE-S ECLAMPSIA P value LBW 21 (38.18%) 23 (58.97%) 44 (68.75%) 13 (68.42%) P = 0.006*
Graph – 10C: Expressing LBW of PIH women based on the severity of complication
2.61 2.33
2.08 2.01
0
0.5
1
1.5
2
2.5
3
3.5
GH PE-M PE-S ECLMP
Wei
ght -
kg
--->
Mean Baby weight Baby weight
38.18
58.97
68.95 68.42
0
10
20
30
40
50
60
70
80
GH PE-M PE-S ECLMP
Perc
enta
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->
% of LBW LBW
6.4.B. Comparison analysis 6.4.B.1. Risk factors
Maternal characteristics, family history, personal lifestyle and obstetric history are the likelihoods
to develop some determinable changes in pregnancy. Those likelihoods causing complications to
pregnancy can be considered as risk factors. Age, BMI, gravidity, parity, irregular menstrual cycle
history, family history of diabetes, previous history of GDM and PIH are the risk factors shown
significant correlation with complications – Table S1.
These risk factors were taken to analysis. As a single or coupled, each risk factor has their own
strength to develop complications to pregnancy. GDM and PIH are the complications having
unique risk factors for the development as well as share some common risk factors also. This
analysis would give better idea on risk factors and their influence. Women diagnosed with GDM
(n=277), PIH (n=172) and both GDM & PIH (n=68) were grouped and taken into the analysis. Risk
factors for all the complications were detailed in the Table 15.
Table S1: Correlation between risk factors and complications; GDM and PIH Correlation coefficient {Pearson Correlation – sig. (2-tailed)} values for Risk factors.
** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the o.05 level (2-tailed)
Risk factors P Value
Age (year) P = 0.009** BMI (kg/m2) P = 0.000** Gravidity P = 0.002** Primigravida P = 0.020* Multigravida P = 0.020* Parity P = 0.002* Nulliparity P = 0.005** Primiparity P = 0.002** Multiparity P = 0.615** Previous GDM P = 0.001** Previous PIH P = 0.002* Family History of DM P = 0.000** Family History of HTN P = 0.540* Hb (gm/dl) P = 0.396* Irreg. Menstrual cycle P = 0.007**
6.4.B.1.a. Risk factors and their values are not equally distributed between the groups.
Complications are varying with risk factors. All the risk factors taken for the analysis showed
significant difference between the groups of women except for multiparity and HB level. Few
women has the risk level of hemoglobin (>13 gm/dl) same way, the overall percentage of
multiparity women were less across the groups.
Age – details shown in Table 15A, Graph 11, 11A. Average age of all the group women are >25
years, which is the age to develop any of these complications. When comparing the age between
the groups, women who developed both were elder than any other groups. PIH complicated
women are younger compare to any other group. From the mean value and SD values, it can be
understand that advancing age from the risky age (>25 years) shows high influence on
development of both complications together. The entire groups have highest percentage of
women between the ages in the range of 25 to 29 years. Percentage of PIH complicated women
are more for the age in the range of 20 to 24 years compare to any other groups. It can be
understand that younger age women are prone to develop PIH compared to GDM and GDM+PIH,
and when age is advancing the risk for developing complications becomes linear from PIH then
GDM then both together.
BMI – details shown in Table 15B, Graph 11B, 11C. Average BMI of all the group women was >25
kg/m2. The BMI value of above 25 was considered as overweight and the risks for developing any
of these complications. When comparing the value between groups, women who developed GDM
and GDM+PIH were having equally high BMI value than PIH group women. From the mean value
and SD values, it can be understood that advancing BMI beyond overweight (>25 kg/m2), shows
high influence on development of GDM and along with PIH, and when BMI reducing below 25 risks
of developing PIH is more. The entire groups have highest percentage of women for the BMI range
of 25 to 29 except for PIH group women. PIH group have more percentage of women between the
BMI ranges of 20 to 24 and below 20 kg/m2. More than half the populations (54%) were below the
BMI of 25 in PIH group. lean women or women with BMI value less than 25, are under the risk to
develop PIH compared to GDM and GDM+PIH, and when BMI is advancing to overweight (>25-29)
the risk for developing complications becomes linear from PIH to GDM then both together, but
when BMI value advancing to obese (>30) the risks to develop GDM and both together are more
and not to PIH.
Gravidity – details shown in Table 15C, Graph 11D, 11E. The average gravidity of all the group
women was 1.81 ± 1.6. Primigravida and multigravida women are equally spread across the
groups. The average gravidity was less with PIH compare to GDM or both group women.
GDM+PIH group women have higher gravidity value than GDM or PIH. Around 63% women are
Primigravida in PIH group. Around 60% women are multigravida in GDM+PIH group, primigravida
women are more prone to develop PIH, and when gravidity increases the risks are more to
develop GDM and both together, whereas multigravida women are more prone to develop both
GDM & PIH complications together.
Parity – Multiparity doesn’t have significant difference between the groups. Nulliparity and
primiparity were not equally distributed. The average parity value is less with PIH group women
compared to other groups. Percentage of nulliparous women are more in the entire group. Around
74% of PIH group women are nulliparous. Women who experienced one previous delivery are
risks to developing PIH then GDM for current pregnancy.
Previous history of GDM / PIH – overall percentage of previous history of either GDM or PIH is less
across the groups. Less than 1% of women have previous history of GDM in PIH group. GDM+PIH
group have more number of women with previous history of either GDM or PIH. The previous
history may not be considered as under significant risk but when combined with other risk factors
this may boost the risks for developing any other complications. Previous history of PIH showed
significant influence to develop both complications together.
Family history of DM / HTN – around 57% of GDM women have the family history of DM either
mother or father or both. This also influences the women to develop PIH as well. Family history of
hypertension doesn’t show the significant correlation to develop any complication. Around 71%
and 47% of women in GDM+PIH group have the family history of DM and HTN respectively.
Women who had family history of DM are more prone to develop both the types of
complications. Paternal history of DM is more in GDM and GDM+PIH group. Around 40% of
women in GDM and GDM+PIH groups have paternal history of DM. Maternal history of DM is
around 30% in both GDM and GDM+PIH group. Paternal history of DM has influence on
development of GDM.
Menstrual cycle – Irregular menstrual cycle women are found to be more prevalent with
GDM+PIH group and less with PIH group. Around 37% of women are having irregular menstrual
cycle in GDM group. It can be understood that irregular menstrual history women are prone to
develop GDM and more prone to develop GDM and PIH together than PIH alone.
Table – 15: Risk factors of GDM, PIH and GDM + PIH women Statistics – P value for non-parametric Kruskal-wallis test given at significance level of 0.05.
Risk factors GDM (n=277) PIH (n=172) GDM & PIH (n=68)
P Value
Age (year) 27.45 ± 3.78 26.55 ± 4.55 29.60 ± 4.52 P = 0.000* ≤ 24 23.82% 38.95% 10.29% 25 - 29 50.18% 43.02% 39.70% ≥ 30 21.66% 17.44% 49.99% Weight (kg) 67.93 ± 9.26 63.51 ± 12.6 70.49 ± 10.43 BMI (kg/m2) 27.77 ± 3.94 25.60 ± 4.579 27.95 ± 3.88 P = 0.000* ≤ 24 .99 19.48% 54.06% 20.58% 25 – 29.99 51.26% 30.23% 50.0% ≥ 30 29.23% 15.10% 30.88% Gravidity 1.91 ± 1.11 1.63 ± 0.97 2.0 ± 1.13 P = 0.001* Primigravida 40.09 % 62.79 % 41.17 % P = 0.009* Multigravida 50. 90 % 37.20 % 58.82 % P = 0.009* Parity 0.46 ± 0.65 0.35 ± 0.69 0.45 ± 0.58 Nulliparity 60.28 % 73.83 % 58.82 % P = 0.008* Primiparity 35.01 % 20.34 % 36.76 % P = 0.002* Multiparity 13 % 5.81 % 5.88 % P = 0.843* Previous GDM 7.94% 0.581% 8.82% P = 0.002* Previous HTN 3.24% 11.22% 20.58% P = 0.000* Family History of DM 57.03% 26.16% 8.82% P = 0.000* Family History of HT 30.68% 26.74% 20.58% P = 0.009* Marital period (year) 3.79 ± 3.09 3.79 ± 3.09 5.80 ± 4.15 MWG (kg) 11.87 ± 3.65 13.40 ± 4.60 10.48 ± 3.6 Hb (gm/dl) 11.45 ± 1.24 11.54 ± 1.52 11.87 ± 1.03 P = 0.135* Irreg. Menstrual cycle
36.10 % 17.63 % 44.11 % P = 0.026*
Table – 15A: Distribution of age as risk factors for all the complications
Graph – 11: Expression
of age as risk factors for all the complications
Graph 11A - Distribution pattern of complication against Age by number of women. (Graph contains line and logarithmic curves. Log curves represent the pattern of distribution of complications for age)
23.82
50.18
21.66
38.95 43.02
17.44
10.29
39.7
49.99
0
10
20
30
40
50
60
≤24 25-29 ≥30
Age
Perc
enta
ge --
->
GDM
PIH
G+P
-5
0
5
10
15
20
25
30
35
17 19 21 23 25 27 29 31 33 35 37 39
Num
ber o
f wom
en
GDMPIHG+PLog. (GDM)Log. (PIH)Log. (G+P)
Age in years
AGE in Years GDM (n=277) PIH (n=172) GDM & PIH(68) P Value ≤ 24 23.82% 38.95% 10.29%
P = 0.000* 25 - 29 50.18% 43.02% 39.70% ≥ 30 21.66% 17.44% 49.99%
Table – 15B: Distribution of BMI as risk factors for all the complications
Graph – 11B: Expression
of BMI as risk factors for all the complications
Graph 11C - Distribution pattern of complication against BMI by number of women. (Graph contains line and logarithmic curves. Log curves represent the pattern of distribution of complications for BMI)
19.48
51.26
29.23
54.06
30.23
15.1
20.58
50
30.88
0
10
20
30
40
50
60
≤24 25-29 ≥30
BMI
Perc
enta
ge --
->
GDM
PIH
G+P
% of women for BMI
-5
0
5
10
15
20
25
30
35
40
45
17 19 21 23 25 27 29 31 33 35 37 39
Num
ber o
f wom
en
GDMPIHG+PLog. (GDM)Log. (PIH)Log. (G+P)
BMI in kg/m2
BMI (kg/m2) GDM (n=277) PIH (n=172) GDM & PIH (68) P Value ≤ 24 .99 19.48% 54.06% 20.58%
P = 0.000* 25 – 29.99 51.26% 30.23% 50.0% ≥ 30 29.23% 15.10% 30.88%
Table – 15C: Distribution of Gravidity as risk factor for all the complications Graph –
11D: Expression of gravidity as risk factors for all the complications
Graph 11E - Distribution pattern of complication against gravidity by percentage of women. (Graph contains line and logarithmic curves. Log curves represent the pattern of distribution of complications for BMI)
40.09
50.9
62.79
37.2 41.17
58.82
0
10
20
30
40
50
60
70
Primigravida Multigravida
Perc
enta
ge --
->
GDM
PIH
G+P
% of women in gravida
-20
-10
0
10
20
30
40
50
60
70
1 2 3 4 5 6
GDM
PIH
G+P
Log. (GDM)
Log. (PIH)
Log. (G+P)
Gravidity
% o
f wom
en
Gravidity GDM (n=277) PIH (n=172) GDM & PIH(68) P Value Primigravida 40.09 % 62.79 % 41.17 % P = 0.009* Multigravida 50. 90 % 37.20 % 58.82 % P = 0.009*
6.4.B.1.b. An increase in number of risk factors and interactions of one on another showed
variation in the development of complications; GDM / PIH / GDM+PIH
Women having number of risk factors are more prone to develop any complications. When a
woman having number of risk factors, probability of developing a particular complication is varies,
the combined effect of those risk factors may influence the women to develop a particular
complication. This analysis was done to understand whether increasing number of risk factors
having any influence on development of particular complication or not.
Details described in Table 16 showed that all the groups of women have at least 3 risk factors. The
average number of risk factors for women who developed both complications was high (4.16 ±
1.19) compare to GDM (3.54 ± 1.48) or PIH (3.27 ± 1.21) group women. PIH group women have
less number of risk factors compared to other groups. Nearly 72% of women had more than 3 risk
factors and 28% had risk factors from 1 to 3 in G+P group. Around 48% of women had the risk
factors from 1 to 3 and 53% of women had the risk factors above 3 in GDM group. Only 41%
women had more than 3 risks factors and 58% of women have from 1 to 3 risk factors in PIH
group. Only 16% women have more than 4 risk factors in PIH group compared to GDM (26%) and
GDM+PIH (43%) group. The increase in the number of risk factors caused a parallel increase of
risks to PIH, GDM and GDM+PIH was followed to be increased.
An influence of risk factors one on another to develop these complications was analyzed, which
showed, the additional risk factors significantly changed the probability of developing
complications. The combination of risk factors and their risks for the development of
complications are varied – Table S2 – Prediction Tool.
A primigravida woman under the age of 25 years, had the probability of developing GDM is 46%
and for PIH is 50% and for developing both together is 4%. When age is increasing probability of
developing GDM (56%) is more than PIH (36%). Primigravida women are prone to develop PIH,
when their age is increasing the probability is increasing to develop GDM than PIH. Addition to
this when BMI is below 25, as a risk factor, the probability varies with 70% to PIH and 26% to GDM.
When BMI increases the probability is more to develop GDM (56%) than PIH (36%).
When family history of DM added to above circumstance, considering age and BMI is under the
risk range, risks to develop PIH is more (54%) compared to GDM or both. When age is increasing
up to 29 years, risks to develop GDM is more (50%) and age increasing above 30 years, risks to
develop GDM+PIH is more (40%) whereas the probability to develop PIH is less. When BMI is also
increasing along with age, risks follow the same pattern as age does. Addition of family history of
HTN doesn’t changes the probability but the percentages of chances to develop the complications
were increased. Addition of irregular menstrual cycle history and risk of HB were also not changed
the probability of developing complications, but varied with the percentages of chances.
A multigravida woman with age under 25 years, has the probability of developing GDM is 47% and
for PIH is 45% and for developing both together is 8%. When age is increasing the probability of
developing GDM (64%) is more than PIH (21%). Multigravida women are prone to develop GDM,
when their age is increasing the probability of developing GDM is also increasing. Leaner body
weight multigravida women have great risks to develop PIH (80%) but not to GDM (16%) when her
age is below 25. when BMI is getting increases the probability of developing GDM is also increases
and reaches high level of 73% when BMI is above 30.
The nulliparous, multigravida women of normal body weight (BMI <25) and age below 25 years
have great risks to develop PIH (74%). The probability is changing with increasing age and also with
increasing BMI, when age is increasing probability to GDM is also increasing, age reaches above 30
the probability of GDM+PIH is great compared to anyone. When BMI increases, same way the
probability to GDM+PIH is more (66%) but very less to PIH (5%).
Addition of family history of DM assures the same trend with changes in the percentage level,
when BMI and age are increases probability for developing GDM+PIH (71%) is great and is very less
to PIH (1%). Addition of irregular menstrual history and risk of HB doesn’t alter the pattern of
development but boosts the percentages of probability for the same trend.
Primiparous, multigravida women of normal body weight (BMI <25) and below 25 years of age
have great risks to develop PIH (87%) than GDM (13%). When BMI and age are advancing, the
probability is increasing to develop first GDM (90%) than PIH (10%). Addition of family history of
diabetes mellitus doesn’t changed the probability, instead greatly increased the risks to develop
complications.
Nulliparous women having more chances to develop PIH (44%) than GDM (38%), and when their
age is increasing probability to develop GDM is increasing and when age is above 30 years, the
probability is increasing (58%) to exist both together.
Primiparous women having more chances to develop GDM (55%) than PIH (46%), and when their
age is increasing probability to develop GDM is increasing and when age is above 30 years, the
probability is still increasing (78%) to develop GDM alone.
Table – 16: Details of number of risk factors women having in each complication No. of Risks Complications
1 2 3 4 5 6 7
GDM 24 50 58 73 49 17 7 PIH 11 33 56 42 27 1 0 G+P 3 5 11 20 21 7 1 Risks Range GDM PIH G+P
1 – 3 47.65% 58.13% 27.94% 4 – 6 50.18% 40.69% 70.58% > 6 2.52% 0% 1.47% No of Risks(avg) 3.54 ± 1.48 3.27 ± 1.20 4.10 ± 1.35
Values expressed in numbers/percentage/mean ± SD.
6.4.B.1.c. The increasing number and values of risk factors causing earlier development of
complications; GDM / PIH
Women having number of risk factors are more prone to develop any complications. An increase
in number of risk factors and their values has significant influence on the early development of
GDM or PIH. This analysis was done to understand the risk factors and their influence on early
development of complications. Details are presented in – Table S2, S3 & Plot S1, S2.
Details were described in – Table 17 & Graph 12. All the GDM and PIH women had at least 3 risk
factors. The maximum of 7 risk factors was recorded with women. For a GDM woman who had 3
risk factors, the average week of diagnosis was 28.48 ± 7.24, the same for PIH woman was 33.25 ±
4.24. Most of the women are having 4 risk factors in GDM group and 3 risk factors in PIH group.
Advancing age, BMI, gravidity and advancing parity significantly changed the development of
complications. When the values of above mentioned risk factors are increasing, it causes earlier
onset of complications of GDM and PIH. Increasing values of risk factors causes earlier
development of complications. Details are presented in – Table S5, S6, S7, S8, S9, S10, S11, S12 &
Plot S3, S4, S5, S6, S7, S8, S9, S10.
Table – 17: Details of number of risk factors and average week of diagnosis for GDM and PIH Values expressed in mean ± SD.
No. of Risk factors Week of Diagnosis GDM (n=277) PIH (n=172)
1 28.23 ± 6.19 33.54 ± 2.97 2 28.85 ± 7.22 30.48 ± 7.28 3 28.48 ± 7.24 33.25 ± 4.24 4 26.50 ± 9.02 29.71 ± 9.01 5 24.77 ± 9.80 31.96 ± 6.77 6 26.11 ± 8.65 NA 7 23.71 ± 10.61 NA
Average Number of Risk factors
3.54 ± 1.48 3.27 ± 1.20
Week of Diagnosis 27.01 ± 8.51 31.76 ± 6.74
Graph 12 - Week of diagnosis of complication against number of risk factors. (Graph contains line and logarithmic curves. Log curves represent the frequency pattern of diagnosis of week for number of risk factors)
18
21
24
27
30
33
36
1 2 3 4 5 6 7
Perc
enta
ge --
->
Number of risk factors --->
Diagnosis week GDMDiagnosis week PIHLog. (Diagnosis week GDM)Log. (Diagnosis week PIH)
The average number of risk factors for women who developed GDM was 3.54 ± 1.48 and the
average week of diagnosis of GDM was 27.17 ± 8.23 weeks – Table 17, S3 & Plot S1.
Table S3 - Model Summary and Parameter Estimates the Number of Risks vs week of diagnosis (GDM) Dependent Variable: GDM Week / The independent variable is Number of Risks. Equation Model Summary Parameter Estimates
R Square
F df1 df2 Sig. Constant b1 b2
Linear .025 8.579 1 328 .004 30.430 -.889 Quadratic .033 5.526 2 327 .004 27.713 .935 -.255
From – Table S3, the estimation of F statistics is significant (P=0.04), which indicated that the
estimation is not due to chance. In the linear and quadratic model the b1 value is less than 1,
indicated, the increase in number of risk factors would actually reduce the week of diagnosis.
An increase of risk factors by 1 reduce the diagnosis of week by 30.430 + (- .889) and 27.713
+0.935. The b2 value is squared value of increasing risk factors, for each increase of number of risk
factors; diagnosis of week reduces by 0.935/2*-0.255.
Plot S1 - Linear and quadratic curve-fit for number of risks against the week of diagnosis
From this – plot S1, the quadratic model curve matches exactly with values and visually showed
the changes of weeks against number of risks.
The average number of risk factors for women who developed PIH was 3.27 ± 1.21and the average
week of PIH was 31.76 ± 6.74 weeks. Details were recorded in – Table 17, S4 & Plot S2
From the – Table S4, it can be understood, the estimation of F statistics significant value is greater
than 0.05, which indicates that the estimation model have some variations in the value. In the
linear model the b1 value is less than 1, which indicates, the increase in number of risk factors
reduces the week of diagnosis. In quadratic model the b1 value is greater than 1 which indicated
the increase in number of risk factors and not reduced the week of diagnosis. An increase of risk
factors by 1 reduced the week of diagnosis by 32.879 + (- .697) – linear model. The b2 value is
squared value of increasing risk factors, for each increase of number of risk factors; diagnosis of
week reduces by 1.410/2*-0.318.
Table S4 - Model Summary and Parameter Estimates the Number of risks vs. Week of diagnosis (PIH) Dependent Variable: PIH diagnosed week, The independent variable; number of risk. Equation Model Summary Parameter Estimates
R Square F df1 df2 Sig. Constant b1 b2 Linear .012 2.235 1 185 .137 32.879 -.697 Quadratic
.018 1.700 2 184 .185 29.878 1.410 -.318
Plot S2 - Linear and quadratic curve-fit for number of risks against the week of diagnosis
From the above – plot S2, the quadratic model curve matches with values and visually shows the
changes of weeks against number of risks.
From the analysis, it can be understood that, the increase of risk factors by 1 would reduce the
week of diagnosis by 0.889 (linear model) or 1.86 weeks (quadratic model) for the GDM
complication. For the PIH complication; increase of risk factors by 1 would reduce the week of
diagnosis by 0.697 week (linear model) or 2.21 weeks (quadratic model). It can be understood
that, the increasing number of risk factors would actually increases the risks for women to
develop the complications early. Increases in number of risk factors causing early development
of GDM may not cause the early development of PIH.
Table S5: Model Summary and Parameter Estimates Advancing age Vs. Diagnosis week: GDM Dependent Variable: Diagnosis week of GDM/ The independent variable is Age. Equation Model Summary Parameter Estimates
R Square
F df1 df2 Sig. Constant b1 b2
Linear .015 5.148 1 328 .024 34.456 -.262
Quadratic .018 2.933 2 327 .055 48.740 -1.274 .018
From – Table S5, the estimation of F statistics is significant (P=0.024, linear modal) with actual
value, which indicates that the estimation is not due to chance. In the linear and quadratic modal
the b1 value is less than 1, indicates, the advancing age would actually reduce the week of
diagnosis. An increase of age by 1 reduce the diagnosis of week by 34.456 + (-.262) and
48.740+1.274. The b2 value is squared value of advancing age, for increase of age by each year;
diagnosis of week reduces by 1.274/2* 0.018. Plot – S3: Linear and quadratic curve-fit for advancing age Vs week of diagnosis: GDM
From this – plot S3, the quadratic modal curve matches exactly with actual values and visually
shows the changes of weeks against advancing age.
Table S6: Model Summary and Parameter Estimates Advancing BMI Vs. Diagnosis week: GDM Dependent Variable: Diagnosis week of GDM / The independent variable is BMI.
Equation Model Summary Parameter Estimates
R Square F df1 df2 Sig. Constant b1 b2
Linear .003 .927 1 328 .336 30.530 -.121
Quadratic .003 .501 2 327 .607 25.325 .267 -.007
From – Table S6, the estimation of F statistics is not significant (P>0.05), which indicates that the
estimation modal has some variation values with actual value. In the linear and quadratic modal the
b1 value is less than 1, indicates, the advancing BMI would actually reduce the week of diagnosis.
An increase of BMI by 1 reduce the diagnosis of week by 30.530 + (-.121) and 25.325+0.267. The b2
value is squared value of increasing risk factors, for increase of BMI by each value; diagnosis of
week reduces by 0.267/2*-0.007.
Plot – S4: Linear and quadratic curve-fit for advancing age Vs week of diagnosis: GDM
From this – plot S4, the quadratic modal curve matches exactly with actual values and visually
shows the changes of weeks against advancing BMI.
Table S7: Model Summary and Parameter Estimates advancing gravida Vs diagnosis week:GDM Dependent Variable: Diagnosis week of GDM / The independent variable is Gravidity.
Equation Model Summary Parameter Estimates
R Square F df1 df2 Sig. Constant b1 b2
Linear .014 4.576 1 328 .033 28.847 -.874
Quadratic .021 3.526 2 327 .031 31.097 -3.208 .454
From – Table S7, the estimation of F statistics is significant (P=0.03) with actual value, which
indicates that the estimation modal is not due to the chance. In the linear and quadratic modal the
b1 value is less than 1, indicates, the advancing gravidity would actually reduce the week of
diagnosis. An increase of gravidity by 1 reduce the diagnosis of week by 28.847 + (-.874) and
31.097+3.208. The b2 value is squared value of increasing risk factors, for increase of gravidity by
each value; diagnosis of week reduces by 3.208/2* 0.454.
Plot S5: Linear and quadratic curve-fit for advancing gravida Vs week of diagnosis: GDM
From this – plot S5, the quadratic modal curve matches exactly with actual values and visually
shows the changes of weeks against advancing gravidity.
Table S8: Model Summary and Parameter Estimates advancing parity Vs diagnosis week: GDM Dependent Variable: Diagnosis week of GDM / The independent variable is Parity.
Equation Model Summary Parameter Estimates
R Square F df1 df2 Sig. Constant b1 b2
Linear .017 5.667 1 328 .018 27.952 -1.681
Quadratic .042 7.190 2 327 .001 28.434 -4.830 1.575
From – Table S8, the estimation of F statistics is significant (P=0.01) with actual value, which
indicates that the estimation modal is not due to the chance. In the linear and quadratic modal the
b1 value is less than 1, indicates, the advancing gravidity would actually reduce the week of
diagnosis. An increase of parity by 1 reduce the diagnosis of week by 27.952 + (-1.681) and
28.434+4.830. The b2 value is squared value of increasing risk factors, for increase of parity by each
value; diagnosis of week reduces by 4.830/2* 1.575.
Plot S6: Linear and quadratic curve-fit for advancing parity Vs week of diagnosis: GDM
From this – plot S6, the quadratic modal curve matches exactly with actual values and visually
shows the changes of weeks against advancing parity.
Table S9: Model Summary and Parameter Estimates advancing age Vs diagnosis of week: PIH Dependent Variable: Week of PIH / The independent variable is Age (PIH)
Equation Model Summary Parameter Estimates
R Square F df1 df2 Sig. Constant b1 b2
Linear .129 27.299 1 185 .000 47.088 -.626
Quadratic .137 14.637 2 184 .000 26.314 .859 -.026
From – Table S9, the estimation of F statistics is significant (P=0.000) with actual value, which
indicates that the estimation is not due to chance. In the linear and quadratic modal the b1
value is less than 1, indicates, the advancing age would actually reduce the week of diagnosis.
An increase of age by 1 reduce the diagnosis of week by 47.088 + (-.626) and 26.314+0.859.
The b2 value is squared value of increasing risk factors, for increase of age by each year;
diagnosis of week reduces by 0.859/2* -0.026. .
Plot S7: Linear and quadratic curve-fit for advancing age Vs week of diagnosis: PIH
From this – plot S7, the quadratic modal curve matches exactly with actual values and visually
shows the changes of weeks against advancing age.
Table S10 Model Summary and Parameter Estimates advancing BMI Vs Diagnosis week: PIH Dependent Variable: Week of PIH / The independent variable is BMI (PIH).
Equation Model Summary Parameter Estimates
R Square F df1 df2 Sig. Constant b1 b2
Linear .046 9.012 1 185 .003 40.057 -.375
Quadratic .046 4.482 2 184 .013 39.536 -.335 -.001
From – Table S10, the estimation of F statistics is significant (P=0.003) with actual value, which
indicates that the estimation is not due to chance. In the linear and quadratic modal the b1 value is
less than 1, indicates, the advancing BMI would actually reduce the week of diagnosis. An increase
of BMI by 1 reduce the diagnosis of week by 40.057 + (-.375) and 39.536+0.335. The b2 value is
squared value of increasing risk factors, for increase of BMI by each value; diagnosis of week
reduces by 0.335/2* -0.01.
Plot S8: Linear and quadratic curve-fit for advancing BMI Vs week of diagnosis: PIH
From this – plot S8, the quadratic modal curve matches exactly with actual values and visually
shows the changes of weeks against advancing BMI.
TableS11:Model Summary and Parameter Estimates advancing gravidaVs diagnosis of week:PIH Dependent Variable: Week of PIH / The independent variable is Gravidity (PIH).
Equation Model Summary Parameter Estimates
R Square F df1 df2 Sig. Constant b1 b2
Linear .046 8.988 1 185 .003 33.308 -1.750
Quadratic .067 6.643 2 184 .002 37.021 -5.917 .854
From – Table S11, the estimation of F statistics is significant (P=0.003) with actual value, which
indicates that the estimation is not due to chance. In the linear and quadratic modal the b1 value is
less than 1, indicates, the advancing BMI would actually reduce the week of diagnosis. An increase
of gravidity by 1 reduce the diagnosis of week by 33.308 + (-1.750) and 37.021+5.917. The b2 value
is squared value of increasing risk factors, for increase of gravidity by each value; diagnosis of week
reduces by 5.917/2*-0.854.
Plot S9: Linear and quadratic curve-fit for advancing gravida Vs week of diagnosis: PIH
From this – plot S9, the quadratic modal curve matches exactly with actual values and visually
shows the changes of weeks against advancing gravidity.
Table S12:Model Summary and Parameter Estimates advancing parity Vs diagnosis of week: PIH Dependent Variable: Week of PIH / The independent variable is Parity PIH.
Equation Model Summary Parameter Estimates
R Square F df1 df2 Sig. Constant b1 b2
Linear .045 8.769 1 185 .003 31.318 -2.446
Quadratic .049 4.780 2 184 .009 31.462 -3.950 .646
From – Table S12, the estimation of F statistics is significant (P=0.003) with actual value, which
indicates that the estimation is not due to chance. In the linear and quadratic modal the b1
value is less than 1, indicates, the advancing BMI would actually reduce the week of diagnosis.
An increase of parity by 1 reduce the diagnosis of week by 31.318 + (-2.446) and 31.462+3.950.
The b2 value is squared value of increasing risk factors, for increase of parity by each value;
diagnosis of week reduces by 3.950/2*-0.646.
Plot S10: Linear and quadratic curve-fit for advancing parity Vs week of diagnosis: PIH
From this – plot S10, the quadratic modal curve matches exactly with actual values and visually
shows the changes of weeks against advancing parity.
6.4.B. Comparison analysis 6.4.B.2. Complications
Whether GDM or PIH once developed, the pregnancy may affect and leaves some traces on
pregnancy life. A good pregnancy outcome is a measure of uncomplicated delivery to mother.
Complications affect both mother and fetus. Outcome of pregnancy varies with complications,
severity of diseases and lifestyle of women. This analysis was done to understand the outcome of
pregnancy for the respective complications. Women diagnosed with GDM (n=277), PIH (n=172)
and both GDM & PIH (n=68) were grouped and taken into the analysis. Pregnancy outcome results
were recorded in the – Table 18, 18A, 18B, 18C, 18D & 13, 13A, 13B.
6.4.B.2.1. Maternal complications
Cesarean delivery: – All the group of women has high percentage of cesarean delivery. In GDM
group 87% of women given birth through cesarean section which was 94% to PIH group women.
But for the GDM+PIH group all the women (100%) given birth through cesarean delivery.
Significant difference was found between the groups. Comparatively GDM group women showed
less number of cesarean deliveries. Both GDM and PIH complications are suspected for the cause
to the mode of delivery, when a woman having both the complications together the chances are
very great to have cesarean delivery. In GDM group 46% of cesarean delivery was emergency
delivery whereas 30% of cesarean delivery was emergency delivery in PIH group.
Insulin administration: Around 81% of GDM women and 75% of GDM+PIH women received
insulin as a treatment for gestational diabetes. Regular and NPH type insulin are used for the
treatment. Most of the GDM women received NPH insulin (48%) where as 21% of women received
both types of insulin.
Drug administration: Around 82% of PIH women and 65% of GDM+PIH women received
antihypertensive drugs as their treatment for hypertension.
Eclampsia: Around 18% PIH women developed eclampsia and 1% of GDM+PIH group women
developed eclampsia.
Mortality: one woman have died because of eclampsia and 2 fetal deaths were occurred in PIH
complicating women.
6.4.B.2.2. Neonatal complications
All the babies were normal and good in health. Two fetal deaths and one maternal death were
occurred as a result of PIH complication. No neonatal birth injury was reported. Macrosomia and
HELLP syndrome were very less with the study population.
Twins: Totally 22 twins were born, 13 twins were born to GDM complication women and 7 were
for PIH alone and 2 twins were born to GDM+PIH women.
Preterm: Around 65% of babies were preterm babies in PIH and GDM+PIH group, which is less
(49%) in GDM group. PIH group women have more number of preterm babies.
Baby weight: Average baby weight of GDM women was 2.67 ± 0.65 kg. Average baby weight of
PIH women was 2.22 ± 0.73 kg and the same was 2.45 ± 0.81 kg. Significantly PIH women’s’ baby
weight was low compared to other group women. GDM complication tends to increase the weight
of baby and PIH tend to decrease the weight of baby, pathological reasons, significant result was
seen in our group’s women. When PIH combined with GDM the baby weight was significantly
altered, the baby weight is above the PIH complicating group babies’ weight and below the GDM
complicating group babies’ weight.
Apgar score at 1st min: Average Apgar score of GDM group babies average Apgar score was 7.69 ±
0.66 and for PIH group was 7.72 ± 0.78 and for GDM+PIH group was 7.55 ± 0.67. Added number
babies (34%) with Apgar score below 7 were seen in GDM+PIH group compare to GDM (24%) and
PIH (28%). Significantly PIH group women have less number of babies with Apgar score below 7.
LBW: GDM group’s women have less number of LBW babies (34%) compare to PIH and GDM+PIH,
whereas GDM+PIH group women had more number of LBW babies.
LGA: LGA babies were more with GDM group (12%) and less with PIH group (3%) women.
SGA: More number of SGA babies was seen in PIH group (37%) women, which is less in GDM group
women (3%).
Macrosomia: Around 2% of GDM and GDM+PIH women had macrosomic babies.
IUGR: Percentage of IUGR was more with GDM+PIH group (15%), which is high compare to PIH
group (13%).
Hypoglycemia: Around 56% babies were experienced hypoglycemia in GDM group and 46% of
babies were experienced hypoglycemia in GDM+PIH group.
Hyperbilirubinemia: Around 62% of babies were experienced hyperbilirubinemia in GDM+PIH
group where as 57% of babies were experienced in GDM group.
Table – 18: Perinatal outcome of GDM, PIH and GDM + PIH women
P values for non-parametric Mann-Whitney U, Kruskal-wallis tests were given at the significance level of 0.05.
Characters GDM alone (n=277)
PIH alone (n= 172)
GDM+PIH (n=68) P value
Maternal complications
Cesarean delivery 87.36% 94.65% 100% P = 0.001* Vaginal delivery 12.63% 5.81 % 0% P = 0.001* Insulin usage m 80.50% 75% P = 0.315 Week of delivery 36.28 ± 1.99 34.74 ± 3.70 34.60 ± 4.00 Neonatal complications (n=290) (n= 177) (n=70)
Term delivery 50.34 % 35.02 % 38.23 % P = 0.001* Preterm delivery 48.96 % 64.97 % 61.76 % P = 0.004* Baby Weight 2.67 ± 0.65 2.22 ± 0.73 2.45 ± 0.81 P = 0.001* Twin babies 4.69 % 4.06 % 2.94 % LBW 33.79 % 55.86 % 47.05 % P = 0.000* NBW 66.2 % 43.5 % 51.42 % P = 0.517 SGA m 2.75 % 37.28 % 17.64 % P = 0.002* LGA m 12.06 % 2.82 % 11.76 % P = 0.847 AGA 80.68 % 59.88 % 73.52 % P = 0.000* IUGR m 0 % 12.99 % 14.70 % P = 0.787 Macrosomia m 2.06 % 0.56 % 2.94 % P = 0.704 Apgar<7at 1st mint 24.13 % 28.81 % 32.29 % P = 0.000* HELLP 0 % 1.12 % 1.56 % Hypoglycemia m 55.51 % 0 45.58 % P = 0.063 Hyperbilirubinemiam 56.55 % 0 61.76 % P = 0.700
Table – 18A: Mode of delivery of GDM, PIH and GDM + PIH women
Characters GDM alone (n=277)
PIH alone (n= 172)
GDM+PIH (n=68) P value
Cesarean delivery 87.36% 94.65% 100% P = 0.001* Vaginal delivery 12.63% 5.81 % 0% P = 0.001*
Graph 13: percentage of Mod of delivery of GDM, PIH and GDM+PIH women
Table 18B: Size of the baby of GDM, PIH, GDM+PIH women complications (n=290) (n= 177) (n=70) P value SGA 2.75 % 37.28 % 17.64 % P = 0.002* LGA 12.06 % 2.82 % 11.76 % P = 0.847
Graph 13A: Percentage of Size of the baby of GDM, PIH and GDM+PIH women
87.36
12.63
94.65
5.81
100
0 0
20
40
60
80
100
120
Cesarean delivery Normal delivery
Perc
enta
ge --
-.
GDMPIHGDM+PIH
2.75
12.06
37.28
2.82
17.64
11.76
0
5
10
15
20
25
30
35
40
LGA SGA
Perc
enta
ge --
->
GDM
PIH
GDM+PIH
Table – 18C: Birth weight of baby of GDM, PIH and GDM + PIH women
Characters GDM alone (n=277)
PIH alone (n= 172)
GDM+PIH (n=68) P value
Baby Weight 2.67 ± 0.65 2.22 ± 0.73 2.45 ± 0.81 P = 0.001*
Graph 13B: Average birth weight of baby of GDM, PIH and GDM+PIH women
Table – 18D: Percentage of babies having apgar <7 at 1st min of GDM, PIH and GDM + PIH
Characters GDM alone (n=277)
PIH alone (n= 172)
GDM+PIH (n=68) P value
Apgar<7at 1st min 24.13 % 28.81 % 32.29 % P = 0.000*
Graph 13C: Average birth weight of baby of GDM, PIH and GDM+PIH women
2.67
2.22 2.45
0
0.5
1
1.5
2
2.5
3
3.5
GDM PIH GDM+PIH
Wei
ght i
n kg
--->
Birth weight in kg Birth weight
24.13
28.81 32.29
0 0
5
10
15
20
25
30
35
GDM PIH GDM+PIH
apga
r val
ue --
->
Apgar<7 at 1stmin Apgar<7 at 1stmin
6.4.B. Comparison analysis 6.4.B.3. Associations
Around 13% of women from total population have both GDM and PIH complications. Where 78%
of GDM women developed PIH and 22% of PIH women developed GDM. The complication which is
developed first is considered as primary diagnosis and the follow up is considered as effect of
that first complication. Average diagnosis week of GDM as a primary diagnosis was 28.01 ± 6.58
week and as a secondary to PIH was 23.86 ± 9.55 week. Average diagnosis week of PIH as a
primary diagnosis was 17.40 ± 9.40 week and as a secondary to GDM was 33.43 ± 2.78 week. The
average time period for developing the second one was 5.78 ± 5.98 week. Details were present in
– Table 19 & Graph 14.
For the comparison of primary diagnosis of GDM, the average week of diagnosis was higher than
GDM population (27.01 ± 8.51) (women who have developed GDM alone, n=277), but as a
secondary diagnosis of GDM, the average week of diagnosis was earlier than GDM alone
population. It may be understood, the development of GDM as a secondary may be influence of
PIH or risk factors.
For the comparison of primary diagnosis of PIH, the average week of diagnosis was lesser than PIH
population (31.76 ± 6.74), but as a secondary diagnosis of PIH, the average week of diagnosis was
later than PIH alone population. It may be understood, the development of GDM as a secondary
may be influence of GDM or risk factors.
For the comparison of primary diagnosis of GDM and PIH, the average age of women was
respectively 29.33 ± 4.52 and 30.53 ± 5.73 years for GDM and PIH, which was higher than GDM
alone and PIH population. Same way the gravidity value also was high for these groups of women
compared to GDM or PIH complicated women.
The development of GDM as a primary diagnosis follows the common GDM development pattern
(GDM alone development) for age as a risk factor. But the same trend was not seen in PIH as a
primary diagnosis case, since the probability of development for common PIH (PIH alone) was
huge with younger women (<25years of age),here the women’s average age was very high
compare to any other women. Development of secondary GDM in these women not may be due
to the influence of PIH, but the secondary development of PIH may be due to the influence of
GDM.
Table 19: Average diagnosis week of complications GDM and PIH in GDM + PIH women
Primary diagnosis – GDM (n=53)/ (week)
Primary diagnosis – PIH (n=15)/ (week)
Week of primary diagnosis 28.01 ± 6.58# 17.40 ± 9.40^ Week of secondary diagnosis 23.86 ± 9.55^ 33.43 ± 2.78# Interval from primary to secondary diagnosis
5.98 ± 5.47$ 5.13 ± 4.06≠
Average interval 5.79 ± 5.78 Primary diagnosis – For a woman which complication is diagnosed first Secondary diagnosis – For a woman which complication is diagnosed second # GDM diagnosis, ^ PIH diagnosis, ≠ - Interval from PIH to GDM, $ - Interval form GDM to PIH
Graph 14: Expressing Average diagnosis week of each complication of GDM+PIH women
28.01
17.4
23.86
33.43
0
5
10
15
20
25
30
35
40
GDM PIH
Wee
k ---
>
Primary diagnosis
Secondary diagnosis
6.4.B.3.1. Common risk factors
GDM and PIH are linked each other as both are the complications of pregnancy. Since pregnancy is
the inducer risk factors may be common for both the complications. This analysis was done to
understand whether the both complications are sharing the common risk factors or not. Details
were presented in – Table S1.
A common pattern of development can be seen between GDM and PIH. Both complications are
developed early when neither risk factors nor their values are increasing. Age, BMI, gravidity and
parity are the risk factors shows common pattern of development for both complications. –Table
S5,S6,S7,S8,S9,S10,S11,S12 & Plot S3,S4,S5,S6,S7,S8,S9,S10. Age, BMI, gravidity, Family history of
DM, irregular menstrual cycle and previous history of GDM and PIH are the common risk factors
for both GDM and PIH complications.
The frequencies of developing complications are common but varied with the values of risk
factors. For PIH, the higher frequency starts from younger age (below 25) to elder age (above 30)
and for GDM the higher frequency starts from risky age (from 25 to 29) to elder age. The same
kind of trend can be seen in BMI also – Table S2 – Prediction Tool. From the common risk factors
analysis; the frequency pattern of development of complications were same but the values of
risk factors varied.
6.4.B.3.2. Pregnancy outcome
Outcome of pregnancy varies with complications, their severity and lifestyle of women. Based on
the pathology and manifestations of disease the outcome complications may varies. Even the
treatments of diseases also worsen the quality of life of pregnant women, and further the
medicines and procedures used in the treatment may also produce some unwanted results.
Cesarean delivery is performed to complicated delivery in order to save the mother and child from
complications, since it is invasive procedure, further worsen the quality of life of women.
Various pregnancy problems can be found for both GDM and PIH. Among the all cesarean delivery,
preterm delivery, LGA, SGA, LBW and baby birth weight showed correlation between GDM, PIH
and GDM+PIH. It can be understood, that these complications are producing some similar
problems to pregnancy outcome.
Cesarean delivery is common problems of both PIH and GDM, 94% of PIH women and 87% GDM
women have given birth through cesarean delivery, whereas all the women in GDM+PIH category
given birth through cesarean delivery. Cesarean delivery will reach maximum, when both
complications are coexists. It can be understood, that the effect of individual complications may
triggered when both are combined.
Preterm delivery is more with PIH and as well as GDM+PIH group, which is less with only GDM
group. By the correlation and common complication analysis it can be understood, that preterm
delivery is an independent problem of PIH complication.
SGA babies are more (38%) with PIH complicating women, whereas GDM women have only 3% of
SGA babies and GDM+PIH women have, more compared to GDM, 17% of SGA babies. It can be
understood that, the SGA outcome is a unique problem of PIH and when it occurs along with GDM,
increases the probability of SGA in GDM populations.
LGA babies are more (13%) with GDM complicating women, whereas PIH women have only 3% of
LGA babies and GDM+PIH women have, more compared to GDM, 12% of LGA babies. It can be
understood that, the LGA outcome is a unique problem of GDM and when it occurs along with PIH,
increases the probability of LGA in PIH populations.
PIH population doesn’t have hypoglycemic or hyperbilirumic babies but the PIH women who
developed GDM later have the hypoglycemic as well as hyperbilirumic babies. GDM+PIH women
have more number of hyperbilirumic babies (66%) than GDM women (56%). Although the
hyperbilirubinemia is unique GDM complication, it is increased in GDM+PIH complicated women.
It can be understood, that the unique problems of particular complications may triggered by
coexistence of both complications.
In general, the pregnancy outcome may vary with complications that women experienced, and
further the outcome may worsen if both complications coexist.
6.5. Development of prediction tool
The probability of developing particular complication in a woman is based on their risk factors.
Maternal characteristics, family history, personal lifestyle and obstetric history are the likelihoods
to develop some determinable changes in pregnancy. Those likelihoods causing complications to
pregnancy are considered as risk factors. Age, BMI, gravidity, parity, irregular menstrual cycle
history, family history of diabetes, previous history of GDM and PIH are the risk factors shown
significant correlation with complications – Table S1. As a single or coupled, each risk factor has
their own strength to develop complications to pregnancy. GDM and PIH are the complications
having unique risk factors for the development and have some common risk factors also. Assessing
these risk factors can provide some understanding on these complications and would help in the
development of tool to assess the women for a particular complication.
6.5.1. Prediction tool an introduction
A prediction tool was developed to assess the women for a complication of GDM and PIH. This is
basically a table that contains percentage values and risk factors, where the values represent the
chances to develop a complication of GDM/PIH for a woman. (Table S2) This tool was developed
by using study data, all the women risk factors were analyzed and compared with corresponding
complications. By using Multinomial logistic regression method this tool was developed. Based on
the observed data, one prediction data will be developed by this method which is then finally
compiled for a single table. The prediction data is basically a percentage value represents
probability of particular complication.
Tool table is basically divided by three major rows as primigravida, multigravida – nulliparity and
multigravida – primiparity. The area in between these rows are relates to particular type of above
said gravidity. The left side first column represents risk factors and right side last column
represents complications, in between this, the 3 columns and 9 sub-columns represent age and
BMI respectively. The meeting point of rows and columns of the tool is the percentage value for
particular complication corresponding to particular risk factor.
6.5.2. Limitations of tool
Since the tool is prepared on the basis of our study population, this tool contains some limitations.
Data for number of samples having more than 5 risk factors was less; hence one cannot be able to
successfully generate the prediction model to access the women having more than 4 risk factors.
The multigravida women having more than 4 risk factors were less hence the prediction values
were not able to be generated successfully.
This tool gives the prediction value up to 5 risk factors for the analysis of primigravida women,
where the risk factors includes age, BMI, family history of diabetes, family history of hypertension
and menstrual history.
This tool gives the prediction value up to 5 risk factors for the analysis of multigravida nulliparous
women, where the risk factors includes age, BMI, family history of diabetes, family history of
hypertension and irregular menstrual history.
This tool gives the prediction value up to 3 risk factors for the analysis of multigravida primiparous
women, where the risk factors includes age, BMI, family history of diabetes, family history of
hypertension and irregular menstrual history.
6.5.3. How to use the Prediction tool
Approaching the prediction tool is explained with following example…
Example: probability of developing complications for a 24 year old overweight, primigravida
woman is as follows-
1) Select age of <25 years column
2) Select BMI of 25-29 column
3) Drag down through BMI column up to meet the PIH row
In Image 1, the circled meeting point is the prediction value for above said woman; she is having
47% of chance to develop PIH, 51% of chance to develop GDM and 2% of chance to have both
together.
Figure 3: Expressing the assessment of prediction tool
A woman of less than 25 years old and BMI
between 25 to 29 kg/m2 having 47% of chance to
develop PIH
AGE = In Years BMI = kg/m2 FM.DM = Family history of Diabetes FM.HTN = Family history of Hypertension G+P = GDM+PIH IRR.MENS = History of Irregular Menstrual cycle ALL = including all risk factors Prev.GDM, Prev.PIH = Previous history of GDM , Previous history of PIH Risk factors: age, BMI, FM.DM, FM.HTN, IRR.MENS, Prev.GDM, Prev.PIH
7. Discussion
7.1. Prevalence of GDM and PIH
The prevalence of GDM was 2.20% for the period of 10 years from January 2003 to December
2012. The prevalence of GDM may range from 1 to 14% of all pregnancies worldwide; the variation
is due to different screening methods used with different ethnic to diagnose GDM12. In India the
prevalence of GDM varies with different areas of country, the range is from 3.8% to 21%110. In
south India, the prevalence of GDM has increased from 1% in 1998 to 16.55% in 2004229. The
prevalence of GDM in Tamilnadu was increasing from 2.1% in 1982, which increased to 7.62% in
1991, which further increased to 16.55% in 20026. We found from our study that the prevalence of
GDM is declined from 3.28% in 2003 to 2.11% in 2012.
The prevalence of PIH was 1.53%for the period of 10 years from January 2003 to December 2012.
The prevalence of PIH may range from 5 to 10% of all pregnancies2. The prevalence of PIH is
increasing and affects about 5 to 8% of pregnancies230. In India the prevalence was recorded with
8% to 10%231. We have found from our study that the prevalence PIH is declining from 2.87% in
2003 to 1.16% in 2012. But the incidence GDM and PIH was found to be increased from 24 to 60
and 21 to 33 cases respectively.
7.2. Risk factors and complication of GDM
Age 25 years and above was considered as risk for development of GDM as many studies reported
that the risk of age greater than 25 years of old232,233. The prevalence of gestational diabetes
mellitus is largely driven by the increase in 25-35 years age group234. The risk of GDM becomes
significantly and progressively increased from the age of 25 years onwards141.We found similar
results in our study. The average of study population age was more than 25 (27.75 ± 3.90) and
half of the population was 25-29 of age, 72% of women were between the age group of 25-34.
The frequency of GDM was found to be increased from the age of 25. The prevalence of GDM is
increased with Increasing age235,236. Advancing age was found to increase the risks for earlier
development of GDM. Women diagnosed with GDM in first and second trimesters were elder than
the women diagnosed at third trimester237was in correlation with our study; the first trimester
group women were elder than second and third trimester group women. The average age of the
population was 28.88 ± 4.65, 27.59 ± 3.77 and 27.02 ± 3.81 respectively. The age of early
diagnosed GDM women was also higher than the age of late GDM diagnosed women. Thus,
advancing age increases the frequency and also causes the earlier development of GDM.
Obesity is one of the important risk factor for GDM238and one of the strongest predictor for GDM
is the BMI239.AbdulbariBener et al104 with 2056 pregnant women in Qatar reported that the
obesity is essential risk factor for GDM and BMI causes a steady increase in GDM. The advancing
BMI is also a risk factor for gestational diabetes mellitus229. Overweight and obesity are the
identifiable risk factors for GDM240. In our population the mean BMI was found to be risk with the
value of 27.71 ± 3.61kg/m2 and 80% of women were above the BMI of 25, and 51% of women
found overweight. The frequency of GDM is also increased from the BMI of 25 to 29 and above.
Thus, advancing BMI increases the frequency and also causes the earlier development of GDM.
Gravidity and Primiparity were found to be high risk to develop GDM241,242. Higher parity was
associated with more prevalence of GDM243,244.. Primigravida women have more risks to develop
GDM245. Several studies suggesting advancing in gravidity increases the prevalence of GDM. In our
study we found the same risk situation; about 52% of women found with multigravida and 36% of
women were primiparous. The average gravidity value was 1.91 ± 1.10 and average parity value
was 0.46 ± 0.63 which were showed the chances of risk. Multigravida and primiparity influences
the early development of GDM as independent risk factors. But multiparity did not show the
influence on the development of GDM, 77% of multigravida and 44% of primiparous women
developed GDM early in their gestation. Thus, increasing gravidity and primiparity are the risk
factors to GDM and also causes the earlier development of GDM.
Family history of diabetes mellitus (DM) has association in the development of GDM246. Family
history act as an independent risk factor for the development of GDM139,247. The maternal history
of diabetes is appears to be a stronger predictor of GDM than paternal history248. Williams et al249
reported in his study that the paternal only history showed two folds increased risk to GDM and
maternal history doesn’t showed risk to GDM. Many studies are stating about the risk of family
history. The above statement was similar with our study; in our study totally 58% of women had
family history of diabetes of which comparatively paternal history was more with 38% against 32%
with maternal diabetes history. Thus, the family history of diabetes is one of the important risk
factor for the development of GDM.
Previous history of GDM was found to be significant risk factor for GDM250. GDM can again lead to
gestational diabetes in the following pregnancies248,251, but in our study only 8% of women had
previous history of GDM and only 6% of women had previous history of PIH.
History of irregular menstrual cycle was found to be an independent risk factor for the
development of GDM43. The blood hemoglobin level of a woman also shows influence on the
development of GDM. The HB concentration more than 13% shows an increased risk for
GDM252.Our study was in correlation with this result, where 36% of women had irregular
menstrual cycle and showed significant influence on the development of GDM. Around 10% of
women had HB level more than 13 and doesn’t show significant influence on the development of
GDM.
The rate of cesarean delivery has increased significantly with GDM253. In our study 89% of women
given birth through cesarean delivery and only 11% of women were given birth through vaginal.
Xionget al254 considered preterm birth is a complication to the infants of GDM mother. Preterm
and term deliveries were not shown much difference in our study, 51% of preterm deliveries were
recorded against 49% of term deliveries.
We found that all new born babies were in good health and there were no reports of shoulder
dystocia, neonatal birth trauma and respiratory complications. The preterm deliveries and LGA
babies are significant to GDM women255. In our study we found that about 12% of babies born
were LGA, whereas 2% born macrosomic babies. The babies born to GDM mother are eight times
more likely to have hypoglycemia and three times more likely to have hyperbilirubinemia256. In our
study 55%of the babies were affected with hypoglycemia and 58% of babies were affected with
hyperbilirubinemia. Overall around 50% of babies were affected neither with hypoglycemia nor
with hyperbilirubinemia.
7.3. Risk factors and complications of PIH
A study done by Navascués et al in Spain on severe maternal complications associated with
preeclampsia found that women greater than 30-35 years of age had an increased risk of
complications257. A study done on 97,270 women with PIH found out that 37.4 % was over 30
years258. Several studies suggesting, younger and first pregnancy women are high risk to
developing PIH and largest number of primiparous women age from 20 found with
preeclampsia259. In our study, 17.44% of the study population was over 30 years of age, 39% of
women were below 24 years of old and 43% of women fall between the age group of 25 to 29. Our
result is similar with above mentioned study; women from the age of 20 to 24 years are more
prone to develop PIH. Thus, the frequency of PIH is more with younger women from the age of 20
to 24 and not much related with elder women age more than 30 years.
One cohort study with 16,582 women with PIH found that, obesity is not associated with the
development of PIH307. Other study conducted in Karachi hospital reported that the development
of PIH is high with obese women than non-obese women308. We found similar results like cohort
study; in our study the percentage of obese women are less compared to non-obese women. Lean
to ideal body weight and overweight women are more prone to develop PIH.
Primiparous women have 4 to 5 time’s more risk than multiparous women to develop PIH260. A
study on the risk factors and clinical manifestation of preeclampsia in Norway foundthat, out of
323 preeclampsia patients 64% were nulliparous261. Nulliparity, previous preeclampsia, high
maternal weight, hypertension, diabetes and twin pregnancies are the risk factors shown strong
relationship to develop PIH147,262. In our study, about 73.79% were nulliparous women and 19%
were primiparous women. Thus, the nulliparity women are more prone to develop PIH than
primiparity whereas multiparity women don’t show much influence to develop PIH. The
frequency of PIH increases with nulliparity compare to primiparity.
The development of preeclampsia is associated with family history of hypertension263. Women
having family history of hypertension are 10 times more risk to develop preeclampsia compared to
women not having family history of hypertension264. In our study, around 30% of PIH women had
family history of hypertension and 31% of women had family history of diabetes mellitus. From
our results, we found that the family history of hypertension doesn’t influence the women for the
development of PIH.
Women with PE in a previous pregnancy had strong risk to develop PE in the current pregnancy149.
Previous preeclampsia and previous diabetes have shown a strong relationship to develop PIH for
current pregnancy265. In our study, 11% of women had previous history of PIH and shown
significant association with current diagnosis of PIH.
Severity of PIH diseased women can be completely brought under control by voluntary delivery
process. The probability of vaginal delivery is very less for the women with preeclampsia
compared to non preeclamptic women266. PIH pregnancy is strongly associated with preterm
delivery182. In our study cesarean delivery was significantly high compared to vaginal delivery,
about 95% of delivery was done through cesarean section. The preterm delivery was also more in
our study, around 65% of women given birth as preterm delivery.
IUGR contributes to two-thirds of LBW babies born in India267. A retrospective study on impact of
PIH on birth weight by gestational age mentioned that the effect of decreased birth weight is
found mostly among preterm births258. The SGA, LBW and preterm birth were higher in PIH
women268. LBW and IUGR babies were significantly increased in women with PIH269. In our study
we found, the mean birth weight was low among the preterm births and overall the low birth
weight babies were more with record of 58%. IUGR was significantly increased to 26% in our
population. The maternal death due to hypertension is accounted for 13% of all pregnancy270.
Totally 2 fetal and one maternal death were occurred in our study due to pregnancy hypertension.
7.4. Discussion for analysis
7.4.1.Gestational diabetes mellitus
7.4.1.1. The duration of GDM is not significantly affecting the outcome of pregnancy.
The duration of GDM varies with women who developed GDM early and late, women who
developed GDM early exposed longer time to GDM and their treatment and progression of
pregnancy were also affected by GDM. Pathologically GDM would develop between the
gestational periods of 24 to 28th weeks but still women are developing GDM very early of gestation
and continuous along with GDM up to delivery. Hence we aimed to find out, whether the duration
of GDM influences the outcome of pregnancy and are there any cardinal risk factors to develop
GDM early. We grouped the women based on the diagnosis through trimester basis and week
basis, the cut off week for early and late diagnosis is – 28thweek.
Not many studies focused on the duration of GDM dividing by trimester and effects on outcome.
Riskin-Mashiahet al271 focused on first trimester glucose level and its effect on pregnancy
outcome, the study found that the elevated fasting glucose levels in first-trimester increases the
risk of adverse pregnancy outcome. Early diagnosis of GDM significantly has long duration of
pregnancy to develop adverse pregnancy outcome. Svareet al272 and Barthaet al273 concluded the
need of insulin, risk of overt diabetes mellitus and neonatal hypoglycemia were higher with
women diagnosed GDM early than women with GDM diagnosed later. Barahona et al274 resulted
that the earlier diagnosis of GDM in pregnancy is a predictor of two adverse pregnancy outcomes
namely PIH and insulin treatment, study also concluded higher incidence of poor pregnancy
outcome, except for PIH which is high in late GDM diagnosed group, with earlier diagnosis of GDM.
But Virally et al275 concluded that with intensive intervention there was no difference in the
pregnancy outcome between early and late diagnosed GDM women.
Similar observation found with our study where there was no significant difference in the
pregnancy outcome between the groups, the second trimester group women shown high
incidence of PIH. But contrary to both above mentioned Svare and Bartha studies, the third
trimester group women were higher in the need of insulin treatment. The onset of GDM doesn’t
show any influence on the development of PIH which is contrary to Barahona et al. Discussion to
neonatal outcome the LGA and macrosomic babies were found higher in women whose GDM
diagnosed early, Moses276 and Leipold277. We found similar observation with our study, as LGA
babies were more with first trimester group but contrary with macrosomia where third trimester
women had more. Contrary to Bartha study our study recorded more hypoglycemic babies with
third trimester followed to second and first trimester group.
Aqeela Ayaz et al278 in their study compared the GDM women on the basis of time they developed
GDM and concluded that, earlier diagnosis of GDM women were associated with less favorable
neonatal outcome. In our study, we found no significant difference in the pregnancy outcome
between the women who developed GDM at 1st, 2nd and 3rd trimester of gestation. Cesarean
delivery was more common for all trimester group women, 86%, 82% and 92% of cesarean
delivery was recorded with 1st,2nd and 3rd trimester group women respectively.
When compared the early and late diagnosis of GDM; results were found to be same with above
mentioned studies by Bartha et al and Barahona et al. Need of Insulin or insulin treatment was
significantly high with early developed group. The cesarean delivery was high with late GDM
developed women compared to early developed women. All the other complications were not
significantly differed between the groups of women.
7.4.1.2. Types of treatment to GDM shown no significant difference in the outcome of pregnancy
When we are comparing the outcome of pregnancy based on the treatment given; the overall
outcome shown no significant difference, except for cesarean delivery and preterm delivery,
between the women grouped according to the treatment they received.
A randomized controlled trial by Castilla et al279 with 152 GDM women were found, the low
carbohydrate diet treatment not influenced the pregnancy outcome and produced the similar
outcome compared to insulin treatment. But contrary to that, the other randomized controlled
trial conducted by Asemi et al280 found, that there was an improvement in the pregnancy outcome
for the women with GDM with DASH diet treatment. We found the similar result of Castilla et al
study, where the pregnancy outcome by insulin treatment not differed with diet treatment.
Study conducted at a maternity hospital, in Kuwait reported, that the rate of cesarean delivery was
increased with dietary treated GDM women and other perinatal outcomes were normal281. Some
studies have reported that the rate of cesarean delivery was reduced because of diet treament282.
Many studies are reporting that the cesarean delivery was higher with dietary treated GDM
women283,284 but other perinatal outcomes were normal to therm285,286. The study by Zanet al287
stated that1% babies delivered to insulin treated women had apgar score less than 7 at 1st min but
3% were reported with diet alone treated women.
We found from our study, nearly 91% of insulin treated women given birth through cesarean
section whereas 10% of diet alone women given birth through cesarean section. Preterm
deliveries are more with insulin treated women than diet alone women. Other than the cesarean
and preterm delivery there was no significant difference in outcome between these two groups of
women.
7.4.1.3. Control of glycemic level with in the normal range has given better pregnancy outcome.
When we compared the outcome of GDM women who controlled the FBS below 95 mg/dl with
GDM women who have not controlled FBS below 95 mg/dl, there was significant difference in the
cesarean delivery, term of delivery, weight of the baby and size of the baby.
Control of glucose level throughout the pregnancy in GDM contribute improvement in pregnancy
outcome288,289.290. If euglycemia is not achieved ultimately result with poor pregnancy
outcome291,292,293. Women with glucose tolerance value of 140 – 162 mg/dl have high rate of
cesarean delivery and macrosomic babies294. Similar results we have found with our study, in our
population the women who controlled glucose level above 95 mg/dl have high rate of cesarean
delivery.
The hyperglycemic and adverse pregnancy outcome (HYPO) study reported the significant
association between elevated glucose level and adverse pregnancy outcome, those are increased
birth weight, preterm delivery, cesarean delivery, hyperbilirubinemia and preeclampsia295,296. LGA
is strongly associated with GDM women of abnormal fasting glucose values297. We have found
similar results with our study; LGA babies and Low birth weight babies (LBW) were significantly
high with the women who have not controlled the blood sugar below 95 mg/dl. The perinatal
problems of cesarean delivery, preterm delivery and LGA will be more if women not treated for
abnormal glucose values298.
The obese women who have not controlled the blood glucose have twice the time of risk
compared to lean women to have LGA babies299. Same way many studies are suggesting the
increased rate of LGA in GDM women and the addition of maternal obesity again increases the
development of LGA. Similarly in our study we found that the BMI is significantly high with women
who have not controlled the glucose level below 95 mg/dl. If glucose level is not controlled under
the normal range the pregnancy outcome will be poorer and addition to this the maternal
obesity further worsen the outcome.
7.4.2. Pregnancy induced hypertension
7.4.2.1. No significant difference in terms of pregnancy outcome between different anti-
hypertensive drugs used in the treatment of PIH.
When we are comparing the outcome of pregnancy based on the treatment given; the overall
outcome shown no significant difference between the women grouped according to the drug
received for treatment. All the drugs have significantly reduced the BP from base to end. It was
similar to a study done on the comparison of Nifedipine with Methyldopa in Srilanka on 126 PIH
patients where the systolic and diastolic BP for nifedipine and methyldopa were significantly
reduced from base to end300. Same result found with the study conducted at National university
hospital, Singapore, concluded that short term treatment with methyldopa significantly reduced
the maternal blood pressure301.
Sibai et al302reported that (compared 300 PIH women for perinatal outcome of treatment by
methyldopa versus no drug) the treatment with methyldopa did not improved the pregnancy
outcome. The calcium channel blocker nifedipine controls the blood pressure as other anti-
hypertensive drugs do, but the advantages over the other drugs to pregnancy outcome need to be
established303. When compared to methyldopa the perinatal outcome was not changed with
nifedipine, both drugs were given similar pregnancy outcome300.
We also found the similar outcome as above mentioned; there were no significant changes in the
outcome of PIH between the methyldopa, nifedipine and no drug treatment. A study done on
methydopa versus no drug treatment in management of mild preeclampsia showed that there was
no much difference in the occurrence of IUGR between the methyldopa group and no drug
treatment group304. But in our study we found no difference in the incidence of IUGR between the
methyldopa group and no drug group.
Randomized clinical trial by Elhassan et al305 compared the treatment of preeclampsia between
methyldopa and no drug found; eclampsia and perinatal death were more with treatment group
than non-treatment group. Similar results found in our study, the eclampsia rate was high with no
drug compared to methyldopa group but contrary to death, one perinatal death occurred with
methyldopa group against no perinatal death with no-treatment group.
7.4.2.2. Pregnancy outcomes were not differed much with the severities of PIH, same time no
special risk factors can be identified corresponding to particular severity.
Alan Buchbinder et al179 compared the pregnancy outcome of preeclampsia with severe
hypertension and reported; there was significant difference in terms of preterm delivery and SGA,
both of this pregnancy problems are high with sever hypertension women. In our study, preterm
delivery and SGA are the important perinatal problems found with significant difference between
all the groups of women. The preterm delivery and SGA were high with mild preeclamptic women
not with gestational hypertension women. In other study the reports stated that the cesarean
delivery was more with sever preeclamptic women than chronic hypertension306, but in our study
the cesarean delivery was same across the groups.
MouniraHabli et al309 found that, other than the SGA all the perinatal outcomes were similar
between the hypertensive disorders in PIH women. We also found the same result in our study,
other than SGA and LBW the perinatal outcomes of all hypertensive disorder groups women were
same.
The assumption is that the etiology of preeclampsia, eclampsia and gestational hypertension
would vary since the definition and clinical symptoms are differs with each other. Former studies
were suggesting similar pattern of risk factors to develop these severities. A study by Rose et al310
reported that, the etiological factors are same between preeclampsia and gestational
hypertension. In our study we also found the same result as that of Rose et al, where no special or
associated risk factors was identified for any particular disorders of PIH.
7.4.3. Associations
Results showed the similarities in the underlying mechanism, and suggested the relationship
between these two complications. We found significant risk of PIH among women with GDM. Each
complication has its own influence in the pregnancy, like increase in blood pressure and increase
in sugar value.
To analyze the risk factors several studies suggested the age, family history, gravidity, parity and
multiple pregnancies has influence on development of GDM and PIH. Doherty et al311 found that
the age and prepregnancy BMI are the common risk factors for the development of both
complications GDM and PIH. Another study by Yariv Yogev et al312 reported that the prepregnancy
BMI and gestational diabetes are the important risk factors to develop preeclampsia.
Sven Schneider et al313 from Germany reported that the advanced age, BMI, multiple pregnancies
and nulliparity are the common risk factors to develop both GDM and PIH. Other study by Roach
et al314 found age, BMI and parity are the common risk factors to develop GDM and PIH. In our
study we found the similar result like above mentioned studies; advancing age, BMI, gravidity,
family history of diabetes mellitus and irregular menstrual cycle are the common risk factors for
the development of both of these complications, but contrary to Sven Schneider et al the parity
was not found to be a common risk factor to the development of GDM and PIH.
GDM women are having more risk to develop PIH. Joffe et al315 compared the non-diabetic women
and GDM women, found a higher risk for GDM women to develop PIH, 17% of GDM women
developed PIH compared to 12% from non-diabetic women. Many studies are suggesting the
influence of one complication on other. GDM women are one and half times more potent to
develop preeclampsia than non-GDM women316. The high blood pressure and the increased insulin
resistance in the GDM women are well associated with the development of preeclampsia317,318. In
our study, we found around 16% of GDM women developed hypertensive disorders of which 4% of
women developed preeclampsia and 9% of women developed severe hypertension.
Cesarean delivery was more and common in women who complicated with both of the
complications, all the women, complicated with both GDM and PIH, were delivered through
cesarean section followed to 94% from PIH alone complicated women and 86% from GDM alone
complicated women. Other perinatal problems like preterm delivery, LGA, SGA, LBW and baby
birth weight were also be the common perinatal problems of women who affected with GDM or
PIH.
8. Conclusion
Incidence of GDM in our study population was found to be high compared to PIH.
Prevalence of both the complications reduced from 2003 to 2012. Prevalence rate of GDM was
3.28% in 2003 which was reduced to 2.11% in 2012 and the prevalence rate of PIH was 2.87% in
2003 to 1.16% in 2012. But the incidence of both the complications was increasing from time.
GDM and PIH were found to be increased from 24 to 60 and 21 to 33 cases respectively.
Age, BMI, gravidity (primigravida, multigravida), parity (nulliparity, primiparity), previous GDM,
previous PIH, family history of DM and irregular menstrual cycle are found to be the risk factors for
GDM or PIH.
Advancing age, advancing BMI, advancing gravidity and advancing parity are the important and
common risk factors for causing GDM and PIH, and when this risk factor’s values reaches the
maximum greater the chances of developing both together.
The frequency patterns for development of both complications were similar, but the peak period
for occurrence is varies with values of risk factors. (For PIH, the higher frequency starts from younger
age to elder age (from 20 to linearly increase to age 25) and for GDM the higher frequency starts from
younger risky age to elder age (from 25 to linearly increase to age 29). The same kind of trend can be seen in
BMI also; the frequency of PIH increases from lean to ideal body weight (BMI of 18 to 24.99 kg/m2,), and
frequency of GDM increases form overweight to obese (BMI of 25 to 29.99 kg/m2,), when age and BMI
reaches above 30 the frequency is higher to develop both complications together).
Primigravida or the first pregnancy women are more prone to develop PIH, and when gravidity is
increasing, the risks are more to develop GDM and both together. (Significantly the average gravidity
was less with PIH women compared to GDM or both group women. GDM+PIH group women have higher
gravidity value than GDM or PIH alone women)
Nulliparity and primiparity are significant risk factors to develop both GDM and PIH, but for a
nulliparous woman the frequency is high to develop PIH first then GDM, and when parity is
increases the frequency is more with GDM, for primiparous women the frequency is high to
develop GDM than PIH. (The average parity value is less with PIH women compare to GDM women)
Women having the family history of DM are prone to develop both kind of complications, but the
frequency is significantly high with GDM than PIH. Family history of hypertension is not influence
the women to develop any complication. Paternal history of DM influences women more to
develop GDM than maternal history of DM do with women.
The previous history of GDM or PIH may not be consider as significant risk but when combined
with other risk factors this may enhance the risks for developing any complications. Previous
history of PIH significantly causes the development both complications together.
Women having more number of risk factors are more prone to develop any complication. The
increases in the number of risk factors may cause a parallel increase in the risks to develop PIH,
GDM then GDM+PIH.
When the risk factors are increasing the addition of risk factor significantly changes the probability
of developing complications. The increasing in number and values of risk factors would actually
increases the risks of women to develop the complications early. Increase in number of risk factors
may cause early development of GDM and not necessarily cause the early development of PIH.
Cesarean delivery is common in both complications, when a woman develops both complications
the greater the chances of cesarean delivery. (GDM alone women – 81% of cesarean delivery, PIH
alone women – 94% cesarean delivery, GDM+PIH woman – 100% cesarean delivery.)
All the new born babies were found to be normal and good in health. Two fetal deaths and one
maternal death were occurred as a result of PIH complication. No neonatal birth injury was
reported. The average baby weight of GDM women was within the normal range and below the
normal range for PIH women. (Average baby weight of GDM women was 2.67 ± 0.65 kg. Average baby
weight of PIH women was 2.22 ± 0.73 kg and the same was 2.45 ± 0.81 kg for GDM+PIH women).
Hypoglycemia and hyperbilirubinemia are very common in babies of GDM women. (Around 60% of
babies affected with both of above mentioned neonatal complications)
The length or duration of GDM doesn’t change the severity of perinatal outcome, whether it is
developed early or late the outcome result will be similar.
The type of treatment, whether it is diet or along with insulin, depends on the blood glucose
maintenance the perinatal outcome is similar for GDM women.
Pregnancy outcome was significantly improved with the GDM women who controlled the fasting
blood glucose level with in the normal range. Strict control of blood glucose level under the normal
range gives better pregnancy outcome in GDM. (The following perinatal complications were improved
in the GDM women who controlled fasting blood glucose level below 95 mg/dl, mode of delivery, term of
delivery, LBW, NBW, LGA and week of delivery).
Anti-hypertensive drugs nifidepine and methyldopa were significantly reducing the elevated blood
pressure to normal range and reduce the perinatal complications also as well, and pregnancy
outcome also same between these two drugs.
The increase in severity of PIH increases the perinatal complications as well. Greater the disease
severity, poorer the pregnancy outcome.
The duration, treatment and development or severity of diseases doesn’t produce significant
changes in the outcome of pregnancy, but the strict control over the disease would definitely give
the good outcome. The GDM women who strictly controlled the blood sugar level with in the
normal range showed significant improvement in the pregnancy outcome, hence, regardless to the
time of diagnosis and treatment of GDM, strict control of blood sugar level with in the normal
range would give beneficial effect to pregnancy outcome. Same way the pregnancy outcome is
worsening with the severity of PIH, and since the control of blood pressure improve the perinatal
outcome, the adequate BP control by any antihypertensive drugs within the normal range would
give a good pregnancy outcome.
The occurrence of GDM itself again act as a risk factor and causes PIH, the coexisting of these
complications influences each other and further worsen the pregnancy outcome. Since both
complications are having common risk factors and frequency of development, identifying the
women early, initiating the treatment early and strict control over the diseases definitely improve
the outcome of pregnancy.
9. Impact of the study
Gestational diabetes mellitus and pregnancy induced hypertension are the most commonly
encountered problems that occur during pregnancy and may lead to serious complications.
Maternal and neonatal morbidity and mortality were found to be high and potentially harm both
the fetus and mother. The impact of diseases continues even after the delivery to both mother
and child. The GDM affected women have 50% more chances to develop type 2 diabetes mellitus
than normal women. The offspring’s of GDM mother too affected with childhood obesity. The
preterm birth and intra uterine growth retardation leaves some traces on child hood growth,
those exposed children shows slow growth mentally and physically compared to non-exposed
children. The maternal mortality rate is still high with hypertensive disorders than any other
complications during pregnancy. But the recognition is still low to these complications.
First, this study would definitely create awareness about these complications in public. The
awareness will draw complete attention and cooperation in the management of diseases. Our
study suggests the possibilities of identifying the susceptible women by assessing the risk factors
very early even before the pregnancy. Early detection and early treatment gives a complete
understanding to health care professionals throughout the remaining pregnancy period.
Awareness and education about this model to society will make the women knowledgeable and
confident to fight against this illness.
We have aimed and developed a strategic tool to find out the susceptibility of women to have
these complications. This is basically a prediction tool assessing the biological risk factors of
women. Since the tool developed with small and single ethnic population it needs a widespread
data from different ethnic to become an adoptive model as a screening tool. Once this model is
successively developed, this will be an easy tool to screen the women in low resources settings
and rural areas.
Currently there were no universally adopted guidelines for the management of these
complications. This study results gives a broad idea about the progress and outcome of diseases. It
also suggests that control in GDM and PIH would give beneficial effect in the outcome of
pregnancy.
Education is a major part in the management of pregnancy complication which involves life style
modification, weight management, knowledge of drugs and self-monitoring of blood glucose and
blood pressure. Our study would give the information to women on all the areas of management
of these complications.
Outcome of the study provide the knowledge on cost-effective management and patient
education to the pharmacists.
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