clinical study the effects of glucose fluctuation on the...

Hindawi Publishing CorporationJournal of Diabetes ResearchVolume 2013 Article ID 576916 6 pageshttpdxdoiorg1011552013576916

Clinical StudyThe Effects of Glucose Fluctuation on the Severity ofCoronary Artery Disease in Type 2 Diabetes Mellitus

Xingguang Zhang Xiuping Xu Xiumin Jiao Jinxiao Wu Shujing Zhou and Xiaofeng Lv

General Hospital of Beijing Military Region No 5 Nan Men Cang Dongcheng Distrct Beijing 100700 China

Correspondence should be addressed to Xiaofeng Lv xiaofenglv7966163com

Received 27 March 2013 Revised 24 May 2013 Accepted 11 June 2013

Academic Editor Joseph Fomusi Ndisang

Copyright copy 2013 Xingguang Zhang et al This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

Objectives To explore the difference of glucose fluctuations between the normal subjects and diabetes mellitus (DM) patients andexplore their impact on the development of CAD in type 2 DM patientsMethods The subjects were divided into 3 groups normalcontrol (group A 119899 = 40) type 2 DMpatients without cardiovascular complications (group B 119899 = 56) and type 2 DMpatients withcardiovascular complications (group C 119899 = 92) The SYNTAX scores were collected in group C CGMS for 72 h was applied on allthe subjects The indexes such as MBG and the LAGE were calculated Glycemic excursions were compared between groups A Band C respectively Results The tested indexes had significant differences among the three groups SYNTAX scores are related tosystolic blood pressure CRP MAGE and HbA1c and are significantly correlated at 600ndash800 and 1100ndash1300 time points in groupCConclusions Compared with normal subjects T2DMpatients have greater blood glucose fluctuations T2DMpatients with CADhave larger glucose fluctuations than T2DMpatients without CAD Blood glucose fluctuations are positively correlated with carotidartery intima-media thickness in T2DM patients and have a significant influence on the development of coronary artery

1 Introduction

The incidence of type 2 diabetes mellitus (T2DM) is increas-ing these years with the improvement of peoplersquos livingstandard the changes of life style and the increasing agingpopulation Yang et al reported that the prevalence of dia-betes in adults over 20 years old was 97 and the prevalenceof prediabetes (impaired fasting glycaemia and impairedglucose tolerance) has reached 155 [1] The complicationsof T2DM almost involved each organ of the body 60ndash80of the patients died of vascular disease [2] Large vasculardisease affects the aorta coronary artery cerebral artery renalartery and peripheral artery mainly which is hard to ignoremany researchers have studied the effect of blood glucosefluctuation on the vascular complications of T2DM [3ndash6]Quagliaro et al confirmed that the blood vessel endotheliumwas damaged greater by blood glucose fluctuation than bychronic persistent hyperglycemia [6] recent studies havedemonstrated that acute and chronic fluctuations in bloodglucose levels can increase oxidative stress in type 2 diabetesmellitus patients [7] which results in cell dysfunction and

tissue injury [8] Therefore it is important to evaluate therelationship between the blood glucose fluctuation and thecoronary artery disease by dynamic glucose monitoring Suet al [9] have reported that the intraday glycemic variabilityis associated with the presence and severity of CAD inpatients with T2DM and effects of glycemic excursions onvascular complications should not be neglected in diabetesHowever the significance and value of this study were limitedby small population and less correlation analysis of someimportant medical indexes such as mean blood glucose(MBG) glucose standard deviation (SD) the largest ampli-tude of glycemic excursions (LAGE) the average amplitudeof glycemic excursions (MAGE) the number of effectiveblood glucose excursions (NEGE) and postprandial glucoseexcursions of 3 dinners (PPGE1 PPGE2 and PPGE3)

Aiming to evaluate the coronary artery disease coronaryangiography and new complexity of coronary artery diseasescoring method (SYNTAX scores) were used in the currentstudy [10] Coronary angiography is accepted as a goldenstandard for the diagnosis of coronary heart disease TheSYNTAX score is a complete angiography scoring system and

2 Journal of Diabetes Research

can be used for the comprehensive evaluation of coronarylesion The higher the score is the more severe it may befollowing treatment may be more difficult and the prognosismay be worse [11]

In this study we explored the effect of chronic bloodglucose fluctuation on coronary artery disease through study-ing T2DM patients with or without cardiovascular compli-cations Compared to previous similar studies [9] SYNTAXscore system was used to estimate the severity of coronarylesion through coronary angiography findings which is sign-ificant for the diagnosis of large vascular complications inpatients with T2DM We also provided more adequate inde-xes such asMBG SD LAGEMAGENEGE PPGE1 PPGE2and PPGE3 We also analyzed the correlation of HOMA-IR HOMA-120573 function index (HBCI) and IMT with glucosefluctuations

2 Patients and Methods

21 Subjects The study has been approved and registeredby our hospitalrsquos Ethics Committee in January 2012 theEthics Committee approved related screening treatment anddata collection of these patients written informed consentwas obtained from each patient for the use of their bloodsample and clinical information All works were undertakenfollowing the provisions of the Declaration of Helsinki

The inclusion criteria of DM patients were 50 to 69years old gender not limited type two diabetes mellitusdiagnosed according to the WHO diagnostic criteria in 1999[12] admission glucose lt167mmolL and without diabeticketosis or nonketotic hyperosmolar coma cardiovascular riskequal or higher than 10 according to continuous metabolicsyndrome risk score [13] They were excluded if they haveknown coronary artery disease symptomatic heart failureobjective inability to perform treadmill exercise known oractive malignancy advanced renal failure (serum creatineclearancelt25mLmi173m2) and liver cirrhosis (child PughIII) stroke within the past 30 days presence of left bundlebranch block or ST depression at rest greater than 09 mm

A total of 148 patients diagnosed with T2DM wereenrolled in this study these patients were suspected withcoronary artery diseaseThe coronary angiographywas cond-ucted to get the information of their coronary lesion inGeneral Hospital of Beijing Military Region PLA Healthyindividuals without history of diabetes mellitus and coronaryartery disease were recruited from volunteers of communityinhabitants in Beijing (matchedwith age range) they were setas normal control group (group A 119899 = 40)

3 Coronary Angiography

Coronary artery angiography was performed by using stan-dard Judkins techniques or a radical approach Duringcardiac catheterization nitroglycerine was administratedroutinely in all cases suspected of having coronary spasmAngiographic analysis was carried out by two experiencedinterventional cardiologists who were blinded to the studyprotocol Angiography results were divided into CAD (ge50

obstruction in ge1 coronary artery) group and non-CADgroup According to coronary angiography results 148patients were divided into 2 groups patients without car-diovascular complications (group B 119899 = 56) and withcardiovascular complications (group C 119899 = 92)

4 Routine and Biochemical Examinations

General clinical data such as the gender age bodymass index(BMI) antihypertension drug systolic pressure (SBP) anddiastolic pressure (DBP) were recorded by routine medicalexamination

Blood samples were obtained under overnight fastingconditions from these patients and high-density lipopro-tein cholesterol (HDL-c) low-density lipoprotein cholesterol(LDL-c) triglyceride (TG) total cholesterol (TC) and Creactive protein (CRP) of all subjects were measured by rou-tine blood examination Serum concentration of hemoglobinA1c (HbA1c) was determined by high-performance liquidchromatographic method using automatic HbA1c analyzer(Tosoh HLC-723G7 Japan) The SYNTAX scores in groupC were calculated with the help of professional website toolhttpwwwsyntaxscorecom

Meanwhile we tested the plasma-reduced glutathione(GSH) level in each group to evaluate the oxidative stressGSH was determined with a colorimetric assay using Biox-ytech GSH-400 kit (Oxis International Portland OR USA)based on a two-step reaction thioethers formation followedby a 120573-elimination under alkaline conditions Thioethersobtained are transformed into chromophoric thiones whichhave a maximal absorbance wavelength at 400 nm

41 Dynamic Blood Glucose Monitoring The HOMA-IR andHBCI were calculated with the homeostasis model assess-ment HOMA-IR = fasting blood glucose (FBG) times fastinginsulin (FINS)225 HBCI = 20 times FINS(FBG-35) [14]

Continuous glucose monitoring system (CGMS) for72 h was applied for all the subjects A CGMS sensor wasinserted into the subcutaneous abdominal fat tissue cal-ibrated according to the standard Medtronic MiniMedoperating guidelines The indexes of mean blood glucose(MBG) glucose standard deviation (SD) the largest ampli-tude of glycemic excursions (LAGE) the average amplitudeof glycemic excursions (MAGE) the number of effectiveblood glucose excursions (NEGE) and postprandial glucoseexcursions of 3 dinners (PPGE1 PPGE2 and PPGE3) wererecorded separately by CGMS

The MAGE was calculated by measuring the arithmeticmean of the differences between consecutive peaks andnadirs provided that the differences are greater than onestandard deviation of the mean glucose value The MODDwas calculated as the mean of the absolute differencesbetween glucose values at the same time of two consecutivedaysThePPGEwas obtained by calculating the postbreakfastincrements in blood glucose

Glycemic excursions were compared between groups AB and C The key factors impacting SYNTAX scores wereanalyzed in group C by multiple linear regression analysisBlood glucose fluctuation was recorded at 8 time sessions

Journal of Diabetes Research 3

Table 1 Comparison of the indexes in the three groups

Group A Group B Group CSex (MF) 2416 2432 4844Age (years) 563 plusmn 61 561 plusmn 66 617 plusmn 72

lowast

BMI (Kgm2) 238 plusmn 25 270 plusmn 36lowast

245 plusmn 17

CD (year) mdash 610 (454 811) 473 (277 770)Antihypertension drug user () 4 (10) 31 (554)lowastlowast 55 (598)lowastlowast

SBP (mmHg) 114 plusmn 13 124 plusmn 9 136 plusmn 18lowastlowast

DBP (mmHg) 70 (65ndash75) 72 (66ndash79) 80 (80-81)lowast

HbA1c () 53 plusmn 03 66 plusmn 12lowastlowast

75 plusmn 14lowastlowast

HDL-c (mmolL) 088 (083ndash092) 096 (092ndash127)lowast 091 (085ndash113)LDL-c (mmolL) 216 (205ndash220) 251 (178ndash292) 217 (207ndash323)TG (mmolL) 163 (158ndash166) 212 (121ndash411) 170 (142ndash223)TC (mmolL) 414 (393ndash425) 474 (405ndash479) 411 (357ndash446)GSH (mmolL) 423 plusmn 064 318 plusmn 086 224 plusmn 073

MBG (mmolL) 61 plusmn 06 81 plusmn 21lowast


MAGE (mmolL) 22 (18 28) 26 (19 35)lowastlowast 40 (33 48)lowastlowast

NEGE (times) 68 (60 77) 41 (35 47)lowastlowast 40 (34 48)lowastlowast

SDBG (mmolL) 08 plusmn 03 15 plusmn 04lowastlowast


LAGE (mmolL) 29 (26ndash45) 66 (58ndash124)lowastlowast 78 (61ndash99)lowastlowast

PPGE1 (mmolL) 27 (16ndash43) 32 (17ndash98) 46 (32ndash81)lowastlowast

PPGE2 (mmolL) 23 (17ndash35) 24 (22ndash86) 33 (26ndash54)lowast

PPGE3 (mmolL) 22 plusmn 04 27 plusmn 11 47 plusmn 25lowastlowast

IMT (mm) 06 plusmn 01 09 plusmn 03lowast


CRP (mgL) 10 (09ndash11) 11 (10ndash28)lowast 38 (28ndash54)lowastlowast

HOMA-IR 158 (152ndash169) 23 (19ndash91)lowastlowast 43 (30ndash49)lowastlowast

HBCI 87 (82ndash103) 45 (28ndash67)lowastlowast 80 (48ndash139)

SYNTAX score mdash 0 235 plusmn 59

CD course of disease Compared with group A lowast119875 lt 005 lowastlowast119875 lt 001 compared with group B 119875 lt 005 119875 lt 001

which were 000ndash300 300ndash600 600ndash800 800ndash11001100ndash1300 1300ndash1700 1700ndash1900 and 1900ndash2400 thecorrelations with SYNTAX scores were analyzed in everysection

42 Statistical Analysis If the data were normal distributiondata t-test was used in comparison of two groups and singlefactor analysis of variance was used in comparison of threegroups If the data were nonnormal distribution data rank-sum test was used in comparison between two groups andthe Kruskal-Wallis analysis was used in comparison of threegroupsThe Chi-square test was used for qualitative data testmultiple factors were analyzed by multiple linear regressionanalysis All analyses were performed using SPSS softwareprogram version 160 for Windows (SPSS Institute Inc) and119875 lt 005 was considered statistically significant

5 Results

51 The Comparison of the Indexes among the Three GroupsAfter coronary angiography DM patients were divided intogroup B and group C Table 1 showed the detailed data ofthe three groups Compared with group A (healthy control)patients from group B have significantly higher BMI (270 plusmn

36 versus 238plusmn25) antihypertension drug using rate (554versus 10) HbA1c (66plusmn12 versus 53plusmn03) HDL-c (096versus 088mmolL)MBG (81plusmn21 versus 61plusmn06mmolL)MAGE (26 versus 22mmolL) SDBG (15 plusmn 04 versus08plusmn03mmolL) LAGE (66 versus 29mmolL) IMT (09plusmn03 versus 06 plusmn 01mm) and CRP (11 versus10mgL)and significantly lower NEGE (41 versus 68 times) HBCI(45 versus 87) and GSH level (318 plusmn 086 versus 423 plusmn064mmolL) 119875 lt 005 or 001

Consistent with group B as shown in Table 1 and com-pared with group A group C had the same trend with signi-ficantly higher age antihypertension drug using rate SBPDBP HbA1c MBG MAGE SDBG LAGE PPGE1 PPGE 2PPGE3 IMT CRP HOMA-IR and GSH and lower NEGEvalue (119875 lt 005 or 119875 lt 001)

Compared with group B patients group C patients havesignificantly higher age (617 plusmn 72 versus 561 plusmn 66 yr) SBP(136 plusmn 18 versus 124 plusmn 9mmHg) DBP (80 versus 72mmHg)MAGE (40 versus 26mmolL) SDBG (20 plusmn 08 versus 15 plusmn04mmolL) PPGE3 (47plusmn25 versus 27plusmn11mmolL) IMT(11plusmn03 versus 09plusmn03mm) CRP (38 versus 11mgL) andHBCI (80 versus 45) and lower NEGE (40 versus 68 times)and GSH level (224plusmn 073 versus 423plusmn 064mmmolL) 119875 lt005 or 119875 lt 001


Table 2 Linear correlation analysis between SYNTAX scores and relative factors in group C

SYNTAX scores Age998787(years)

BMI998787(Kgm2)

SBP998787(mmHg)

DBP998771(mmHg)

CD998787(year)

CRP998787(mgL)

HbA1c998787()

119877 minus0115 0046 0551 minus0015 minus0298 0435 0488119875 0602 0836 0006 0947 0167 0038 0018

SYNTAX scores MAGE998787(mmolL) HOMA-IR998771 HBCI998771 HDL-c998771

(mmolL)LDL-c998771(mmolL)

TC998771(mmolL)

TG998771(mmolL)

119877 0518 minus0199 minus0040 0329 0183 minus0069 minus0059119875 0011 0363 0855 0125 0403 0754 0789CD course of disease 998787Pearsonrsquos correlation analysis 998771Spearmanrsquos correlation analysis

Table 3 Correlation analysis between SYNTAX scores and the blood glucose excursion of different time sessions in group C

SYNTAX scores 000ndash300 (mmolL) 300ndash600 (mmolL) 600ndash800 (mmolL) 800ndash1100 (mmolL)119877 minus0442 minus0208 0678 0115119875 0035 0340 0000 0600SYNTAX scores 1100ndash1300 (mmolL) 1300ndash1700 (mmolL) 1700ndash1900 (mmolL) 1900ndash2400 (mmolL)119877 0523 0257 0358 minus0018119875 0011 0237 0094 0933Pearson correlation analysis was used in 000ndash300 and Spearmanrsquos correlation analysis was used in otherrsquos time sessions

Table 4 Linear correlation analysis between MAGE and the related factors in groups B and C

MAGE Age BMI CD CRP HbA1c HOMA-IR HBCI IMT(years) (Kgm2) (year) (mgL) () (mm)

119877 0383 minus0193 minus0065 0599 0595 0498 minus0297 0460119875 0008 0193 0702 0000 0000 0000 0042 0001

MAGE NEGE SD MBG LAGE PPGE1 PPGE2 PPGE3(time) (mmolL) (mmolL) (mmolL) (mmolL) (mmolL) (mmolL)

119877 minus0712 0928 0576 0862 0764 0631 0672119875 0000 0000 0000 0000 0000 0000 0000CD course of disease All are analyzed with Spearmanrsquos correlation analysis

52 The Linear Correlation Analysis between SYNTAX Scoresand Relative Factors in Group C Multiple linear regressionanalysis showed the SYNTAX scores were significantly corre-latedwith CRPMAGE andHbA1c in groupC (119875 lt 005) andwere significantly correlated with SBP (119875 lt 001) (Table 2)

53 The Correlation Analysis between SYNTAX Scores and theBloodGlucose Excursion of Different Time Sessions inGroupCIn our study a day was divided into eight sessions Significantcorrelations were found in 600ndash800 (119875 lt 001) and 1100ndash1300 (119875 lt 005) between the SYNTAX scores and bloodglucose excursion in group C (Table 3)

54 The Linear Correlation Analysis between MAGE and theRelated Factors in Groups B and C After analysisMAGEwaspositively correlated with age CRP HbA1c HOMA-IR IMTSD MBG LAGE and glucose excursions before and aftermeals (119875 lt 001) and was negatively correlated with HBCI(119875 lt 005) and NEGE (119875 lt 001) both in groups B and C(Table 4)

6 Discussion

The risk of coronary heart disease (CHD) mortality in type 2diabetic patients is more than twofold higher compared withthat in age-matched healthy subjects The incidence of strokeevents and all manifestations of CHD myocardial infarction(MI) sudden death and angina pectoris are at least twofoldhigher in patients with type 2 diabetes than in nondiabeticindividuals [15] Therefore it is important to investigate therelevant affecting factors which cause such high risk

Brownlee found that too much mitochondrial reactiveoxygen species (ROS) may be a common mechanism of dia-betic complications [16]Theoxidative stresswas enhanced bythe blood sugar disorder in T2DM patients the uncompen-sated antioxidant capacity in vivo leads to endothelial dam-age thus causingmacrovascular complications In the currentstudy the lowest CGH level in group C also proved this pointCRP a biomarker of cardiovascular diseases [17] was highlyrelated toMAGE in our study Glucose excursions in subjectswith impaired glucose regulation and T2DM trigger theactivation of oxidative stress [18] MAGE was correlated withHOMA-IR positively and negatively correlated with HBCI


which suggests MAGE could affect the insulin resistance andthe function of pancreatic islets

Recently large-scale clinical studies have suggested thatonly using HbA1c for strict glycemic control is not sufficientto reduce the risk of macrovascular complications [19 20]The effects of blood glucose fluctuation on vascular compli-cations in T2DM have been researched by many scientistsHanefeldM et al found that postprandial blood glucose peakcan predict myocardial infarction better than fasting glucose[21] Ceriello et al demonstrated that accelerated oxidativestress accompanying fluctuations in blood glucose levelscould worsen endothelial dysfunction more than constanthyperglycemia [22] Torimoto et al found that fluctuationsin blood glucose levels play a significant role in vascularendothelial dysfunction in T2DM [23] Su et al found thatthe glucose variability was closely associated with the severityof cardiovascular disease in T2DM the effect of MAGE oncoronary artery was greater than that of HbA1c [9] Coletteand Monnier suggested that the MAGE can serve as the goldstandard to measure the blood glucose fluctuation [24] Wefound that MAGE in T2DM patients with coronary arterydisease was higher than that in T2DM patients withoutcoronary artery disease Multiple linear regression analysissuggested that both HbAlc and MAGE were importantfactors affecting the cardiovascular complications of T2DMbut MAGE was more predictive than HbAlc This studyalso showed that there was significant correlation betweenMAGE and IMT IMT can be used as the index of earlyatherosclerosis

In this study MAGE was positively correlated with ageCRP HbA1c HOMA-IR IMT SD MBG LAGE and glucoseexcursions before and after meal and negatively correlatedwith HBCI and NEGE It suggested that MAGE may beinfluenced by the above factors

The shortage of this research lies in that the impact ofother factors such as blood pressure age and HbA1c can-not be completely ruled out although the multiple linearregression analysis has been used these previous factorsalso can influence progression of CAD Group C patientshave higher age and antihypertension drug using rate 85of the blood pressure of them is below or near the criticalrange 14090mm Hg Previous studies have reported thatDM patients with pressure below 140mm Hg can benefitfromaggressive antihypertensive treatment [25] Besides thatother few limitations of this study should be mentionedFirstly the sample size was relatively small in this studyso some subgroup comparisons may have lacked power todetect significant differences for selected variables Secondlyalthough we had maintained the patients antihyperglycemictherapy as usual and avoided glucose infusion during CGMSmonitoring period some factors such as different diets andphysical and emotional stress which may affect levels ofadmission glucose fluctuations could not be all preventedThirdly lack of microvascular complications data in anotherlimitation we did not include those risk factors in study

Currently although there is still an extensive debate aboutglucose fluctuation as a risk factor for complications inde-pendent of HbA1c in diabetes [26 27] by this present studywe provide some evidence to suggest that at least glucose

fluctuation has potential to be a risk factor for predicting theoccurrence and progression of CAD it can be helpful to testthis index in clinical treatment for DM patients

7 Conclusions

Compared with normal subjects T2DMpatients have greaterblood glucose fluctuations and higher average blood glu-cose T2DM patients with larger glucose fluctuations couldhave higher risk for coronary artery disease compared withpatients having smaller glucose fluctuations Compared withhigh blood glucose blood glucose fluctuations may be moreimportantly influential on the development of coronaryartery disease in patients with T2DM Blood glucose fluctu-ation is significantly related to carotid artery intima-mediathickness in T2DM

Abbreviations

BMI Body mass indexCD Course of diseaseCGMS Continuous glucose monitoring systemCRP C reactive proteinDBP Diastolic pressureDM Diabetes mellitusHbA1c Hemoglobin A1cHBCI HOMA 120573-cell function indexHDL-c High-density lipoprotein cholesterolHOMA-IR HOMA insulin resistance indexLAGE Largest amplitude of glycemic excursionsLDL-c Low-density lipoprotein cholesterolMAGE Mean amplitude of glycemic excursionsMBG Mean blood glucoseNEGE Number of effective glucose excursionsPPGE1 Postprandial glucose excursions of breakfastPPGE2 Postprandial glucose excursions of lunchPPGE3 Postprandial glucose excursions of supperSBP Systolic pressureSDBG Standard deviation of blood glucoseTC Total cholesterolTG TriglycerideSYNTAX Synergy between PCI with taxus and cardiac

surgeryCAD Coronary artery disease

Conflict of Interests

The authors have no conflict of interests to declare

References

[1] Z-J Yang J Liu J-P Ge L Chen Z-G Zhao and W-YYang ldquoPrevalence of cardiovascular disease risk factor in theChinese population the 2007-2008 China National Diabetesand Metabolic Disorders Studyrdquo European Heart Journal vol33 no 2 pp 213ndash220 2012

[2] R Huxley F Barzi and M Woodward ldquoExcess risk of fatalcoronary heart disease associated with diabetes in men andwomen meta-analysis of 37 prospective cohort studiesrdquo BritishMedical Journal vol 332 no 7533 pp 73ndash76 2006


[3] F Cavalot A Petrelli M Traversa et al ldquoPostprandial bloodglucose is a stronger predictor of cardiovascular events thanfasting blood glucose in type 2 diabetes mellitus particularlyin women lessons from the San Luigi Gonzaga Diabetes StudyrdquoJournal of Clinical Endocrinology and Metabolism vol 91 no 3pp 813ndash819 2006

[4] M Muggeo G Zoppini E Bonora et al ldquoFasting plasmaglucose variability predicts 10-year survival of type 2 diabeticpatients the Verona Diabetes Studyrdquo Diabetes Care vol 23 no1 pp 45ndash50 2000

[5] G Zoppini G Verlato G Targher E Bonora M TrombettaandMMuggeo ldquoVariability of body weight pulse pressure andglycaemia strongly predict total mortality in elderly type 2 dia-betic patientsTheVeronaDiabetes StudyrdquoDiabetesMetabolismResearch and Reviews vol 24 no 8 pp 624ndash628 2008

[6] L Quagliaro L Piconi R Assaloni L Martinelli E Motzand A Ceriello ldquoIntermittent high glucose enhances apoptosisrelated to oxidative stress in human umbilical vein endothelialcells the role of protein kinase C and NAD(P)H-oxidase acti-vationrdquo Diabetes vol 52 no 11 pp 2795ndash2804 2003

[7] C-M Chang C-J Hsieh J-C Huang and I-C Huang ldquoAcuteand chronic fluctuations in blood glucose levels can increaseoxidative stress in type 2 diabetes mellitusrdquo Acta Diabetologicavol 49 supplement 1 pp S171ndashS177 2012

[8] A Piwowar M Knapik-Kordecka and M Warwas ldquoOxidativestress and endothelium dysfunction in diabetes mellitus type 2rdquoPolski Merkuriusz Lekarski vol 25 no 146 pp 120ndash123 2008

[9] G Su S Mi H Tao et al ldquoAssociation of glycemic variabilityand the presence and severity of coronary artery disease inpatients with type 2 diabetesrdquo Cardiovascular Diabetology vol10 article 19 2011

[10] T Palmerini P Genereux A Caixeta et al ldquoPrognostic value ofthe SYNTAX score in patients with acute coronary syndromesundergoing percutaneous coronary intervention analysis fromthe ACUITY (Acute Catheterization and Urgent InterventionTriage StrategY) trialrdquo Journal of the American College ofCardiology vol 57 no 24 pp 2389ndash2397 2011

[11] D Y Sahin M Gur Z Elbasan et al ldquoSYNTAX score is a pre-dictor of angiographic no-reflow in patients with ST-elevationmyocardial infarction treated with a primary percutaneouscoronary interventionrdquo Coronary Artery Disease vol 24 no 2pp 148ndash153 2013

[12] P G Colman D W Thomas P Z Zimmet T A Welborn PGarcia-Webb and M P Moore ldquoNew classification and criteriafor diagnosis of diabetes mellitus The Australasian Work-ing Party on Diagnostic Criteria for Diabetes Mellitusrdquo NewZealand Medical Journal vol 112 no 1086 pp 139ndash141 1999

[13] G-D Kang L Guo Z-R Guo X-S Hu M Wu and H-T Yang ldquoContinuous metabolic syndrome risk score for pre-dicting cardiovascular disease in the Chinese populationrdquo AsiaPacific Journal of ClinicalNutrition vol 21 no 1 pp 88ndash96 2012

[14] C Cobelli G M Toffolo C Dalla Man et al ldquoAssessment of 120573-cell function in humans simultaneously with insulin sensitivityand hepatic extraction from intravenous and oral glucose testsrdquoAmerican Journal of Physiology vol 293 no 1 pp E1ndashE15 2007

[15] Z T Bloomgarden ldquoCardiovascular disease in diabetesrdquo Dia-betes Care vol 31 no 6 pp 1260ndash1266 2008

[16] M Brownlee ldquoBiochemistry and molecular cell biology ofdiabetic complicationsrdquo Nature vol 414 no 6865 pp 813ndash8202001

[17] M S Joshi L Tong A C Cook et al ldquoIncreased myocardialprevalence of C-reactive protein in human coronary heart

disease direct effects on microvessel density and endothelialcell survivalrdquo Cardiovascular Pathology vol 21 pp 428ndash4352012

[18] F ZhengW Lu C Jia H Li ZWang andW Jia ldquoRelationshipsbetween glucose excursion and the activation of oxidative stressin patients with newly diagnosed type 2 diabetes or impairedglucose regulationrdquo Endocrine vol 37 no 1 pp 201ndash208 2010

[19] A Patel S MacMahon J Chalmers et al ldquoIntensive bloodglucose control and vascular outcomes in patients with type 2diabetesrdquoTheNew England Journal of Medicine vol 358 no 24pp 2560ndash2572 2008

[20] H C Gerstein M E Miller R P Byington et al ldquoEffects ofintensive glucose lowering in type 2 diabetesrdquoTheNew EnglandJournal of Medicine vol 358 no 24 pp 2545ndash2559 2008

[21] M Hanefeld S Fischer U Julius et al ldquoRisk factors formyocardial infarction and death in newly detectedNIDDM theDiabetes Intervention Study 11-year follow-uprdquo Diabetologiavol 39 no 12 pp 1577ndash1583 1996

[22] A Ceriello K Esposito L Piconi et al ldquoOscillating glucose ismore deleterious to endothelial function and oxidative stressthan mean glucose in normal and type 2 diabetic patientsrdquoDiabetes vol 57 no 5 pp 1349ndash1354 2008

[23] K Torimoto Y Okada H Mori and Y Tanaka ldquoRelationshipbetween fluctuations in glucose levels measured by continuousglucose monitoring and vascular endothelial dysfunction intype 2 diabetes mellitusrdquo Cardiovascular Diabetology vol 12article 1 2013

[24] C Colette and L Monnier ldquoAcute glucose fluctuations andchronic sustained hyperglycemia as risk factors for cardiovas-cular diseases in patients with type 2 diabetesrdquo Hormone andMetabolic Research vol 39 no 9 pp 683ndash686 2007

[25] X Geng W Cui X H Yang R Q Xie J D Zhang and H MZheng ldquoThe efficacy of antihypertensive treatment on diabetesmellitus or impaired glucose tolerance patients with bloodpressure below 14090mm Hg a meta-analysisrdquo Zhonghua NeiKe Za Zhi vol 51 pp 875ndash879 2012

[26] E S Kilpatrick A S Rigby and S L Atkin ldquoFor debate Glucosevariability and diabetes complication risk we need to know theanswerrdquo Diabetic Medicine vol 27 no 8 pp 868ndash871 2010

[27] S E Siegelaar F Holleman J B L Hoekstra and J H DeVriesldquoGlucose variability does it matterrdquo Endocrine Reviews vol 31no 2 pp 171ndash182 2010

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Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom


can be used for the comprehensive evaluation of coronarylesion The higher the score is the more severe it may befollowing treatment may be more difficult and the prognosismay be worse [11]

In this study we explored the effect of chronic bloodglucose fluctuation on coronary artery disease through study-ing T2DM patients with or without cardiovascular compli-cations Compared to previous similar studies [9] SYNTAXscore system was used to estimate the severity of coronarylesion through coronary angiography findings which is sign-ificant for the diagnosis of large vascular complications inpatients with T2DM We also provided more adequate inde-xes such asMBG SD LAGEMAGENEGE PPGE1 PPGE2and PPGE3 We also analyzed the correlation of HOMA-IR HOMA-120573 function index (HBCI) and IMT with glucosefluctuations

2 Patients and Methods

21 Subjects The study has been approved and registeredby our hospitalrsquos Ethics Committee in January 2012 theEthics Committee approved related screening treatment anddata collection of these patients written informed consentwas obtained from each patient for the use of their bloodsample and clinical information All works were undertakenfollowing the provisions of the Declaration of Helsinki

The inclusion criteria of DM patients were 50 to 69years old gender not limited type two diabetes mellitusdiagnosed according to the WHO diagnostic criteria in 1999[12] admission glucose lt167mmolL and without diabeticketosis or nonketotic hyperosmolar coma cardiovascular riskequal or higher than 10 according to continuous metabolicsyndrome risk score [13] They were excluded if they haveknown coronary artery disease symptomatic heart failureobjective inability to perform treadmill exercise known oractive malignancy advanced renal failure (serum creatineclearancelt25mLmi173m2) and liver cirrhosis (child PughIII) stroke within the past 30 days presence of left bundlebranch block or ST depression at rest greater than 09 mm

A total of 148 patients diagnosed with T2DM wereenrolled in this study these patients were suspected withcoronary artery diseaseThe coronary angiographywas cond-ucted to get the information of their coronary lesion inGeneral Hospital of Beijing Military Region PLA Healthyindividuals without history of diabetes mellitus and coronaryartery disease were recruited from volunteers of communityinhabitants in Beijing (matchedwith age range) they were setas normal control group (group A 119899 = 40)

3 Coronary Angiography

Coronary artery angiography was performed by using stan-dard Judkins techniques or a radical approach Duringcardiac catheterization nitroglycerine was administratedroutinely in all cases suspected of having coronary spasmAngiographic analysis was carried out by two experiencedinterventional cardiologists who were blinded to the studyprotocol Angiography results were divided into CAD (ge50

obstruction in ge1 coronary artery) group and non-CADgroup According to coronary angiography results 148patients were divided into 2 groups patients without car-diovascular complications (group B 119899 = 56) and withcardiovascular complications (group C 119899 = 92)

4 Routine and Biochemical Examinations

General clinical data such as the gender age bodymass index(BMI) antihypertension drug systolic pressure (SBP) anddiastolic pressure (DBP) were recorded by routine medicalexamination

Blood samples were obtained under overnight fastingconditions from these patients and high-density lipopro-tein cholesterol (HDL-c) low-density lipoprotein cholesterol(LDL-c) triglyceride (TG) total cholesterol (TC) and Creactive protein (CRP) of all subjects were measured by rou-tine blood examination Serum concentration of hemoglobinA1c (HbA1c) was determined by high-performance liquidchromatographic method using automatic HbA1c analyzer(Tosoh HLC-723G7 Japan) The SYNTAX scores in groupC were calculated with the help of professional website toolhttpwwwsyntaxscorecom

Meanwhile we tested the plasma-reduced glutathione(GSH) level in each group to evaluate the oxidative stressGSH was determined with a colorimetric assay using Biox-ytech GSH-400 kit (Oxis International Portland OR USA)based on a two-step reaction thioethers formation followedby a 120573-elimination under alkaline conditions Thioethersobtained are transformed into chromophoric thiones whichhave a maximal absorbance wavelength at 400 nm

41 Dynamic Blood Glucose Monitoring The HOMA-IR andHBCI were calculated with the homeostasis model assess-ment HOMA-IR = fasting blood glucose (FBG) times fastinginsulin (FINS)225 HBCI = 20 times FINS(FBG-35) [14]

Continuous glucose monitoring system (CGMS) for72 h was applied for all the subjects A CGMS sensor wasinserted into the subcutaneous abdominal fat tissue cal-ibrated according to the standard Medtronic MiniMedoperating guidelines The indexes of mean blood glucose(MBG) glucose standard deviation (SD) the largest ampli-tude of glycemic excursions (LAGE) the average amplitudeof glycemic excursions (MAGE) the number of effectiveblood glucose excursions (NEGE) and postprandial glucoseexcursions of 3 dinners (PPGE1 PPGE2 and PPGE3) wererecorded separately by CGMS

The MAGE was calculated by measuring the arithmeticmean of the differences between consecutive peaks andnadirs provided that the differences are greater than onestandard deviation of the mean glucose value The MODDwas calculated as the mean of the absolute differencesbetween glucose values at the same time of two consecutivedaysThePPGEwas obtained by calculating the postbreakfastincrements in blood glucose

Glycemic excursions were compared between groups AB and C The key factors impacting SYNTAX scores wereanalyzed in group C by multiple linear regression analysisBlood glucose fluctuation was recorded at 8 time sessions




lowast


245 plusmn 17


























5 Results








BMI998787(Kgm2)

SBP998787(mmHg)

DBP998771(mmHg)

CD998787(year)

CRP998787(mgL)

HbA1c998787()




TC998771(mmolL)

TG998771(mmolL)












6 Discussion










7 Conclusions


Abbreviations





References



































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of



















lowast


245 plusmn 17


























5 Results








BMI998787(Kgm2)

SBP998787(mmHg)

DBP998771(mmHg)

CD998787(year)

CRP998787(mgL)

HbA1c998787()




TC998771(mmolL)

TG998771(mmolL)












6 Discussion










7 Conclusions


Abbreviations





References



































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of



















BMI998787(Kgm2)

SBP998787(mmHg)

DBP998771(mmHg)

CD998787(year)

CRP998787(mgL)

HbA1c998787()




TC998771(mmolL)

TG998771(mmolL)












6 Discussion










7 Conclusions


Abbreviations





References



































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of























7 Conclusions


Abbreviations





References



































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of
















































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of
















clinical study the effects of glucose fluctuation on the...

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