Received: 16 May 2001Accepted: 10 April 2002Published online: 15 June 2002© Springer-Verlag 2002

Abstract Objective: To evaluatehealth-related quality of life (HR-QOL) and study its determi-nants in adult patients dischargedfrom an intensive care unit (ICU).Design: Cohort study. Setting: Inten-sive care unit (ICU), tertiary carehospital, Oporto, Portugal. Patients: Of all the patients dis-charged over a 2year period, 355 wereconsidered eligible and 275 comple-ted the study. Measurements and results: Patients were interviewed6 months after ICU discharge usingEuroQol 5-D (EQ-5D). At the inter-view only 29% reported feelingworse than 6 months before ICU ad-mission. The proportions of those re-porting moderate to extreme prob-lems in the five dimensions studiedwere as follows: mobility (37%),self-care (22%), usual activities(46%), pain/discomfort (45%) andanxiety/depression (54%). Although77% of patients reported a problemin at least one dimension, 44% re-

ferred to no problems or only moder-ate problems regarding pain or anxi-ety. EQ visual analogue scale (VAS)and EQ Index medians were 60 and81, respectively. Conclusions: Inten-sive care unit variables (e.g., diagno-sis, length of stay and severity ofdisease) and patient’s backgrounddata (e.g., age, gender, education,main activity, smoking habits, expe-rience with serious illness and previ-ous health status) may be significantdeterminants of HR-QOL. However,when adjusted for background data,most ICU variables are no longer as-sociated with EQ-5D. This shouldcause attention to be paid to the roleof a patient’s background in the eval-uation of HR-QOL and to a carefulinterpretation of EQ-5D results whencomparing ICUs.

Keywords Evaluation · Intensivecare · Quality of life · EuroQol · EQ-5D questionnaire

Intensive Care Med (2002) 28:898–907DOI 10.1007/s00134-002-1345-z O R I G I N A L

Cristina GranjaArmando Teixeira-PintoAltamiro Costa-Pereira

Quality of life after intensive care – evaluation with EQ-5D questionnaire

Introduction

Intensive care units (ICUs) are designed for managementof critically ill patients with a wide range of surgical andmedical conditions. Whilst ICUs provide treatment in-tended to save lives, some patients do not survive and,among the survivors, some are left with physical and/ormental disabilities. Furthermore, the rising cost of inten-sive care has been prompting questions concerning thebenefit of such care and, correspondingly, has motivatedthe evaluation of intensive care outcome [1, 2].

In contrast to the amount of data relating to the effectof ICU care on survival, evaluation of quality of life hasbeen scarce [1, 2]. Recently, Heyland et al. concludedthat health-related quality of life (HR-QOL) assessmentsoccur infrequently in the ICU literature and are of limit-ed methodological quality, and they recommended thatmore studies using valid and reliable instruments shouldbe undertaken to document the long-term HR-QOL ofcritically ill patients, especially those at risk of a “poor”outcome [2]. More recently, K.L. Grady, in an editorialcomment [3], advised continued study of HR-QOL out-

C. Granja (✉ )Intensive Care Unit, Hospital Pedro Hispano, 4450, Matosinhos, Portugale-mail: cristinagranja@hotmail.comTel.: +351-22-9391169Fax: +351-22-9391654

A. Teixeira-Pinto · A. Costa-PereiraDepartment of Biostatistics and Medical Informatics, Faculty of Medicine of the University of Oporto, Alameda Prof Hernani Monteiro,4250–319, Oporto, Portugal

899

comes in critically ill patients, recommending the same standards of methodological rigour as the study ofHR-QOL in chronically ill populations. HR-QOL is asubjective concept, primarily reflecting individual pa-tients’ attitudes; measuring HR-QOL is in essence evalu-ating the health status of individuals, both mental andphysical, and their own sense of well-being [4]. A num-ber of reasons make this evaluation difficult: first, thetiming of data collection from critically ill patients; thenthe choice of particular dimensions to be included; alsothe lack of consensus over the instruments to be usedand, finally, the interpretation of the results [4, 5, 6, 7].

Many instruments have been devised [4, 5, 6, 7, 8, 9,10, 11] and HR-QOL after hospital discharge is increas-ingly being used and accepted as a relevant measure ofICU outcome [2, 3, 5, 12]. A number of questionnairesaimed at measuring specific dimensions of quality of lifehave been developed, using different criteria dependingon the aim of the study and the patient population [6, 7,8, 10, 11]. One such instrument is the EuroQol 5-D (EQ-5D), a generic HR-QOL instrument which was de-veloped at an European level [13, 14]. The EQ-5D hasbeen used both in healthy populations [15, 16] and in anumber of patients with specific diseases [17], includingcritically ill patients [18]. It is designed for use in clini-cal activities, allowing the evaluation of medical inter-ventions at the community level and for health policy[14, 15]. Examining post-hospital non-fatal outcomesalso enables us to understand the needs and problems ofICU survivors and to develop systems for the care of pa-tients after discharge from the ICU [19].

This study aims to evaluate the HR-QOL in ICU pa-tients 6 months after being discharged and to study pos-sible determinants of HR-QOL, such as ICU variablesand patient background data.

Patients and methods

Patients

This study addressed all adult patients (18 years old or more) dis-charged from an eight-bed medical/surgical ICU between 1st May1997 and 31st July 1999. Patients readmitted during the study pe-riod were enrolled in relation to the time of their first admission.Children, those who died before the 6month follow-up time hadbeen completed, patients from distant locations and those whowere bedridden and/or in prison were excluded afterwards. Thestudy was approved by the hospital’s ethics committee.

Background and intensive care unit variables

Background variables included the patient’s age, gender, educa-tion, main activity, smoking habit, experience with serious illness(the patient himself, with his family or in caring for others) andprevious health status. Previous health status was evaluated ac-cording to three main categories: healthy, chronic non-disablingdiseases (i.e. able to work or normal daily activities) and chronicdisabling diseases (i.e. unable to work or to undertake normal

daily activities). ICU variables included diagnosis, severity of disease at admission and length of stay (LOS).

EuroQol 5-D questionnaire

The EQ-5D questionnaire is a generic instrument designed to mea-sure health outcome, which was developed in 1990 and furthermodified to the current version with five dimensions in 1991 bythe EuroQol Group [14, 15]. The Portuguese version of the EQ-5Dwas originally developed by the EuroQol group in 1998 [20]. TheEQ-5D comprises two parts: the EQ-5D self-classifier, a self-reported description of health problems according to a five-dimen-sional classification (i.e., mobility, self-care, usual activities,pain/discomfort and anxiety/depression) and the EQ VAS, a self-rated health status using a visual analogue scale (VAS), similar toa thermometer, to record the perceptions of a participant’s currentoverall health; the scale is graduated from 0 (the worst imaginablehealth state) to 100 (the best imaginable state) [15, 20]. In both,the time frame is the day of responding. An index (EQ Index),based on the five dimensions and the EQ VAS and ranging from 0to 100, was also calculated and used to describe the overall QOLof these patients [17, 21].

Because the ICU stay was only 6 months before the interview,the “perceived current health status” required in the EQ-5D ques-tionnaire was changed from “Compared with my general level ofhealth over the past 12 months, my health state today is better/thesame/worse” to “Compared with my general level of health12 months ago my health state today is better/the same/ worse”.All questionnaires were applied by one of the authors during a fol-low-up consultation 6 months after discharge.

Statistical analysis

Statistical analysis was performed using SPSS 10.0.7. The resultsrelated to the self-reported description of health problems were de-scribed according to ICU variables, patient’s background data andperceived current health state. Pearson’s chi-square and linear bylinear association chi-square tests were used for analysis of cate-gorical data while median tests, Mann-Whitney and Pearson corre-lation, were used for continuous variables. Statistical significancewas considered at p less than 0.05. Medians were used for centraltendency whenever the distribution of variables was skewed. Mul-tiple logistic regressions were performed to analyse how ICU andbackground variables together were related with problems report-ed in each EQ-5D dimension (dichotomised in “no problems” and“moderate/extreme problems”). Linear regressions were also usedfor EQ VAS and the EQ Index for the same purpose. A stepwisemethod was used to select the variables for all regressions.

Results

Participants and non-participants

Between April 1997 and July 1999, 656 patients wereadmitted to the ICU. Fifty-six percent were male, themedian (minimum-maximum) age was 60 (1–92), medi-an APACHE II was 15 (0–58) and median LOS was2 days (1–120). Hundred twenty-seven (19%) patientsdied in the ICU and a further 41 (6%) patients died in theward after ICU discharge.

Of the 488 patients who were discharged from hospi-tal, 67 (14%) were excluded from the study: 42 died dur-

900

ing the 6month follow-up period and 25 were children.Of the remaining 421 patients, 66 (13%) did not have theopportunity to answer the questionnaire as: 59 lived indistant locations and do not attend our out-patient clinic(they are normally referred to a nearby hospital); 4 wereconfined to bed at home; 3 returned to prison. Of the 355who were asked to attend the follow-up clinic, 275 cameand answered the EQ-5D questionnaire and the remain-ing 80 did not attend their scheduled follow-up consulta-tion at 6 months.

Overall, the 146 non-participants (66 who were notasked to answer the questionnaire and 80 who did not at-tend the follow-up) were significantly older (65 versus 57)than the 275 participants (Table 1). Among medical, non-scheduled surgery and trauma patients there were no statis-tically significant differences between participants and non-participants regarding age, LOS and APACHE II (Table 1).

Intensive care unit variables

Given the diverse nature of illness in a general ICU,long-term outcome is expected to be quite variable. Thepatients were therefore grouped into four main catego-ries of diagnosis, namely, medical, scheduled and non-scheduled surgery, and multiple trauma. Of a total of 656patients, 45% of the patients were admitted for medicalreasons (respiratory infection and pneumonia being themost frequent diagnoses); 33% of the patients were ad-mitted after scheduled surgery (thus postoperative respi-ratory failure and craniotomy for neoplasm were themost frequent diagnoses); 18% for non-scheduled sur-gery (in whom postoperative respiratory failure and sep-sis were the most frequent diagnoses), and 4% after mul-tiple trauma. The 6month mortality rates from these fourgroups ranged from 14% among scheduled surgery pa-tients to 44% among medical patients, and were stronglyrelated to the APACHE II scores (data not shown).

Background data

Of the 275 participants, 57% were male and the medianage was 57 years. Regarding education, 48% did notcontinue their education after minimum schooling; interms of main activity, 54% were retired and 22% wereemployed; regarding smoking habits, 52% were currentor ex-smokers. Prior to ICU admission, 28% of the participants were healthy, 51% exhibited chronic non-disabling diseases and 21% had chronic disabling diseases.

Health status before intensive care unit and 6 months after discharge

Regarding the comparison between their perceivedhealth status currently and 12 months ago (6 months be-fore ICU), overall, 54% stated their general level ofhealth was better on the day of testing and only 29%considered that it was worse at that time than previously.However, according to main diagnosis at ICU admission,63% of the scheduled surgery patients claimed to be bet-ter on the day of testing in contrast to 54% of non-sched-uled surgery patients, 42% of the medical patients andonly 22% among multiple trauma patients. Patients whoreported feeling worse at testing were those who had sig-nificantly longer stays in the ICU (median LOS 2 dayscompared with only 1 day among those who reportedfeeling better at testing).

Description of EuroQol-5D questionnaire

Seventy-seven percent of the patients reported a problem(moderate or extreme) in at least one dimension.

The four most frequent health states (combinationsof the answers to the five dimensions), including 44%of all participants, showed no problems or only moder-

Table 1 EuroQol visual analogue scale (EQ VAS) and EuroQol In-dex (EQ Index) among responders to the questionnaire and com-parison to the non-responders regarding age, length of stay (LOS)and APACHE II scores according to main diagnosis at ICU admis-

sions. Sixty-six did not have the opportunity to answer the ques-tionnaire and 80 did not attend their scheduled follow-up consulta-tion at 6 months are included

Main diagnosis Responders Non-responders

n (%) EQ VAS EQ Index Age LOS (days) APACHE II n (%) Age LOS (days) APACHE IIMedian Median Median Median Median Median Median Median

Scheduled surgery 132 (48) 63 76 58* 1 9* 45 (31) 68* 1 10*Medical 95 (34) 60 82 50 6 17 58 (40) 58 5 17Non-scheduled 38 (14) 60 77 70 2 15 35 (24) 71 3 14surgeryMultiple trauma 10 (4) 70 59 46 7 9 8 (5) 43 3 11Total 275 (100) 60 81 57* 2 13* 146 (100) 65* 3 14*

* Significant difference between responders and non-responders using the Mann-Whitney test

901

ate problems in pain or anxiety (Table2). Thirteen per-cent of patients reported moderate to extreme problemsof anxiety/depression without any problems in the otherfour dimensions. No other dimension was describedalone as extreme with all other dimensions withoutproblems. In general, there was a decrease in the medi-an EQ VAS with the increase of reported problems in the five dimensions. The most frequently reportedsymptom was anxiety/depression, where 54% patientsreported moderate to extreme problems. In contrast, on-ly 22% reported moderate to extreme problems in self-care. However, this percentage increased when patientswere asked about their mobility, usual activities andpain/discomfort, where 37%, 46% and 45%, respective-ly, reported moderate to extreme problems (Tables 3and 4).

The median EQ VAS was 60 (Table 2) with 90% ofthe values reported ranging between 10 and 99. The me-dian EQ Index was greater than 75 for all except themultiple trauma diagnostic group (Table 2).

Determinants of the EuroQol-5D self-classifier

Mobility, self-care and usual activities

Severity of disease at admission (APACHE II) and diag-nosis were significantly and positively related to report-ed problems in mobility. In the self-care and usual activi-ties dimensions only severity of disease at admissionwas significantly and positively related to problems re-ported in those dimensions. Although LOS was consis-

tently greater in those reporting extreme problems, thesedifferences did not achieve statistical significance. Interms of main activity, retired and housework patients re-ported more problems in the three dimensions; regardingage and education, older and less educated patients re-ported more problems. Previous chronic disease was as-sociated with more problems in all the three dimensions.Patients who experienced serious illnesses themselvesreported fewer problems in mobility, while those whoexperienced serious illnesses in their relatives reportedfewer problems with self-care. Patients who smoked, orused to smoke, reported fewer problems in the mobilityand usual activities dimensions (Table 3). As expected,perceived current health state was significantly associat-ed with specific reporting of problems in all or any ofthese dimensions (Table 3).

Pain/discomfort and anxiety/depression

Older patients and those with less education reportedmore moderate and extreme problems related to pain/discomfort. Previous chronic disease was associated withmore problems in both dimensions. In addition, patientsthat were admitted to the ICU after multiple trauma andnon-scheduled surgery reported more problems thanthose admitted after scheduled surgery or for medicalreasons. Anxiety/depression was the dimension with ahigher percentage of moderate and extreme problems.Patients admitted for multiple trauma and after sched-uled surgery reported more problems with anxiety/depression (Table 4).

Table 2 Most frequent healthstates and corresponding medi-an, minimum and maximumvalues of the reported visualanalogue scale (VAS) Catego-ries of the dimensions: mobility(M), self-care (SC), usual activ-ities (UA), pain/discomfort(P/D) and anxiety/depression(A/D) (n=275)

Health state n (%) EQ VAS EQ IndexValue

M SC UA P/D A/D Median (Minimum,maximum)

1 1 1 1 1 62 (23) 80 (50, 100) 1001 1 1 1 2 28 (10) 70 (5, 95) 911 1 1 2 2 18 (7) 60 (50, 80) 811 1 1 2 1 10 (4) 70 (9, 80) 911 1 2 2 2 8 (3) 73 (40, 80) 672 1 2 2 2 8 (3) 45 (15, 90) 531 1 2 1 2 8 (3) 50 (40, 70) 761 1 1 1 3 7 (3) 50 (0, 95) 822 1 2 2 1 6 (2) 65 (5, 75) 622 2 2 2 1 6 (2) 70 (30, 90) 591 1 2 1 1 5 (2) 70 (30, 80) 851 1 2 2 1 5 (2) 30 (0, 50) 761 1 3 2 2 5 (2) 60 (40, 70) 522 1 1 2 1 5 (2) 55 (50, 60) 772 1 2 1 1 5 (2) 50 (50, 90) 722 2 2 2 2 5 (2) 58 (30, 70) 502 3 3 2 2 5 (2) 30 (10, 50) 32Sub-total 196 (71) 70 (0, 100) 91*Other heath states 79 (29) 50 (9, 99) 57*Total 275 (100) 60 (0, 100) 81*

1= no problems, 2= moderateproblems, 3= extreme problems*Median

902

Table 3 Problems reported in mobility, self-care and usual activities according to ICU variables, background data and perceived currenthealth state (n=268)

Problems in mobility Problems in self care Problems in usual activities

None Moderate Extreme None Moderate Extreme None Moderate Extreme63% 34% 3% 78% 13% 9% 54% 30% 16%

ICU variablesICU stay (days, n=267) Median 2 2 5 2 2 3 2 1 3

DiagnosisScheduled surgery % 65 35 0 82 12 6 52 37 11(n=129, 48%)Non-scheduled surgery % 51 49 0 62 24 14 52 24 24(n=37, 14%)Medical (n=93, 35%) % 68 25 7 80 8 12 60 20 20Multiple trauma (n=9, 3%) % 44 44 12 67 22 11 44 44 12APACHE II at admission Median 11 14 17 11 14 16 11 12 15(n=267)

Background dataAge in years (n=268) Median 51 67 64 54 68 69 52 62 63

GenderMale (n=153, 57%) % 69 28 3 76 14 10 53 27 20Female (n=115, 43%) % 56 41 3 80 11 9 56 34 10

Minimum educationNo (n=127, 48%) % 54 42 4 70 20 10 47 35 18Yes (n=136, 52%) % 72 26 2 85 7 8 62 26 12

Main activityEmployed (n=58, 22%) % 88 12 0 95 2 3 83 10 7Retired (n=142, 54%) % 51 44 5 66 20 14 42 35 23Housework (n=18, 7%) % 50 50 0 83 11 6 50 44 6Student (n=5, 2%) % 100 0 0 100 0 0 100 0 0Seeking work (n=11, 4%) % 100 0 0 100 0 0 64 36 0Other (n=29, 11%) % 66 31 3 90 7 3 48 42 10

Smoking habitsSmoker (n=35, 13%) % 86 14 0 89 11 0 77 17 6Ex-smoker (n=102, 39%) % 64 31 5 74 15 11 52 28 20Never smoked % 57 41 2 78 12 10 50 36 14(n=125, 48%)

Previous health statusHealthy (n=77, 28%) % 82 17 1 88 8 4 72 20 8Chronic non-disabling % 60 38 2 75 17 8 49 36 15disease(n= 139, 51%)Chronic disabling disease % 43 47 10 67 9 24 40 28 33(n=58, 21%)

Experience with serious illness in the familyNo (n=189, 80%) % 61 35 4 76 15 9 54 29 17Yes (n=48, 20%) % 73 27 0 92 8 0 56 40 4

Experience with serious illness in othersNo (n=224, 94%) % 64 33 3 78 14 8 56 29 15Yes (n=14, 6%) % 57 43 0 100 0 0 50 43 7

Experience with serious illness in yourselfNo (n=40, 15%) % 50 47 3 70 25 5 60 30 10Yes (n=219, 85%) % 65 32 3 79 11 10 53 31 16

903

Determinants of the EuroQol visual analogue scale

A patient’s background was significantly related to theEQ VAS regarding age, main activity and education. EQ VAS decreased with patients’ ages (r=–0.21,p=0.002); patients with less education reported a lowerEQ VAS (median –60 versus median –70 for patientswith more education) and, in main activity, unemployedpatients reported higher EQ VAS (median –80). Also pa-tients with chronic disabling diseases had significantlylower EQ VASs (median –50) when compared with pa-tients exhibiting chronic non-disabling diseases (median–60) and healthy patients (median –80).

Regarding ICU variables, only APACHE II was sig-nificantly correlated with EQ VAS (r=–0.21, p=0.002).EQ VAS decreased significantly with the number ofproblems in the five dimensions. The lower median value of EQ VAS (median –30) was found in patientswith extreme problems in the self-care dimension (Table3).

Determinants of EuroQol Index

EuroQol Index was significantly associated with somevariables of background data – older, less educated,smokers, retired or housework patients and patients withchronic disabling disease exhibit lower EQ Indexes (median –68) when compared with patients exhibitingchronic non-disabling disease (median –76) and healthypatients (median –91). APACHE II was the only ICUvariable correlated with EQ Index (r=–0.13, p=0.029).

Regression results

The multiple logistic regression results showed that age,gender, main activity, experience with serious illness inthemselves and ICU LOS were all significantly associat-

ed with mobility dimension: older patients, female, re-tired, housework, those that did not return to work, withno experience of serious illness in themselves and withlonger ICU stay were at higher risk of having problemsin mobility.

The significant variables associated with the self-caredimension in the logistic model were: age, minimum education, experience with serious illness in the familyand ICU LOS. Patients who were older, less educated,with no experience of serious illness in the family andwith longer ICU stay showed an increased risk of prob-lems in self-care. For the usual activities dimension onlyage and main activity remained significantly associatedafter adjustment through the logistic model. Older pa-tients and those retired, doing housework or seekingwork were at higher risk of reporting problems in theusual activities dimension. Diagnosis was the only vari-able that remained associated with the pain/discomfortdimension. Compared to medical diagnosis, surgical(scheduled and non-scheduled) and trauma patients wereat higher risk of reporting pain or discomfort problems.For the anxiety/depression dimension only those whohad experience with serious illness in themselves had asignificantly higher risk of reporting problems in this dimension, after adjustment for the other variables.

In the multiple linear regression for EQ VAS, the onlysignificant variables were previous health status andminimum education. Patients with lower education andprevious chronic disease reported a lower VAS. For theEQ Index, age and previous health status were the onlyvariables significantly associated. Older patients and patients with previous chronic disease had lower scores.

The results of logistic regression analysis for each ofthe five dimensions showed that the variables related tothe ICU that had a significant difference for patients whoreported problems in the five dimensions were no longersignificant when adjusted for the background data, ex-cept in the pain/discomfort dimensions, where the diag-nosis at admission remained significantly related to the

Table 3 (continued)

Problems in mobility Problems in self care Problems in usual activities

None Moderate Extreme None Moderate Extreme None Moderate Extreme63% 34% 3% 78% 13% 9% 54% 30% 16%

Perceived current health stateHealth state today compared with 12 months ago*Better (n=144, 54%) % 70 29 1 85 11 4 58 31 11The same (n=46, 17%) % 67 30 3 76 15 9 67 24 9Worse (n=76, 29%) % 49 43 8 66 14 20 39 33 28EQ Index (n=268) Median 91 59 9 85 59 32 91 63 32EQ VAS in a 100% scale Median 70 50 50 70 50 30 75 50 50(n=219)

* This question has been modified from the original EQ-5DSignificant differences are in boldface

904

Table 4 Reported problems in pain/discomfort and anxiety/depression according to ICU variables, background data and perceived cur-rent health state (n=268)

Problems in pain/discomfort Problems in anxiety/depression

None Moderate Extreme None Moderate Extreme55% 41% 4% 46% 41% 13%

ICU variablesICU stay (days, n=267) Median 2 2 3 2 2 2

DiagnosisScheduled surgery (n=129, 48%) % 50 46 4 39 50 11Non-scheduled surgery (n=37, 14%) % 43 49 8 62 30 8Medical (n=93, 35%) % 68 29 3 51 34 15Multiple trauma (n=9, 3%) % 22 78 0 33 33 34APACHE II at admission (n=267) Median 12 13 16 13 12 14

Background dataAge in years (n=268) Median 55 60 63 60 57 56

GenderMale (n=153, 57%) % 57 38 5 46 42 12Female (n=115, 43%) % 51 45 4 47 40 13

Minimum educationNo (n=127, 48%) % 46 50 4 46 43 11Yes (n=136, 52%) % 62 34 4 47 40 13

Main activityEmployed (n=58, 22%) % 59 38 3 40 45 15Retired (n=142, 54%) % 49 46 5 48 40 12Housework (n=18, 7%) % 61 39 0 44 44 12Student (n=5, 2%) % 100 0 0 60 40 0Seeking work (n=11, 4%) % 64 36 0 64 27 9Other (n=29, 11%) % 59 38 3 45 45 10

Smoking habitsSmoker (n=35, 13%) % 63 34 3 40 46 14Ex-smoker (n=102, 39%) % 57 38 5 55 38 7Never smoked (n=125, 48%) % 50 47 3 42 43 15

Previous health statusHealthy (n=77, 28%) % 64 32 4 54 36 9Chronic non-disabling disease (n=139, 51%) % 51 46 4 45 42 12Chronic disabling disease (n=58, 21%) % 46 46 9 21 26 10

Experience with serious illness in the familyNo (n=189, 80%) % 55 41 4 47 41 12Yes (n=48, 20%) % 50 48 2 42 52 6

Experience with serious illness in othersNo (n=224, 94%) % 55 41 4 46 42 12Yes (n=14, 6%) % 50 50 0 36 57 7

Experience with serious illness in yourselfNo (n=40, 15%) % 53 47 0 63 30 7Yes (n=219, 85%) % 54 41 5 44 43 13

Perceived current health stateHealth state today compared with 12 months ago*Better (n=144, 54%) % 56 42 2 47 45 8The same (n=46, 17%) % 63 33 4 63 30 7Worse (n=76, 29%) % 47 45 8 33 41 26EQ Index (n=268) Median 91 62 14 98 76 47EQ VAS in a 100% scale (n=219) Median 70 50 50 75 60 40

* This question has been modified from the original EQ-5D. Significant differences are boldface

905

report of problems. In contrast, LOS became significantin the mobility and self-care dimensions after adjustmentfor background data.

None of the ICU variables were found to be related tothe EQ VAS and EQ Index after adjustment with a multi-ple linear regression. Age was significant in all regres-sions except for pain/discomfort, anxiety/depression andEQ VAS.

Discussion

Main findings

Three main findings may be identified in this study.First, 54% of patients reported that they felt better at thetime of the interview than a year before (i.e., 6 monthsbefore ICU admission), the median EQ Index was great-er than 75 for the majority of patients and 44% of allparticipants showed either no problems or only moderateproblems with pain or anxiety. This shows a relativelyhigh level of HR-QOL among the majority of those whosurvived 6 months after ICU discharge. These findingsagree with other reports using different tools [6, 10, 22]and with the study by Sznajder et al. using the EQ-5D,although EQ Index was lower in their sample [18]. Inten-sive care treatment can, therefore, certainly be consid-ered worthwhile.

Secondly, moderate to extreme problems in usual ac-tivities were reported by 46% of the responders, but only22% reported the same level of problems in self-care;another 45% reported moderate to extreme problemswith pain/discomfort; furthermore, anxiety was the onlydimension causing moderate to extreme problems inmore than 50% of the patients; in addition, it was the only dimension described as being extreme while all other dimensions were reported as causing no problems.These are particularly interesting findings as they aresimilar to those of Sznajder et al. [18] using the EQ-5D,where moderate pain and anxiety were the most fre-quently mentioned problems, and three other studies (using different tools), where the report of anxiety and ofemotional problems was the most common one [10, 19,23]. EQ-5D may be used to understand better patientproblems and needs in specific dimensions, which canguide health professionals to an improvement in patientmanagement after intensive care [19, 23].

Finally, multivariate analysis showed that ICU vari-ables – when adjusted for background variables such asgender, age, main activity, education, smoking habits,previous health status and experience with serious illness –were, in general, not associated with the HR-QOL mea-sures studied (i.e., EQ-5D, EQ VAS or EQ Index). Twoexceptions were found: a longer ICU LOS was associat-ed with a higher risk of reporting mobility and self-careproblems: a finding similar to that of Niskanen et al.

[22]; diagnosis was also significantly associated with thepain/discomfort dimension: a finding similar to previousreports, showing that diagnosis influenced subsequentHR-QOL [6, 10, 22]. In particular, age and previoushealth status were the only variables significantly associ-ated with EQ Index. An impairment of HR-QOL withage has been previously reported [4, 10, 22, 24, 25, 26],whereas other studies showed no influence of age [6, 27].

Capuzzo et al. [9], using an instrument they them-selves developed, showed that HR-QOL was influencedmore by the pre-ICU admission condition than by theICU course or treatments, calling attention to the im-portance of previous health status when performing HR-QOL evaluations. Likewise, Niskanen et al. [22], us-ing the Nottingham Health Profile, also underlined thatimpairment in QOL after intensive care may, at least par-tially, be attributable to the chronic disease present be-fore critical illness; Vazquez Mata et al., using their owntool [24] and Wehler et al. [26], using EQ-5D, also found the same influence of previous health status onHR-QOL. Unfortunately, neither age nor previous healthstatus are subject to intervention during an ICU stay inorder to improve HR-QOL but, together with other back-ground variables, they should always be taken into account when assessing HR-QOL after intensive care.This may be of special importance when comparingICUs with different patient case-mixes.

Methods and limitations of this study

In the present study, QOL was evaluated at 6 months af-ter ICU discharge. This decision took into account previ-ous studies suggesting that, in most patients, the healthproblem which caused admission to the ICU has stabili-sed after 6 months and that mortality beyond this pointin time may be caused by other factors, namely, chronicunderlying conditions or unrelated health problems com-monly encountered in the elderly population [1, 3, 6].EQ-5D was the instrument of choice as it is a simple andshort questionnaire easily understood and answered bythe patients; furthermore, it is a generic HR-QOL instru-ment that, apart from permitting the estimation of anoverall QOL index [21], specifically measures a range ofphysical and non-physical dimensions [13, 14, 15, 16].In addition, its usefulness and construct validity havebeen tested in patient groups using different EQ-5D lan-guages [13, 15, 20, 28].

With the transposition of instruments in English toother languages, cross-cultural differences must be takeninto account; this questionnaire appeared to be the mostappropriate choice as it has been used successfullyamong Spanish and Catalan populations [15]. The Portu-guese version of the EQ-5D was officially translated bythe EuroQol group in 1998 [20]. It has been used in pre-

906

vious studies on critically ill patients; these demonstratedthat it could be reliably used to determine the state ofhealth of patients prior to ICU admission [29]. On theother hand, EQ-5D is a generic measure and may not de-tect the particularities of critical illness, which made us aware of the need for complement HR-QOL studieswith a questionnaire specifically designed for critical pa-tients, such as the one developed by Rivera Fernandez et al. [7].

Although statistically significant differences werefound between participants and non-participants regard-ing age and severity of disease, these differences hardlyreached clinical significance and a selection bias istherefore negligible.

The present study has other limitations. Prior to ad-mission, evaluation of HR-QOL with EQ-5D was notperformed. We found that the psychosocial componentsof HR-QOL are difficult to survey at admission, as others have also found [3, 22] and, when collected dur-ing and after hospital stay, a patient’s report on pre-admission health status may present lack of consistency[30]. Recently K.L. Grady suggested that researchers becautious [3], emphasising that recall of an earlier timecan be influenced by the current situation. Yet, evalua-tion of previous health status was made, as explainedelsewhere in this paper, and a significant associationwith EQ VAS and EQ Index was found.

In summary, three main conclusions may be drawnfrom this study. Firstly, the majority of those who sur-vived 6 months after ICU stay showed a positive-percep-tion of their own well being, which shows the benefit ofintensive care treatment. Secondly, the EQ-5D question-naire was able to produce relevant information on thesepatients, mainly through the five dimensions. Thirdly,background variables, particularly age and previoushealth status, should always be taken into account when assessing HR-QOL after intensive care. Therefore,HR-QOL assessments in the ICU setting should becomemore frequent as, potentially, they can teach us moreabout the long-term outcome of ICU survivors and helpin the decision-making process at both the individual andorganisational levels [2, 3, 21].

It is our belief that critical care bears the potential forsaving the lives of critically ill patients who would other-wise die. We also believe that QOL studies trying to elu-cidate the main problems patients face after dischargemay help in the design of special programmes targetingtheir needs. Further studies are needed to improve as-sessment of HR-QOL, allowing comparisons amongICUs and increasing our skills and knowledge on pa-tients’ problems after discharge.

Acknowledgements We thank Alexandra Vieira for her invalu-able help in data management and analysis.

References

1. Konopad E, Noseworthy TW, JonhstonR, Shustack A, Grace M (1995) Quali-ty of life measures before and one yearafter admission to an intensive careunit. Crit Care Med 23:1653–1659

2. Heyland DK, Guyatt G, Cook DJ,Meade M, Junipet E, Cronin L, GafniA (1998) Frequency and methodologicrigor of quality-of-life assessments inthe critical care literature. Crit CareMed 26:591–598

3. Grady KL (2001) Beyond morbidityand mortality: quality of life outcomesin critical care patients. Crit Care Med29:1844–1845

4. Tian ZM, Reis Miranda D (1995) Qual-ity of life after intensive care with thesickness impact profile. Intensive CareMed 21:422–428

5. Leplège A, Hunt S (1997) The problemof quality of life in medicine. JAMA278:47–50

6. Hurel D, Loirat P, Saulnier F, NicolasF, Brivet F (1997) Quality of life6 months after intensive care: results of a prospective multicenter study using a generic health status scale anda satisfaction scale. Intensive Care Med23:331–337

7. Rivera Fernandez R, Sanchez Cruz JJ,Vasquez Mata G (1996) Validation of aquality of life questionnaire for critical-ly ill patients. Intensive Care Med22:1034–1042

8. Bergner M, Bobbitt RA, Carter WB,Gilson BS (1981) The Sickness ImpactProfile: development and final revisionof a health status measure. Med Care8:787–805

9. Capuzzo M, Bianconi M, Contu P,Pavoni V, Gritti (1996) Survival andquality of life after intensive care. Intensive Care Med 22:947–953

10. Pettila V, Kaarlola A, Makelainen(2000) Health-related quality of life ofmultiple organ dysfunction patientsone year after intensive care. IntensiveCare Med 26:1473–1479

11. Capuzzo M, Grasselli C, Carrer S,Gritti G, Alvisi R (2000) Validation of two quality of life questionnairessuitable for intensive care patients. Intensive Care Med 26:1296–1303

12. Suter P, Armaganidis A, Beaufils F,Bonfill X, Burchardi H, Cook D, Fagot-Largeault A, Thijs L, Vesconi S,Williams A (1994) Predicting outcomein ICU patients. Consensus Conferencein Intensive Care Medicine. IntensiveCare Med 20:390–397

13. The EuroQol Group (1990) EuroQol –a new facility for the measurement ofhealth-related quality of life. HealthPolicy 16:199–208

14. Brooks R, with the EuroQol Group(1996) EuroQol: the current state ofplay. Health Policy 37:53–72

15. Badia X, Schiaffino A, Alonso J, Herd-man M (1998) Using the EuroQol 5-Din the Catalan general population: fea-sibility and construct validity. QualLife Res 7:311–322

16. Kind P, Dolan P, Gudex C, Williams A(1998) Variations in population healthstatus: results from a United Kingdomnational questionnaire survey. BMJ 316:736–741

907

17. Kuilman M, Bleeker JK, HartmanJAM, Simoons ML (1999) Long-termsurvival after out-of-hospital cardiacarrest: an 8year follow-up. Resuscita-tion 41:25–31

18. Sznajder M, Aegerter P, Launois R,Merliere Y, Guidet B, CubRea (2001)A cost-effectiveness analysis of staysin intensive care units. Intensive CareMed 27:146–153

19. Brooks R, Kerridge R, Hillman K,Bauman A, Daffurn K (1997) Qualityof life outcomes after intensive care.Intensive Care Med 23:581–586

20. EuroQol Group Newsletter. January2000

21. Dolan P (1997) Modeling valuationsfor EuroQol health states. Med Care35:1095–1108

22. Niskanen M, Ruokonen E, Takala J,Rissanen P, Kari A (1999) Quality oflife after prolonged intensive care. Crit Care Med 27:1132–1139

23. Thiagarajan J, Taylor P, Hogbin E, Ridley S (1994) Quality of life aftermultiple trauma requiring intensivecare. Anaesthesia 49:211–218

24. Vasquez Mata G, Rivera Fernandez R,Perez Aragon A, Gonzalez Carmona A,Mondejar Fernandez E, Navarrete Navarro P (1996) Analysis of qualityof life in polytraumatized patientstwo years after discharge from an in-tensive care unit. J Trauma 41:326–332

25. Rivera-Fernandez R, Sanchez-Cruz JJ,Abizanda-Campos R, Vazquez-Mata G(2001) Quality of life before intensivecare unit admission and its influenceon resource utilization and mortalityrate. Crit Care Med 29:1701–1709

26. Wehler M, Martus P, Geise A, Bost A,Mueller A, Hahn EG, Strauss R (2001)Changes in quality of life after medicalintensive care. Intensive Care Med27:154–159

27. Chelluri L, Pinsky MR, Donahaoe MP,Grenvik A (1993) Long term outcomeof critically ill elderly patients requiringintensive care. JAMA 269 (24):3119–3123

28. Coons SJ, Rao S, Keininger DL,Hays RD (2000) A comparative reviewof generic quality-of-life instruments.Pharmacoeconomics 17:13–35

29. Badia X, Diaz-Prieto A, Rué M, PatrickDL (1996) Measuring health and healthstate preferences among critically illpatients. Intensive Care Med22:1379–1384

30. Guadagnoli E, Cleary PD (1995) Howconsistent is patient reported pre-admission health status when collec-ted during and after hospital stay? Med Care 33:106–112