Quality of life after intensive care: A systematic review of the literature

Article (PDF Available)inCritical care medicine 38(12):2386-400 · December 2010with407 Reads
DOI: 10.1097/CCM.0b013e3181f3dec5 · Source: PubMed
Abstract
To evaluate quality of life at least 12 months after discharge from the intensive care unit of adult critically ill patients, to evaluate the methodology used to assess long-term quality of life, and to give an overview of factors influencing quality of life. EMBASE-PubMed, MEDLINE (OVID), SCI/Web of Science, the Cochrane Library, Google Scholar, and personal files. Data extraction was performed independently and cross-checked by two reviewers using a predefined data extraction form. Eligible studies were published between 1999 and 2009 and assessed quality of life ≥12 months after intensive care unit discharge by means of the Medical Outcomes Study 36-Item Short Form Health Survey, the RAND 36-Item Health Survey, EuroQol-5D, and/or the Nottingham Health Profile in adult intensive care unit patients. Fifty-three articles (10 multicenters) were included, with the majority of studies performed in Europe (68%). The Medical Outcomes Study 36-Item Short Form Health Survey was used in 55%, and the EuroQol-5D, the Nottingham Health Profile, the RAND 36-Item Health Survey, or a combination was used in 21%, 9%, 8%, or 8%, respectively. A response rate of ≥80% was attained in 26 studies (49%). Critically ill patients had a lower quality of life than an age- and gender-matched population, but quality of life tended to improve over years. The worst reductions in quality of life were seen in cases of severe acute respiratory distress syndrome, prolonged mechanical ventilation, severe trauma, and severe sepsis. Study quality criteria, defined as a baseline quality of life assessment, the absence of major exclusion criteria, a description of nonresponders, and a comparison with a reference population were met in only four studies (8%). Results concerning the influence of severity of illness, comorbidity, preadmission quality of life, age, gender, or acquired complications were conflicting. Quality of life differed on diagnostic category but, overall, critically ill patients had a lower quality of life than an age- and gender-matched population. A minority of studies met the predefined methodologic quality criteria. Results concerning the influence of the patients' characteristics and illnesses on long-term quality of life were conflicting.
Review Articles
Quality of life after intensive care: A systematic review of the
literature
Sandra G. Oeyen, MD; Dominique M. Vandijck, PhD; Dominique D. Benoit, MD, PhD; Lieven Annemans, PhD;
Johan M. Decruyenaere, MD, PhD
B
ecause intensive care medicine
by definition treats the most
critically ill patients who have
an inherent high risk of mor-
tality, it seems logical that, for many years,
the primary outcome parameter has been
survival rate. Although this is without any
doubt an important issue, survival and
mortality rate also have the advantage of
being unambiguous and easy to measure.
Advances in diagnostic and therapeutic op-
tions enable more and more patients to
survive critical illness. Although studies in-
vestigating survival rates of critically ill
patients are widely performed, we also
have to question whether critical illness
has any impact on an individual’s (very)
long-term (i.e., 12 months after in-
tensive care unit [ICU] discharge)
health status and quality of life (QOL).
Therefore, next to survival or mortality
rate, QOL has to be considered of equal
importance as an outcome parameter.
Although QOL has been accepted to be
valuable regarding outcome, it is not rou-
tinely included in studies, and research on
this topic is still in its infancy. This has
many reasons. Measuring QOL with spe-
cific questionnaires is more labor-intensive
and time-consuming and will always be
more ambiguous for interpretation than
the “dead” or “alive” outcome parameters.
Optimal follow-up periods for measuring
QOL are not defined. Baseline assessment
of QOL is difficult but of great value to
examine the burden of the critical illness.
Only a few reviews of QOL after inten-
sive care have been published (1– 4). There
has been no systematic review providing
accurate and recent data on the burden of
critical illness on a patients’ long-term
QOL. Nevertheless, a better understanding
of how intensive care affects the health and
well-being of its survivors will help physi-
cians when deciding on allocating thera-
peutic efforts in the future. Consequently,
it is the purpose of this article to give a
systematic review of the literature pub-
lished in the past decade of QOL and influ-
encing factors at least 1 yr after discharge
from the ICU and of the methodology used.
Finally, we hope to give better insights into
long-term QOL and to make methodologic
recommendations for further research on
this topic.
MATERIALS AND METHODS
Data Sources, Search Strategy,
Study Selection, and Data
Extraction
A two-stage systematic review process of
existing published original research articles
was conducted. First, two authors (SGO, DMV)
independently searched EMBASE-PubMed,
MEDLINE (OVID), SCI/Web of Science, the
From Department of Intensive Care Medicine (SGO,
DDB, JMD), Ghent University Hospital, Ghent, Belgium;
Faculty of Medicine and Health Sciences (DMV, LA),
Ghent University, Ghent, Belgium.
The authors have not disclosed any conflicts of
interest.
For information regarding this article, E-mail:
sandra.oeyen@ugent.be
Copyright © 2010 by the Society of Critical Care
Medicine and Lippincott Williams & Wilkins
DOI: 10.1097/CCM.0b013e3181f3dec5
Objectives: To evaluate quality of life at least 12 months after
discharge from the intensive care unit of adult critically ill patients,
to evaluate the methodology used to assess long-term quality of life,
and to give an overview of factors influencing quality of life.
Data Sources: EMBASE-PubMed, MEDLINE (OVID), SCI/Web of
Science, the Cochrane Library, Google Scholar, and personal files.
Data Extraction: Data extraction was performed indepen-
dently and cross-checked by two reviewers using a predefined
data extraction form. Eligible studies were published between
1999 and 2009 and assessed quality of life >12 months after
intensive care unit discharge by means of the Medical Out-
comes Study 36-Item Short Form Health Survey, the RAND
36-Item Health Survey, EuroQol-5D, and/or the Nottingham
Health Profile in adult intensive care unit patients.
Data Synthesis: Fifty-three articles (10 multicenters) were in-
cluded, with the majority of studies performed in Europe (68%). The
Medical Outcomes Study 36-Item Short Form Health Survey was used
in 55%, and the EuroQol-5D, the Nottingham Health Profile, the RAND
36-Item Health Survey, or a combination was used in 21%, 9%, 8%,
or 8%, respectively. A response rate of >80% was attained in 26
studies (49%). Critically ill patients had a lower quality of life than an
age- and gender-matched population, but quality of life tended to
improve over years. The worst reductions in quality of life were seen
in cases of severe acute respiratory distress syndrome, prolonged
mechanical ventilation, severe trauma, and severe sepsis. Study
quality criteria, defined as a baseline quality of life assessment, the
absence of major exclusion criteria, a description of nonresponders,
and a comparison with a reference population were met in only four
studies (8%). Results concerning the influence of severity of illness,
comorbidity, preadmission quality of life, age, gender, or acquired
complications were conflicting.
Conclusions: Quality of life differed on diagnostic category but,
overall, critically ill patients had a lower quality of life than an age-
and gender-matched population. A minority of studies met the pre-
defined methodologic quality criteria. Results concerning the influ-
ence of the patients’ characteristics and illnesses on long-term
quality of life were conflicting. (Crit Care Med 2010; 38:2386–2400)
K
EY WORDS: intensive care unit; quality of life; long-term outcome;
critically ill patients; methodology; comorbidity
2386 Crit Care Med 2010 Vol. 38, No. 12
Cochrane Library, and Google Scholar on Jan-
uary 9, 2010, using the medical subject head-
ings or text key words “quality of life,” or
“long-term outcome” cross-referenced with
“intensive care,” “critical care,” “critically ill
patients,” “ICU patients,” “critical care pa-
tients,” “ICU stay,” or “ICU.” Limitations were
applied regarding language (English lan-
guage), time (articles published between Jan-
uary 1, 1999 and December 31, 2009), age
(older than 18 yrs), and humans. Personal files
that were known to the authors and reference
lists of relevant articles also were hand-
searched. Outcomes articles including exclu-
sively cardiac or thoracic aortic surgery pa-
tients, methodologic articles, literature
reviews, case reports, editorials, and letters
were excluded. Studies with 50 patients
were also not included. If it was unclear
whether patients were admitted to the ICU,
then articles were excluded (5–7).
In stage two, all abstracts were evaluated
independently by two authors (SGO, DMV)
for the following methodologic criteria: 1)
assessment of QOL by means of at least one
of the following instruments: the Medical
Outcomes Study 36-Item Short Form
Health Survey (SF-36), the RAND 36-Item
Health Survey (RAND-36), EuroQol-5D (EQ-
5D), and/or the Nottingham Health Profile
(NHP); and 2) a follow-up period of 12
months after discharge from the ICU. Dis-
agreements regarding eligibility were re-
solved by consensus.
Subsequently, identified articles were
downloaded and screened electronically. For
each eligible article, using a predefined cate-
gorization system, information was extracted
on the authors, journal, year of publication,
study design, inclusion period, initial study
cohort, number of eligible patients for long-
term QOL assessment, instrument(s) and
method(s) used for QOL assessment, response
rate, follow-up period. final conclusion con-
cerning QOL, and factors determining QOL.
Study quality was assessed using four im-
portant criteria, analogous to those used by
Dowdy et al (1): 1) QOL assessment before
ICU admission, 2) description of key inclu-
sion or exclusion criteria, 3) description of
nonresponders and comparison with those
remaining in the study, and 4) adjustment
for confounders such as age and gender. The
aforementioned criteria were not used in
decisions regarding inclusion or exclusion
of eligible studies. Any discrepancies be-
tween both reviewers were resolved by
discussion.
QOL Measurement Instruments
SF-36, RAND-36, EQ-5D, and NHP were
considered because they are generic instru-
ments commonly used in intensive care re-
search (8); they are well validated and have
population norms in the literature (9–16).
The SF-36 questionnaire contains 36 items
measuring eight multi-item domains: physical
and social functioning, role limitations caused
by physical or emotional problems, mental
health, vitality, bodily pain, and general per-
ception of health (9–13).
Arising from SF-36, the RAND-36 ques-
tionnaire was developed. Although the count
system in the latter differs somewhat com-
pared to SF-36, questions and final results are
almost identical (14).
The EQ-5D is a short questionnaire con-
sisting of three parts (15, 17–19). A descriptive
system measures health in five domains: mo-
bility, self-care, usual activities, pain/discom-
fort, and anxiety/depression. Each domain has
three levels: no problems, moderate problems,
or severe problems. Therefore, patients can be
classified into 1 of 243 (3
5
) possible health
states. Each of these can be converted into one
single summary index that can be used in
health– economy studies. On a visual analog
scale, patients can rate their overall health
between 0 and 100. Although the EQ-5D is a
well-known and well-validated instrument to
measure QOL in general populations, it has
been less well validated in the critically ill
population (17–19), and it may provide less
information and may be less discriminative
than the SF-36 (20).
The NHP consist of a two-part question-
naire (16). The first one comprises 38 state-
ments related to six domains: physical mobil-
ity, pain, sleep, energy, emotional reactions,
and social isolation. The second part lists
seven activities of daily life: occupation,
housework, social activity, home life, sex
life, hobbies, and holidays. The NHP has
already been used to evaluate QOL in the
critically ill population, especially in cardiac
surgery patients (21). Nevertheless, internal
consistency and sensitivity to change were
better for the SF-36 and RAND-36 than for
the NHP (22–24).
RESULTS
A total of 53 articles were finally in-
cluded in the review. The articles were
grouped according to diagnostic cate-
gory. Studies concerning critically ill pa-
tients in general were separated based on
follow-up period. Eleven articles con-
cerning acute respiratory distress syn-
drome (ARDS) (25–35), three articles
about prolonged mechanical ventilation
(36 –38), eight trauma studies (20, 39
45), six articles concerning cardiac arrest
(46 –51), six studies about elderly patients
(52–57), two pancreatitis studies (58, 59),
three sepsis studies (60 62), and four
studies with various topics (63– 66) were
included. There were four studies con-
cerning outcome and QOL in general
critically ill patients 1 yr after intensive
care (19, 67– 69) and six with longer fol-
low-up periods (70–75). Table 1 gives an
overview of the characteristics of these
studies. All the studies were performed in
large hospitals. Ten were multicenter
studies (32–34, 40, 45, 48, 51, 57, 61, 66).
Thirty-six were conducted in Europe (19,
20, 26–28, 35, 36, 41, 42, 44 46, 48, 49,
51–56, 59, 61–75), 13 were conducted in
the United States (25, 29 –31, 37– 40, 43,
47, 50, 57, 58), and four were conducted
in Canada (32–34, 60). Within Europe,
the majority of studies were performed in
Scandinavian countries (42, 44, 45, 51,
54, 59, 61, 64 67, 72–75), Germany (26
28, 35, 49, 71), and the Netherlands (20,
48, 55, 63).
Inclusion periods varied between 1
yr (61, 68, 70, 71) and 10 yrs (26–28,
35, 47, 50). All but three studies concern-
ing critically ill patients in general had an
inclusion period of 1 yr (19, 67, 69, 72–
75). In three articles, the inclusion period
was not further specified (32, 33, 40) (Ta-
ble 1).
Table 2 gives an overview of QOL as-
sessment after ICU discharge. The most
frequently used QOL instrument was the
SF-36 (55%), followed by the EQ-5D
(21%), the NHP (9%), and the RAND-36
(8%). Four studies (8%) used a combina-
tion of QOL instruments: the SF-36 with
the EQ-5D (19, 53), the RAND-36 with
the EQ-5D (54), or the NHP with the
Patrick’s Perceived Quality of Life score,
another QOL questionnaire (52).
Follow-up periods for QOL assessment
varied between the included studies.
Some had a strict follow-up period of 1 yr
(29, 30, 37, 40, 41, 56, 67, 68), whereas
others had large ranges within their fol-
low-up time (26–28, 35, 43– 47, 50, 52,
55, 58 60), and in one study, although at
least 12 months, the follow-up period for
QOL evaluation was not clearly defined
(39). Twelve studies evaluated QOL at
strict time points during the follow-up
period (19, 31–34, 38, 51, 57, 66, 72, 74,
75). Median follow-up periods of 5 yrs
were found in eight studies (26–28, 42,
48, 49, 71, 73). The Scandinavian area
seemed to be particularly interested in
research on QOL a long period after ICU
discharge (42, 54, 59, 64, 65, 72–75).
QOL was assessed at follow-up by a
mailed survey in 22 studies (42%) (20, 35,
36, 39, 45, 48, 49, 53, 54, 57, 59, 61, 67,
68, 63– 66, 72–75), by telephone in 14
(26%) (19, 25, 32, 33, 40, 41, 44, 52, 55,
2387Crit Care Med 2010 Vol. 38, No. 12
Table 1. Study characteristics
Reference Country Study Design Inclusion Period Patient Cohort
Eligible Patients for
Long-Term QOL
Assessment, N (%)
a
ARDS
Davidson et al,
1999 (25)
United States Prospective, matched,
controlled
January 1994–July 1996 102 sepsis or trauma-
induced ARDS patients
80 (78%)
Schelling et al,
2000 (26)
Germany Follow-up cohort January 1985–January
1995
192 consecutive ARDS
patients
119 (62%)
Rothenhäusler et
al, 2001 (27)
Germany Exploratory January 1985–January
1995
192 consecutive ARDS
patients
119 (62%)
Kapfhammer et al,
2004 (28)
Germany Follow-up cohort January 1985–January
1995
80 long-term ARDS
survivors
80 (100%)
Hopkins et al,
1999 (29)
United States Prospective February 1994–July 1998 106 enrolled out of 274
ARDS patients
67 (63%)
Orme et al, 2003
(30)
United States Prospective, cohort of a RCT February 1994–December
1999
120 ARDS patients enrolled
in high tidal volume vs.
low tidal volume study
74 (62%)
Hopkins et al,
2005 (31)
United States Longitudinal prospective,
cohort of a RCT
February 1994–December
1999
120 ARDS patients enrolled
in high tidal volume vs.
low tidal volume study
74 (62%)
Heyland et al,
2005 (32)
Canada Prospective, observational,
multicenter
NA 221 ARDS patients enrolled
in a phase III
multicenter RCT
103 (47%)
Parker et al, 2006
(33)
Canada Prospective, observational,
multicenter
NA 221 ARDS patients enrolled
in a phase III
multicenter RCT
103 (47%)
Herridge et al,
2003 (34)
Canada Longitudinal, multicenter May 1998–May 2001 195 adult ARDS patients 109 (56%)
Deja et al, 2006
(35)
Germany Prospective controlled 1991–2000 263 patients with severe
ARDS
129 (49%)
Prolonged
mechanical
ventilation
Combes et al,
2003 (36)
France Prospective cohort January 1995–June 1999 347 consecutive patients
receiving mechanical
ventilation for 14 d
99 (29%)
Chelluri et al,
2004 (37)
United States Prospective, observational June 1997–July 1999 817 patients receiving
mechanical ventilation
for 48 hrs
359 (44%)
Cox et al, 2009
(38)
United States Prospective, observational April 2006–April 2007 126 consecutive patients
receiving mechanical
ventilation 21dor
with a tracheotomy after
4 d of mechanical
ventilation
90 (71%)
Trauma
Miller et al, 2000
(39)
United States Retrospective January 1991–December
1997
115 severely injured
patients spending 3
wks in the ICU
90 (78%)
Mackenzie et al,
2002 (40)
United States Retrospective (hospital stay),
prospective (QOL)
multicenter
NA Sample of 1587 patients
registered in the
Pennsylvania Trauma
Outcomes Study
1587 (100%)
Dimopoulou et al,
2004 (41)
Greece Prospective cohort 1999–2000 191 consecutive multiple
trauma patients
requiring mechanical
ventilation
117 (61%)
Sluys et al, 2005
(42)
Sweden Retrospective (patient cohort),
prospective (QOL)
1996–1997 309 trauma patients 246 (80%)
Vles et al, 2005
(20)
The Netherlands Prospective January 1996–January
1999
295 severely injured
patients (injury severity
score 16)
196 (66%)
Jackson et al,
2007 (43)
United States Retrospective 2003 97 trauma ICU survivors
without intracranial
hemorrhage
58 (60%)
2388 Crit Care Med 2010 Vol. 38, No. 12
Table 1. Continued
Reference Country Study Design Inclusion Period Patient Cohort
Eligible Patients for
Long-Term QOL
Assessment, N (%)
a
Ulvik et al, 2008
(44)
Norway Follow-up cohort 1998–2003 325 trauma patients 228 (70%)
Ringdal et al, 2009
(45)
Sweden Exploratory multicenter September 2001–August
2002
344 adult trauma survivors 344 (100%)
Cardiac arrest
Saner et al, 2002
(46)
Switzerland Retrospective case-control 1991–1996 439 OOHCA patients (of
1307 resuscitations)
50 (11%)
Bunch et al, 2003
(47)
United States Prospective (cardiac arrest,
survival, QOL)
November 1990–January
2001
145 OOHCA patients (of
200 resuscitations)
60 (41%)
Kuilman et al,
1999 (48)
The Netherlands Retrospective, multicenter 1988–1994 441 OOHCA patients (of
898 resuscitations)
132 (30%)
Graf et al, 2008
(49)
Germany Prospective cohort January 1999–December
2000
354 consecutive patients
with cardiac arrest
110 (31%)
Mahapatra et al,
2005 (50)
United States Prospective (cardiac arrest,
survival, QOL)
November 1990–January
2001
142 OOHCA patients (of
200 resuscitations)
60 (42%)
Lundgren-Nilsson
et al, 2005 (51)
Sweden Longitudinal multicenter 1996–1999 51 cardiac arrest survivors 51 (100%)
Elderly
Montuclard et al,
2000 (52)
France Prospective cohort January 1993–August
1998
75 consecutive patients 70
yrs with ICU LOS 30 d
30 (40%)
Merlani et al, 2007
(53)
Switzerland Retrospective January 1999– December
2000
141 consecutive patients
70 yrs with abdominal
pathologies
52 (37%)
Kaarlola et al,
2006 (54)
Finland Cross-sectional survey 1995–2000 882 elderly (65 yrs) 1,827
controls (65 yrs)
354 elderly (40%)
1,074 controls
(59%)
de Rooij et al,
2008 (55)
The Netherlands Retrospective cohort January 1997–December
2002
578 consecutive patients
80 yrs
231 (40%)
Garrouste-Orgeas
et al, 2006 (56)
France Prospective, observational March 2002–November
2003
180 patients 80 yrs
triaged for ICU
admission; 48 ICU
admissions
28 (16%; only 9
ICU patients)
Kleinpell, 2003
(57)
United States Longitudinal, prospective,
multicenter
Period of 14 mos 883 patients 45 yrs, ICU
LOS 24 hrs
284 (32%)
Pancreatitis
Soran et al, 2000
(58)
United States Retrospective January 1992–December
1996
52 ICU patients with acute
pancreatitis
39 (75%)
Halonen et al,
2003 (59)
Finland Retrospective January 1989–December
1997
283 consecutive patients
with severe acute
pancreatitis
174 (61%)
Sepsis
Heyland et al,
2000 (60)
Canada Cross-sectional survey 1993–1998 78 sepsis patients 30 (38%)
Karlsson et al,
2009 (61)
Finland Prospective, observational,
multicenter
November 2004–February
2005
470 severe sepsis patients 278 (59%)
Korosˇecetal,
2006 (62)
Slovenia Observational 2003 164 patients (66 sepsis, 98
trauma)
78 patients (48%;
21 sepsis, 57
trauma)
Mixed ICU patients 1
yr after ICU
Pettilä et al, 2000
(67)
Finland Prospective, observational 1995 591 consecutive ICU
patients
354 (60%)
Badia et al, 2001
(68)
Spain Prospective cohort October 1994–June 1995 523 consecutive patients
(84 trauma, 239
scheduled surgery, 57
unscheduled surgery,
143 medical)
375 (69 trauma,
198 SS, 23
unscheduled
surgery, 85
medical; 72%)
Cuthbertson et al,
2005 (19)
United Kingdom Prospective cohort May 2001–April 2002 423 consecutive ICU
patients
300 (71%)
Stricker et al,
2005 (69)
Switzerland Prospective, observational,
case-control
September 1998–August
1999
173 patients with ICU LOS
7 d vs. 1,506 patients
with ICU LOS 7d
116 with an ICU
LOS 7 days
(67%)
2389Crit Care Med 2010 Vol. 38, No. 12
56, 58, 60, 62, 69), by face-to-face inter-
views in 12 (23%) (26 –31, 34, 43, 46, 47,
50, 51), and by a combination of these
methods in five studies (9%) (37, 38, 42,
70, 71). To gain the highest response rate
possible, many studies sent reminder
mails or phoned in the absence of any
response by mail (20, 35, 39, 42, 45, 49,
53, 54, 57, 59, 65, 67, 68, 72–74). Never-
theless, there were three studies (6%)
with a response rate of 50% (26, 27,
39), 24 studies (45%) with a response rate
between 50% and 79% (19, 28, 32, 33, 35,
37, 38, 40, 41, 45, 49, 51, 53, 57, 58, 61,
62, 64 66, 69, 73–75), and 26 studies
(49%) had a response rate of at least 80%
of the eligible patient population for
long-term outcome and QOL assessment
(20, 25, 29, 30, 31, 34, 36, 42– 44, 46 48,
50, 52, 54 –56, 59, 60, 63, 67, 68, 70 –72).
Four studies (8%) met all of the four
predefined study quality criteria: assess-
ment of QOL at baseline, no major exclu-
sion criteria within the study population,
description of the nonresponder group
vs. the responder group, and comparison
with an age- and gender-matched normal
population (19, 37, 53, 61) (Table 3). By
omitting assessment of baseline QOL as
quality criterion, the number of studies
fulfilling the other three quality criteria
increased to 21 (40%) (26 –28, 32, 35, 36,
39, 40, 42, 45, 47, 49, 57, 59, 62, 6466,
69, 72, 74). Only nine studies (17%) mea-
sured QOL before ICU (19, 37, 38, 44, 52,
53, 61, 68, 70), and in 27 articles (51%)
(19, 26 –28, 32, 35, 36, 37, 39, 40, 42, 44,
45, 47, 49, 53, 57, 59, 61, 62, 64 66, 69,
70, 72, 74), a description was given of the
nonresponder group and compared with
patients who responded to the QOL sur-
vey. All studies defined clearly which pa-
tients were included or excluded.
Table 4 summarizes the major finding
concerning long-term QOL per article.
Long-term QOL varied between diagnos-
tic categories. ARDS patients, patients af-
ter prolonged mechanical ventilation, se-
vere trauma patients, and sepsis survivors
showed significant impairments in long-
term QOL (25– 45, 60 62). Although
physical aspects improved slowly over the
years, mental and emotional conditions
were stagnant or declined even further.
However, survivors of cardiac arrest, se-
vere pancreatitis, esophagectomy, and
acute kidney injury had a good QOL,
which was comparable with or even bet-
ter than that of an age- and gender-
matched population (46 –51, 58, 59, 63,
64). In the elderly, QOL was somewhat
decreased, especially in the physical do-
mains, but elderly patients generally
adapted well to these limitations and per-
ceived their QOL as good (27–32). One
year after ICU, critically ill patients in
general had a lower QOL, especially in
physical domains, than an age- and gen-
der-matched population (19, 67– 69).
However, a slow improvement to premor-
bid QOL levels could be found. The in-
crease in QOL could be further seen sev-
eral years after ICU, when QOL was quite
comparable with that of the normal pop-
ulation (70 –75).
Factors associated with reductions in
QOL at least 1 yr after ICU discharge are
also displayed in Table 4. In ARDS or
patients with prolonged mechanical ven-
tilation, ARDS and its sequelae influ-
enced QOL by impairments in pulmonary
Table 1. Continued
Reference Country Study Design Inclusion Period Patient Cohort
Eligible Patients for
Long-Term QOL
Assessment, N (%)
a
Long-term QOL
García Lizana et
al, 2003 (70)
Belgium Prospective, observational June 25–September 10,
2000
202 consecutive admitted
patients
118 (58%)
Graf et al, 2005
(71)
Germany Prospective cohort November 1997–February
1998
303 consecutive patients
with ICU LOS 24 hrs
190 (63%)
Kaarlola et al,
2003 (72)
Finland Prospective observational 1995 591 consecutive patients 169 (29%)
Flaatten and
Kvåle, 2001 (73)
Norway Retrospective (ICU stay),
prospective (survival,
QOL)
1987 219 ICU patients 88 (40%)
Kvåle and
Flaatten, 2003
(74)
Norway Prospective cohort July 1999–August 2000 226 patients with ICU LOS
24 hrs discharged alive
226 (100%)
Kvåle and
Flaatten, 2002
(75)
Norway Prospective and
retrospective cohort
1987 compared with 1997 219 patients with ICU LOS
24 hrs in 1987, 338 in
1997
88 (40%; 1987) 106
(31%; 1997)
Various diseases
De Boer et al,
2000 (63)
The Netherlands Prospective, observational January 1993–May 1996 100 consecutive patients
who underwent a trans-
hiatal esophagectomy
35 (35%)
Ahlström et al,
2005 (64)
Finland Cross-sectional cohort 1998–2002 703 patients receiving renal
replacement therapy for
acute kidney injury
229 (33%)
Ylipalosaari et al,
2007 (65)
Finland Prospective May 2002–June 2003 272 hospital survivors with
ICU-LOS 48 hrs
187 (69%)
Orwelius et al,
2008 (66)
Sweden Prospective, multicenter
cohort
August 2000–November
2003
1,625 consecutive adult
patients with ICU LOS
24 hrs
723 (44%)
QOL, quality of life; ARDS, acute respiratory distress syndrome; RCT, randomized controlled trial; NA, not available; ICU, intensive care unit; ISS, injury
severity score; ICH, intracranial hemorrhage; OOHCA, out-of-hospital cardiac arrest; LOS, length of stay.
a
Percentage of initial patient cohort.
2390 Crit Care Med 2010 Vol. 38, No. 12
Table 2. Assessment of quality of life after ICU
Reference
QOL Assessment
Instrument Method of QOL Assessment
Response Rate, % (N of QOL
Responders) Follow-Up Period
Acute respiratory distress
syndrome
Davidson et al, 1999 (25) SF-36 Telephone 96% (77) Median 23 mos
Schelling et al, 2000 (26) SF-36 Face-to-face 42% (50) Median 5.5 yrs (range 1–10
yrs)
Rothenhäusler et al, 2001 (27) SF-36 Face-to-face 39% (46) Median 6 yrs (range 1–12 yrs)
Kapfhammer et al, 2004 (28) SF-36 Face-to-face 58% (46) Median 8 yrs (range 3–13 yrs)
Hopkins et al, 1999 (29) SF-36 Face-to-face 82% (55) 1 yr
Orme et al, 2003 (30) SF-36 Face-to-face 89% (66) 1 yr
Hopkins et al, 2005 (31) SF-36 Face-to-face 84% (62) 1 and 2 yrs
Heyland et al, 2005 (32) SF-36 Telephone 71% (73) 3, 6, 12 mos
Parker et al, 2006 (33) SF-36 Telephone 71% (73) 3, 6, 12 mos
Herridge et al, 2003 (34) SF-36 Face-to-face 80% (83) 3 mos 82% (82) 6
mos 86 % (83) at 12 mos
3, 6, 12 mos
Deja et al, 2006 (35) SF-36 Mail, telephone if no answer 50% (65) 57 32 mos
Prolonged mechanical ventilation
Combes et al, 2003 (36) NHP Mail 88% (87) Average 3 yrs
Chelluri et al, 2004 (37) SF-36 Telephone or face-to-face 64% (231) full interview 18%
(65) mini-interview
1yr
Cox et al, 2009 (38) EQ-5D Telephone or face-to-face 78% (70) 3, 12 mos
Trauma
Miller et al, 2000 (39) RAND-36 Mail, telephone if no answer 39% (35) Unclear, mean of several
years
Mackenzie et al, 2002 (40) SF-36 telephone 78% (1230) 1 yr (range, 10–14 mos)
Dimopoulou et al, 2004 (41) NHP Telephone 74% (87) 1 yr
Sluys et al, 2005 (42) SF-36 Mail or telephone, reminder
mail
83% (205) 5 yrs
Vles et al, 2005 (20) EQ-5D Mail, telephone if no answer 85% (166) Mean 41 mos
Jackson et al, 2007 (43) SF-36 Face-to-face 100% (58) 12–24 mos
Ulvik et al, 2008 (44) EQ-5D Telephone 92% (210) 2–7 yrs (median 4 yrs)
Ringdal et al, 2009 (45) SF-36 Mail, one written reminder,
then telephone
69% (239) 6–18 mos
Cardiac arrest
Saner et al, 2002 (46) NHP Face-to-face 100% (50) Mean 31.7 mos (range, 5–
68 mos)
Bunch et al, 2003 (47) SF-36 Face-to-face 83% (50) 4.8 3.0 yrs
Kuilman et al, 1999 (48) EQ-5D Mail 83% (109) Mean 6.71 yrs
Graf et al, 2008 (49) SF-36 Mail or telephone if no
answer
74% (81) 5 yrs
Mahapatra et al, 2005 (50) SF-36 Face-to-face 83% (50) 4.8 3.0 yrs
Lundgren-Nilsson et al, 2005
(51)
NHP Face-to-face 51% (26) at 1 yr 14 days, 45 days,
3mos,1yr
Elderly
Montuclard et al, 2000 (52) Patrick’s Perceived
Quality of Life
(1996) NHP
(1998)
Telephone 93% (28) (first study) 95%
(21) (second study)
557 117 days for the first
study, second 2 yrs later
Merlani et al, 2007 (53) ED-5D, SF-36 Mail, telephone if
no/incomplete answer
79% (41) 2 yrs
Kaarlola et al, 2006 (54) EQ-5D, RAND-36 Mail, reminder mail 87% (307) elderly 77% (828)
controls
Median 3 yrs for elderly
median 4 yrs for controls
de Rooij et al, 2008 (55) EQ-5D Telephone 88% (204) 1 to 6 yrs, median 3.7 yrs
Garrouste-Orgeas et al, 2006
(56)
NHP Telephone 100% (28) 1 yr
Kleinpell, 2003 (57) SF-36 Mail, reminder mail,
telephone if no answer
70% (199) 1, 3, 6, 12 mos
Pancreatitis
Soran et al, 2000 (58) SF-36 Telephone 54% (21) Median 42 mos (range, 17–
69 mos)
Halonen et al, 2003 (59) RAND-36 Mail, reminder mail, or
telephone
83% (145) Median 61 mos (range, 19–
127 mos)
Sepsis
Heyland et al, 2000 (60) SF-36 Telephone 100% (30) first interview 87%
(26) second interview
16.6 10.6 mos
Karlsson et al, 2009 (61) EQ-5D Mail 52% (252) QOL before 58%
(156) long-term QOL
Median 17 mos
2391Crit Care Med 2010 Vol. 38, No. 12
functions, cognitive disorders, weakness,
and post-traumatic stress disorders (25–
35). In trauma patients, the injury sever-
ity, the degree of brain damage, and fe-
male gender dominated long-term QOL
in a negative way (20, 41, 43, 44). How-
ever, in other studies the severity of ill-
ness played a less important role (71, 74).
In a mixed ICU patient population, diag-
nostic category determined QOL (67, 68,
70). There were conflicting results re-
garding the influence of age on long-term
QOL (19, 37, 42, 57, 59, 63, 67, 70, 74).
Two studies found that poor preadmis-
sion QOL played a role in the reduction in
QOL a long period after ICU discharge
(19, 70).
DISCUSSION
It was the purpose of this review to
give an overview of the literature of QOL
at least 1 yr after discharge from the ICU,
of the factors that determine QOL, and of
the methodology used. Because of differ-
ences in study design, patient popula-
tions, QOL instruments, follow-up times,
and response rates, it is impossible to
make one overall conclusion. However,
this review has some important findings.
First, long-term QOL depends largely
on diagnostic category. Patients with severe
ARDS, prolonged mechanical ventilation,
severe trauma, and severe sepsis appeared
to have the worst reductions in QOL, which
lasted a long time. Although physical as-
pects improved slowly over the years, men-
tal and emotional aspects were stagnant or
declined even further. Trauma patients
were usually healthy and young before ICU
admission. Their QOL often declined sub-
stantially after the trauma, both in physical
and psychosocial dimensions, and delu-
sional memories and the inability to return
to work negatively influenced their per-
ceived QOL (20, 41, 45). Survivors of car-
diac arrest, elderly, patients with severe
pancreatitis, patients after esophagectomy,
or patients with acute kidney injury had
good QOL or perceived it as even better
than before illness. Acceptance of disability
is, in general, higher among older patients,
and it is even better if they have a good
socioeconomic status (52). A high QOL de-
spite the severity of illness or persisting
symptoms may be explained by the fact that
patients who are confronted with a life-
threatening disease are faced with the ne-
cessity to acclimate to the disease, which
may lower internal standards (63). Criti-
cally ill patients in general had a lower QOL
than an age- and gender-matched popula-
tion 1 yr after ICU discharge, but a slow
improvement in QOL could be seen, and
several years after ICU, QOL was quite com-
parable with that of the normal population.
The second finding was that factors
that could be presumed to result in a
poor QOL after ICU, such as age, pro-
longed mechanical ventilation, or a
long ICU or hospital stay, are not indi-
cators per se of reductions in QOL af-
terward (25, 27, 44). Other issues, such
as cognitive impairments, sleep distur-
bances, post-traumatic stress disorder,
the rehabilitation process, employment
status, and cultural and payment differ-
ences, can influence QOL in a less tan-
gible way than, for example, physical
impairments after major trauma (26,
27, 35, 49, 52, 66).
Third, there were important method-
ologic differences between the included
studies. Four of the 53 included studies
met all four quality criteria. Only a mi-
nority of studies had a uniform follow-up
time or measured QOL before ICU admis-
sion, and response rates to QOL surveys
were generally low, which resulted in a
limited interpretation of study results.
The ideal assessment of long-term
QOL after critical care should use vali-
dated QOL instruments in large cohorts
without major exclusions, with an exten-
sive but reasonably long and uniform fol-
low-up period, and with comparison with
baseline evaluation before ICU stay (61).
Future research on long-term QOL
should focus on that. In this review, only
Table 2. Continued
Reference
QOL Assessment
Instrument Method of QOL Assessment
Response Rate, % (N of QOL
Responders) Follow-Up Period
Korosˇec et al, 2006 (62) EQ-5D Telephone 50% (39) 2 yrs
Mixed ICU patients 1 yr after ICU
Pettilä et al, 2000 (67) RAND-36 Mail, reminder mail 87% (307) 1 yr
Badia et al, 2001 (68) EQ-5D Mail, telephone or face-to-face
interview if no answer
89% (334) 1 yr
Cuthbertson et al, 2005 (19) SF-36, also EQ-5D
at 12 mos
Telephone 78% (233) 3 mos 67% (201) 6
mos 58% (173) 12 mos
3, 6, 12 mos
Stricker et al, 2005 (69) SF-36 Telephone 65% (75) 12–18 mos
Long-term QOL
García Lizana et al, 2003 (70) EQ-5D Mail or telephone 81% (96) 1, 5 yrs
Graf et al, 2005 (71) SF-36 Mail or telephone 91% (173) 5 yrs
Kaarlola et al, 2003 (72) RAND-36 Mail, reminder mail if no
response
84 % (298) 1 yr 76 % (192) 6
yrs
1yrand6yrs
Flaatten and Kvåle, 2001 (73) SF-36 Mail, reminder mail if no
response
58% (51) 12 yrs
Kvåle and Flaatten, 2003 (74) SF-36 Mail, one reminder mail 56% (126) at 6 mos 79%
(100) after 2 yrs
6 mos and 2 yrs
Kvåle and Flaatten, 2002 (75) SF-36 Mail 58 % (51) in 1987 62 % (66)
in 1997
3 yrs and 13 yrs
Various diseases
De Boer et al, 2000 (63) SF-36 Mail 100% (35) Minimum of 2 yrs
Ahlström et al, 2005 (64) EQ-5D Mail 67% (153) Median 2.4 yrs
Ylipalosaari et al, 2007 (65) EQ-5D Mail, telephone if no response 76% (142) Median 22 mos
Orwelius et al, 2008 (66) SF-36 Mail 69% (497) after 12 mos 6 and 12 mos
ICU, intensive care unit; QOL, quality of life; SF-36, Short-Form 36; NHP, Nottingham Health Profile; EQ-5D, EuroQol-5D.
2392 Crit Care Med 2010 Vol. 38, No. 12
Table 3. Study quality criteria
Reference
QOL
Before
ICU Key Inclusion or Exclusion Criteria
Description of
Nonresponders
Age-/Gender-Matched General
Population to Compare QOL
ARDS
Davidson et al, 1999 (25) No ARDS survivors with severe head injuries
were excluded
No Matched with sepsis and trauma patients
without ARDS
Schelling et al, 2000 (26) No Study population was a follow-up cohort
of 80 long-term ARDS survivors and
QOL responders in a study 3 yrs
before
Yes Age- and gender-matched control group
of normal German subjects
Rothenhäusler et al, 2001 (27) No Only long-term ARDS survivors were
included
Yes Age- and gender-matched control group
Kapfhammer et al, 2004 (28) No Only long-term ARDS survivors were
included
Yes Standard values of the Short-Form 36
from volunteers of the West German
population
Hopkins et al, 1999 (29) No 168 ARDS patients were excluded for
various reasons
No Normative population data
Orme et al, 2003 (30) No Only long-term ARDS survivors were
included
No Normative population data
Hopkins et al, 2005 (31) No Long-term ARDS survivors were included No Normative population data
Heyland et al, 2005 (32) No Long-term ARDS survivors were included Yes Age- and gender-matched population
derived from literature
Parker et al, 2006 (33) No Long-term ARDS survivors were included No Primary ARDS patients were compared
to secondary ARDS patients
Herridge et al, 2003 (34) No Only severe ARDS patients were included
Immobile patients, patients with a
history of pulmonary resection or with
a neurologic or psychiatric disease
were excluded
No Normal Canadian population
Deja et al, 2006 (35) No Only severe ARDS patients were included Yes Age- and gender-matched healthy
German controls
Prolonged mechanical ventilation
Combes et al, 2003 (36) No Only patients with prolonged mechanical
ventilation (14 d) were included
Yes Community-based age- and gender-
matched controls
Chelluri et al, 2004 (37) Yes Patients with prolonged mechanical
ventilation (48 hrs) were included
Yes Samples of the U.S. population
Cox et al, 2009 (38) Yes Patients with 21 d mechanical
ventilation or with tracheotomy after
4 d mechanical ventilation were
included
No U.K. population norms for persons aged
55–65 yrs
Trauma
Miller et al, 2000 (39) No Only severely injured patients spending
3 wks in the ICU were included
Yes General U.S. population
Mackenzie et al, 2002 (40) No Blunt trauma patients (18–59 yrs), with
a hospital stay of 72 hrs were
included. Drownings, electrocutions,
burns, and hip or femoral neck
fractures were excluded
Yes Age- and gender-matched general
population
Dimopoulou et al, 2004 (41) No Only mechanically ventilated polytrauma
patients were included
No No
Sluys et al, 2005 (42) No Blunt or penetrating trauma patients
with an ISS of 9 were included;
patients with psychiatric disorders or
cognitive impairments were excluded
Yes Swedish age- and gender-matched
reference sample
Vles et al, 2005 (20) No Only patients with ISS 16 were
included
No Swedish reference database, corrected
for age and gender
Jackson et al, 2007 (43) No Only trauma ICU survivors (ISS 25)
without intracranial hemorrhage were
included
No General U.S. population
Ulvik et al, 2008 (44) Yes Foreign trauma patients were excluded
because of difficulties with follow-up
Yes No
Ringdal et al, 2009 (45) No Nonsurvivors, attempted suicide, not
resident in Sweden, intellectual
impairment, and patients with
unknown address were excluded
Yes Age- and gender-matched reference
sample drawn from the Swedish
Short-Form 36 norm database
2393Crit Care Med 2010 Vol. 38, No. 12
Table 3. Continued
Reference
QOL
Before
ICU Key Inclusion or Exclusion Criteria
Description of
Nonresponders
Age-/Gender-Matched General
Population to Compare QOL
Cardiac arrest
Saner et al, 2002 (46) No Patients with hypoxic brain damage,
drug abusers, in hospital resuscitation,
non-German-speaking, and 20 or
80 yrs were excluded
No Healthy controls of similar age, gender,
and socioeconomic status
Bunch et al, 2003 (47) No Only patients with OOHCA with
ventricular fibrillation were included
Yes Age- and gender-matched norms from a
sample of the general U.S. population
Kuilman et al, 1999 (48) No Successfully resuscitated patients were
included
No No
Graf et al, 2008 (49) No Patients who received cardiopulmonary
resuscitation for an in-hospital cardiac
arrest or OOHCA were included
Yes Healthy German population
Mahapatra et al, 2005 (50) No Only patients with an OOHCA with
ventricular fibrillation were included
No Age- and gender-matched norms from a
sample of the general U.S. population
Lundgren-Nilsson et al, 2005
(51)
No Only cardiac arrest survivors were
included
No Reference Swedish population
Elderly
Montuclard et al, 2000 (52) Yes Consecutive patients 70 yrs with an
ICU LOS 30 d were included
No General French population of mixed age
and 76-yr-old Swedish urban citizens
Merlani et al, 2007 (53) Yes Patients aged 70 yrs with abdominal
pathologies were included
Yes Age-matched population
Kaarlola et al, 2006 (54) No All consecutive patients admitted within
the study period were included
No Controls and an age- and gender-
matched Finnish population
de Rooij et al, 2008 (55) No Consecutive patients aged 80 yrs admitted
within the study period were included
No Age-matched British non-ICU general
population
Garrouste-Orgeas et al, 2006
(56)
No In 73% of patients aged 80 yrs ICU
admission was refused
No Age- and gender-matched general
French population
Kleinpell, 2003 (57) No Patients 45 yrs with ICU LOS of 24
hrs were included
Yes General U.S. population
Pancreatitis
Soran et al, 2000 (58) No Only acute pancreatitis patients were
included
No Age-matched normal control group
Halonen et al, 2003 (59) No Patients (majority needed ICU admission)
with acute pancreatitis were included
Yes Age- and gender-matched Finnish
population
Sepsis
Heyland et al, 2000 (60) No Patients with sepsis were included;
patients with disabilities that would
preclude a telephone interview were
excluded
No General U.S. population
Karlsson et al, 2009 (61) Yes All severe sepsis patients at admission or
during ICU stay were included
Yes Age- and gender-adjusted Finnish
reference population
Korosˇec et al, 2006 (62) No Only sepsis and trauma patients were
included
Yes No
Mixed ICU patients 1 yr after ICU
Pettilä et al, 2000 (67) No No major exclusion criteria No Age- and gender-matched general
Finnish population
Badia et al, 2001 (68) Yes No major exclusion criteria No No
Cuthbertson et al, 2005 (19) Yes Patients who were not expected to
survive ICU were excluded
Yes Age- and gender-matched general U.K.
population
Stricker et al, 2005 (69) No Surgical and trauma patients with ICU
LOS 7 d and with ICU-LOS 7d
were matched. Burn injuries were
excluded
Yes Age- and gender-matched sample of the
German population
Long-term QOL
García Lizana et al, 2003 (70) Yes ICU admissions for uncomplicated
elective postoperative surgery were
excluded
Yes No
Graf et al, 2005 (71) No Patients with ICU LOS 24 hrs were
excluded
No Age-matched group of healthy Germans
Kaarlola et al, 2003 (72) No Patients who responded to both
questionnaires in 1996 and 2001 were
included
Yes Age- and gender-matched Finnish
population
Flaatten and Kvåle, 2001 (73) No Heart surgery and burn patients were
not included
No Age- and gender-matched general
Norwegian population
2394 Crit Care Med 2010 Vol. 38, No. 12
studies that used at least one of four
generic QOL instruments (SF-36, EQ-5D,
RAND-36, NHP) were included. Generic
instruments apply to a broad spectrum of
populations and therefore are less re-
sponsive to changes in specific conditions
as compared with specific QOL instru-
ments (9). Although there is still no con-
sensus about which tool should be used
to measure QOL in critical care patients,
SF-36 and EQ-5D are considered to be
valid and reliable instruments for criti-
cally ill patients (10). The EQ-5D is vali-
dated for European populations (76, 77),
but some still consider SF-36 or
RAND-36 as the generic instrument of
first choice in critically ill patients (19,
60, 67). Using use both EQ-5D and SF-36
together can be recommended (20).
One of the goals of QOL measures is
differentiating between people with a bet-
ter and a worse QOL and measuring how
much QOL has changed over time (9).
This change in QOL over time leads to an
important and difficult issue in QOL
studies. How long is “long” in long-term
outcome, and when will functional out-
come measures and questionnaires no
longer give additional information? The
follow-up intervals for QOL were very dif-
ferent in the included studies, which
made it difficult to conclude which time
course should be considered as the best
to interpret the overall results and as
sufficient to allow regaining the best
achievable QOL (71). Between studies,
there were large differences in timing,
but also within the studies themselves
there were large differences; the fol-
low-up intervals differed greatly, which
was correctly considered as a limitation
of study results (26, 27, 35, 36, 45– 47,
50). A follow-up period of 1 yr is probably
too short because physical limitations
still tend to dominate over emotional
problems (19, 30, 31, 35, 37, 41), and
physical problems will not always be re-
covered (67). One year may also be too
short to become accustomed to more re-
strictions in daily life (72). When fol-
low-up periods extend to 1 yr, a ten-
dency toward more emotional problems
was found. It is generally accepted that
the real burden of critical illness is seen
up to 6 months after ICU discharge (32,
64), although it is possible that studies
using 6 months as the first time point for
data collection missed an earlier decline
in QOL (19). Follow-up of 1 or 2 yrs will
probably capture the most, and it may be
the limit for improvement in most QOL
dimensions, as seen after severe trauma
(44, 68). Still, mental health will be af-
fected for many more years (35, 70).
The most important problem of long-
term follow-up times is that more pa-
tients will be lost to follow-up, which
could lead to an important bias in results.
Patients who do not respond can do so for
many different reasons. They can con-
sider QOL questionnaires trivial if they
recovered well, they can have post-
traumatic stress disorder and avoid seek-
ing memories of their ICU treatment,
they can be too ill to have the ability to
respond, or they may have died before
completing the survey (35, 36, 54). As
such, QOL responders may represent a
sample of healthier patients (47, 58).
Therefore, analyzes of responders vs.
nonresponders concerning severity of ill-
ness scores, comorbidities, mortality, or
age should be made (44). To avoid selec-
tion bias, every effort has to be made to
target the highest response rate possible.
In many studies, although it was time-
consuming and labor-intensive to do so,
patients who did not respond to the ini-
tial mailed survey or to a mailed re-
minder were phoned, which did not al-
ways guarantee a high response rate (35,
39, 73). A lost-to-follow-up rate of 20% is
considered to be acceptable for QOL stud-
ies (19), but only 49% of the studies had
a response rate of at least 80% of the
eligible patient population for long-term
outcome and QOL assessment. As a con-
sequence, the number of patients with a
reliable QOL assessment at least 1 yr after
ICU discharge was low.
When QOL measures are used as dis-
criminative instruments, possible con-
founders that could influence QOL
should be eliminated. Therefore, QOL in
ICU patients can be compared to an age-
and gender-matched general population,
which should be considered as the upper
limits of what is achievable (75). In most
studies, QOL responders were matched
with a representative healthy population.
The study findings can also be compared
with an appropriate control group, elim-
inating the influence of specific health
conditions (25, 62). More important,
Table 3. Continued
Reference
QOL
Before
ICU Key Inclusion or Exclusion Criteria
Description of
Nonresponders
Age-/Gender-Matched General
Population to Compare QOL
Kvåle and Flaatten, 2003 (74) No Heart surgery and burn patients were
not included
Yes Scores after 6 mos compared with scores
after 2 yrs
Kvåle and Flaatten, 2002 (75) No Heart surgery and burn patients were
not included
No Age- and gender-matched control groups
from the general Norwegian
population
Various diseases
De Boer et al, 2000 (63) No Only long-term survivors without tumor
recurrence were included
No Age-matched reference population
Ahlström et al, 2005 (64) No Only acute kidney injury patients
needing renal replacement therapy
were included
Yes Age- and gender-matched population
Ylipalosaari et al, 2007 (65) No Only hospital survivors with ICU LOS
48 hrs were included
Yes No
Orwelius et al, 2008 (66) No Only adult patients with ICU LOS 24
hrs and alive 6 mos after discharge
were included
Yes Random sample from the main intake
area of the hospitals was used as a
reference group
QOL, quality of life; ICU, intensive care unit; ARDS, acute respiratory distress syndrome; ISS, injury severity score; OOHCA, out-of-hospital cardiac
arrest; LOS, length of stay.
2395Crit Care Med 2010 Vol. 38, No. 12
Table 4. Major findings and factors influencing long-term QOL
Reference Long-Term QOL: Major Finding QOL: Influencing Factors
ARDS
Davidson et al, 1999 (25) ARDS survivors had a significant reduction in QOL; sepsis-
induced ARDS patients had more severe reductions in
QOL than trauma-induced ARDS patients
ARDS and its sequelae, not comorbid disease,
severity of trauma or illness, duration of
mechanical ventilation, or hospital stay
Schelling et al, 2000 (26) Long-term ARDS survivors have a significant reduced QOL Multiple pulmonary function impairments
Rothenhäusler et al, 2001 (27) Long-term QOL was impaired Cognitive deficits and disability
Kapfhammer et al, 2004 (28) Long-term ARDS survivors had major impairments in
long-term QOL
Posttraumatic stress disorder
Hopkins et al, 1999 (29) After 1 yr, there was improvement for the physical but not
for the emotional domains
Cognitive impairments
Orme et al, 2003 (30) ARDS survivors, treated with high or low tidal volume
ventilation, had a reduced QOL, which was related to
physical rather than emotional concerns
Pulmonary function impairments
Hopkins et al, 2005 (31) ARDS survivors had decreased QOL, with physical and
emotional domains improving at 1 yr, but no additional
change or decline at 2 yrs
Neurocognitive impairments, although these may
represent morbidity from critical illness rather
than be specific for ARDS
Heyland et al, 2005 (32) ARDS survivors had a significantly lower QOL than age-
and gender-matched controls; after 1 yr, there was an
improvement in the physical domains, whereas the
mental scores remained unchanged
Pulmonary function impairments, baseline
comorbidities
Parker et al, 2006 (33) Primary ARDS patients had significantly better QOL scores
than patients with secondary ARDS
Primary vs. secondary ARDS; not ICU LOS,
hospital LOS, duration of mechanical
ventilation, comorbidity, lung function
Herridge et al, 2003 (34) QOL improved over 1 yr after ICU discharge but remained
lower than these of the control population
Functional disability attributable to muscle
wasting, weakness, fatigue
Deja et al, 2006 (35) QOL in patients with ARDS was significantly reduced in
all dimensions
Posttraumatic stress disorder
Prolonged mechanical ventilation
Combes et al, 2003 (36) QOL was impaired but perceived as acceptable, with
psychosocial aspects being better than physical
performance
Worse QOL seen in ARDS survivors
Chelluri et al, 2004 (37) QOL was impaired mainly on the physical and social
domains but comparable on the mental health and
emotional domains
Influence of age and chronic illness predominate
the long-term outcome
Cox et al, 2009 (38) One year after ICU discharge, the majority of patients had
a poor QOL
NA
Trauma
Miller et al, 2000 (39) QOL was low, especially in the physical domains NA
Mackenzie et al, 2002 (40) 1 yr after trauma, QOL was low, except for vitality and
mental health
NA
Dimopoulou et al, 2004 (41) QOL was impaired in physical functioning, working ability,
and emotional well-being
Injury severity, degree of brain trauma
Sluys et al, 2005 (42) 5 yrs after trauma, QOL was low in all dimensions of the
Short-Form 36
Age, surgical procedures, ICU and hospital LOS,
in-hospital complications, inadequate
information
Vles et al, 2005 (20) QOL was low and one-quarter of those of working age
were unable to return to work
Injury severity, female gender
Jackson et al, 2007 (43) QOL was low Cognitive impairments
Ulvik et al, 2008 (44) More than 2 yrs postinjury, 74% reported impaired QOL,
mostly caused by pain and discomfort, but only a
minority had severe problems
Severity of illness and injury, time since trauma
(pain), female gender, degree of brain trauma;
not age
Ringdal et al, 2009 (45) Trauma patients scored low on all Short-Form 36 domains Delusional memories, comorbidity
Cardiac arrest
Saner et al, 2002 (46) Long-term QOL remained fulfilling with only a few
changes in the psychosocial profile
Little impact of changes in psychosocial profile
Bunch et al, 2003 (47) Except from a reduction in vitality, QOL was similar to
that of the general population
NA
Kuilman et al, 1999 (48) No difference in QOL between patients resuscitated by
emergency personnel, physicians, or bystanders
NA
Graf et al, 2008 (49) Patients who survive without severe neurologic disabilities
may expect a good QOL
NA
Mahapatra et al, 2005 (50) Long-term survival and QOL are equally favorable in both
genders
NA
Lundgren-Nilsson et al, 2005
(51)
QOL improved over the year with values comparable to
the reference population
Cognitive impairments
2396 Crit Care Med 2010 Vol. 38, No. 12
Table 4. Continued
Reference Long-Term QOL: Major Finding QOL: Influencing Factors
Elderly
Montuclard et al, 2000 (52) After 1 yr, perceived QOL was good, especially emotional
and social functioning
A moderate disability influenced QOL
Merlani et al, 2007 (53) A high mortality and a decrease in QOL were observed for
elderly patients with abdominal pathologies; these
patients adapted well to their physical limitations
NA
Kaarlola et al, 2006 (54) Aging decreased QOL mostly in the physical domains, but
elderly patients had better values for mental health than
the younger controls
Acceptance of disability is better with a good
social network
de Rooij et al, 2008 (55) QOL was significantly lower for usual activities; most
patients were willing to receive ICU treatment again if
necessary
NA
Garrouste-Orgeas et al, 2006
(56)
After 1 yr, QOL was poorer than in the general population;
one-half of the survivors did not want further ICU
admission if necessary
NA
Kleinpell, 2003 (57) In the middle-aged and elderly patient group, Short-Form
36 scores remained below the general population norms
but increased over time
Severity of illness rather than age
Pancreatitis
Soran et al, 2000 (58) Long-term QOL is good and comparable with an age-
matched control population
NA
Halonen et al, 2003 (59) Long-term QOL is good and comparable with an age-
matched control population
Working status before acute pancreatitis, age;
not follow-up time, cause, gender, ICU
treatment, ICU LOS, multiple organ failure,
operating status
Sepsis
Heyland et al, 2000 (60) The QOL of sepsis survivors is lower than that of the
general population and comparable to QOL of patients
with chronic disease or survivors of acute lung injury
NA
Karlsson et al, 2009 (61) QOL in most patients was already lower before the episode
of severe sepsis than in the general population, and it
was even lower after the critical illness
NA
Korosˇec et al, 2006 (62) Surgical ICU patients with sepsis have a higher mortality
than trauma patients; however, QOL after 2 yrs is
reduced to the same level in both groups
Anxiety and depression (trauma)
Mixed ICU patients 1 yr after ICU
Pettilä et al, 2000 (67) Survivors had a lower QOL than an age- and gender-
matched general population; however, patients perceived
their QOL as better or similar as before their ICU stay
Multiple organ failure, age, diagnostic category
Badia et al, 2001 (68) Trauma patients experienced a worsening, unscheduled
surgery and medical patients experienced a slight
deterioration, and scheduled patients experienced a
considerable improvement in QOL
Diagnostic category
Cuthbertson et al, 2005 (19) Physical QOL increased to premorbid levels 1 yr after ICU
discharge but physical scores remained below the
population norms; mental scores were similar or higher
than population norms; nonsurvivors had a lower QOL
than survivors at all time points
Poor baseline situation; not prolonged ICU LOS,
age, surgical or medical admissions
Stricker et al, 2005 (69) When taking into account severity of illness, QOL 1 yr
after ICU discharge is comparable between patients with
short and long ICU stay; QOL remained lower than in a
general population, mostly in physical aspects
Not prolonged ICU LOS
Long-term QOL
García Lizana et al, 2003 (70) 38% felt their QOL was worse, 37% felt it to be similar,
and 25% felt it was better than before their ICU
admission; psychology domains were the most
frequently affected
Previous QOL, prolonged hospital stay, ICU
readmission, diagnostic category, Acute
Physiology and Chronic Health Evaluation II
score, age, female gender, organ failure
Graf et al, 2005 (71) After 5 yrs, most patients lived independently and had a
good QOL
Not severity of illness, morbidity, resource
consumption, age, or gender
Kaarlola et al, 2003 (72) Six years after ICU discharge, QOL was comparable with
that of the general population; QOL revealed worse
physical functioning, pain, and general health but
improvement in the psychological domains
NA
Flaatten and Kvåle, 2001 (73) QOL was acceptable but it was still lower than in the
general population
NA
2397Crit Care Med 2010 Vol. 38, No. 12
long-term QOL should also be compared
with QOL before ICU admission, to dis-
criminate whether poor long-term QOL
is a result of the severity of illness or is
attributable to confounding factors or
“background variables,” such as comor-
bid disease, poor preadmission QOL, age,
gender, or acquired complications (44).
Which factor will influence the most
long-term QOL is a difficult question, and
literature is definitively not conclusive
about this issue (74). The long-term ef-
fect of a certain condition on QOL is
cohort specific and may be the residua of
any severe critical illness (34). It will also
depend on the follow-up period and the
tools used and will probably be a mixture
of severity of illness, previous health sta-
tus, premorbid QOL, age, gender, and di-
agnostic category.
Previous studies of QOL before ICU
admission support the hypothesis that
patients’ premorbid QOL has a large ef-
fect on QOL after critical illness (78, 79).
It has been proved that pre-ICU QOL is
low compared to that of the general pop-
ulation, indicating that ICU patients dif-
fer from the average population even be-
fore the onset of critical illness (10, 44,
80). Poor QOL before critical illness is
also correlated with poor outcome (19,
81– 84). Impaired QOL after ICU thus
may reflect a poor baseline situation
rather than being a function of intensive
care (19, 67). Measuring QOL at baseline
is difficult; in the majority of studies
(83%), this was not performed. One-third
of these studies considered this as a lim-
itation (20, 25, 31, 36, 42, 43, 54–57, 62,
64, 65, 67). Most patients will not be able
to complete questionnaires at time of ICU
admission and many studies asked pa-
tients or proxies a long period afterward
how QOL was before admission (20, 44,
52, 53, 62). Recall bias can influence
results of these QOL surveys. In retro-
spective studies, recall bias can also add
some uncertainty to the study findings
because QOL assessment is based on
patient’s recall of memories from the
ICU stay (45, 46). No baseline assess-
ment of QOL because it would have
been assessed retrospectively can be the
reason for not measuring QOL prior to
ICU admission (56).
Some authors considered that only pa-
tients could evaluate their own QOL (56),
or they considered it a potential danger
for bias if questionnaires were completed
by proxies (67). However, the SF-36 and
EQ-5D questionnaire completed by prox-
ies can reliably assess the QOL of the
critically ill patient on admission to the
ICU (68, 81), although it is difficult to
interview proxies when their relatives are
critically ill (37). Proxies tend to under-
estimate the QOL of the patient, but dif-
ferences are usually small (81).
There are some methodologic limita-
tions in this review. First, only four ge-
neric QOL instruments were included,
which are, however, commonly used in
critically ill patients (8). This allowed us
to compare among studies and make
more comprehensive conclusions. Sec-
ond, some studies had a low number of
QOL responders and a nonuniform fol-
low-up time, which limits the interpreta-
tion of study results. The findings of this
review are also limited because of infre-
quent collection of QOL at baseline.
CONCLUSION
Future outcome evaluations should
not be limited to “dead” or “alive” but
should also incorporate QOL, even
though this is much more complicated to
investigate. Long-term QOL in critically
ill patients depends largely on diagnostic
category, with the worst reductions
found in patients who survive severe
ARDS, sepsis, trauma, and prolonged me-
chanical ventilation. For critically ill pa-
tients in general, a lower QOL compared
to that of an age- and gender-matched
healthy population was seen. However,
evidence for poorer QOL after ICU is mis-
leading when the previous health state of
the patient is not taken into account.
Baseline QOL assessment is necessary
when investigating the influence of the
critical illness and should be assessed on
ICU admission to avoid recall bias. Fol-
low-up periods should be kept strictly
uniform, although there is no consensus
regarding the most appropriate follow-up
time. Measures to gain the highest re-
sponse rate to avoid selection bias should
be taken. Nevertheless, comparisons be-
tween responders and nonresponders
should always be made.
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2400 Crit Care Med 2010 Vol. 38, No. 12
    • "In the present study, two scales were used to assess the PFS with the goal of increasing the reliability of our results. Studies assessing the quality of life after ICU discharge suggest that these patients do not return to the same level of health that they had before they fell ill and that their quality of life is lower than that of the general population, at least in the early years [23]. Interestingly, our data revealed that the source of care, that is, public or private, did not influence the PFSs of the survivors. "
    [Show abstract] [Hide abstract] ABSTRACT: Purpose. The long-term outcomes of patients after discharge from tertiary ICUs as they relate to the public versus private healthcare systems in Brazil have not yet been evaluated. Materials and Methods. A multicenter prospective cohort study was conducted to compare the all-cause mortality and the physical functional status (PFS) 24 months after discharge from the ICU between adult patients treated in the public and private healthcare systems. A propensity score- (PS-) matched comparison of all causes of mortality and PFS 24 months after discharge from the ICU was performed. Results. In total, 928 patients were discharged from the ICU including 172 (18.6%) patients in the public and 756 (81.4%) patients in the private healthcare system. The results of the PS-matched comparison of all-cause mortality revealed higher mortality rates among the patients of the public healthcare system compared to those of the private healthcare system (47.3% versus 27.6%, P = 0.003 ). The comparison of the PS-matched Karnofsky performance and Lawton activities of daily living scores between the ICU survivors of the public and private healthcare systems revealed no significant differences. Conclusions. The patients of private healthcare system exhibited significantly greater survival rates than the patients of the public healthcare system with similar PFS following ICU discharge.
    Full-text · Article · Mar 2016
    • "It is a broad ranging concept affected in a complex way by the person's physical health, psychological state, personal beliefs, social relationships and their relationship to salient features of their environment [5]. QoL has been investigated in a number of previous studies, including healthy individuals [6,7] as well as patients with various medical conditions, such as: low-back pain [8], diabetes [9], multiple sclerosis [10], cutaneous melanoma [11], and among patients: after injuries [12], after intensive care [13]. To date, only in one study examined quality of life in patients with cervicogenic headache [14]. "
    [Show abstract] [Hide abstract] ABSTRACT: Abstract Introduction: Although the quality of life has been investigated in a numerous of previous studies, still is little known about this topic among patients with cervicogenic headache diagnosis. Aim of the study: To assess QoL in CGH group and to explore the relationship of QoL to selected demographic and medical variables. Material and methods: A total of 47 patients with cervicogenic headache were examined. On average, participants were 47,21 years old and 55,3% was female. To evaluate a quality of life the WHOQOL-BREF questionnaire was used. Results: Means and standard deviations in each domain were as follows: DOM1=10,04±3,07; DOM2=14,49±2,88; DOM3=16,59±3,12; DOM4=15,80±2,85. The highest mean values were noted in following items: Q25 (transport; M=4,46), Q11 (body appearance; M=4,33) and Q13 (vailability of information; M=4,31). The lowest scores concerned Q3 (pain; M=1,86), Q4 (dependence on medical treatment; M=1,94) and Q10 (energy; M=2,07). Differences in QoL due to age, sex and selected medical variables were observed. Relationship of QoL to education level, marital status and local residence were also found. Conclusions: The present study supports the hypothesis that quality of life impairment is likely to be present in clinical samples of CGH and is directly associated with duration time of CGH and number of CGH incidence during day.
    Full-text · Article · Jan 2016
    • "This finding illustrates that simply to measure HRQOL after intensive care as better or worse, relates to the reference we use to compare. In particular patient groups, morbidity changes have been described as more severe [31]. "
    [Show abstract] [Hide abstract] ABSTRACT: The documentation of patient outcomes after intensive care unit stays has long been an important task for the intensivist. Mortality was the first parameter to be utilized with the introduction of the APACHE and SAPS mortality prediction scores. Mortality, however, is difficult to predict in individuals and at present must be group based. Morbidity, however, can be individualized and has gained a significant amount of recent interest.
    Chapter · Jan 2016 · Journal of Education, Health and Sport
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