[Skip to Content]
Access to paid content on this site is currently suspended due to excessive activity being detected from your IP address 54.211.168.204. Please contact the publisher to request reinstatement.
[Skip to Content Landing]
Download PDF
Table 1. 
Physiologic Status of Patients Hospitalized for Acute Exacerbation of Severe CHF*
Physiologic Status of Patients Hospitalized for Acute Exacerbation of Severe CHF*
Table 2. 
Health-Related Quality of Life Among Patients Hospitalized for Acute Exacerbation of Severe CHF*
Health-Related Quality of Life Among Patients Hospitalized for Acute Exacerbation of Severe CHF*
Table 3. 
Change of HRQL Among Patients Hospitalized for Acute Exacerbation of Severe CHF*
Change of HRQL Among Patients Hospitalized for Acute Exacerbation of Severe CHF*
Table 4. 
Effect of Missing Data on HRQL Outcomes*
Effect of Missing Data on HRQL Outcomes*
1.
Ho  KKLPinsky  JLKannel  WBLevy  D The epidemiology of heart failure: the Framingham study. J Am Coll Cardiol. 1993;22 (suppl A) 6A- 13AArticle
2.
Schocken  DDArrieta  MILeaverton  PERoss  EA Prevalence and mortality rate of congestive heart failure in the United States. J Am Coll Cardiol. 1992;20301- 306Article
3.
Ghali  JKCooper  RFord  E Trends in hospitalization rates for heart failure in the United States, 1973-1986: evidence for increasing population prevalence. Arch Intern Med. 1990;150769- 773Article
4.
Doval  HCNul  DRGrancelli  HOPerrone  SVBortman  GRCuriel  R Randomized trial of low-dose amiodarone in severe congestive heart failure. Lancet. 1994;344493- 498Article
5.
Kennedy  HLBrooks  MMBarker  AH  et al.  Beta-blocker therapy in the cardiac arrhythmia suppression trial. Am J Cardiol. 1994;74674- 680Article
6.
The Acute Infarction Ramipril Efficacy (AIRE) Study Investigators, Effect of ramipril on mortality and morbidity of survivors of acute myocardial infarction with clinical evidence of heart failure. Lancet. 1993;342821- 828
7.
Bourassa  MGGurne  OBangdiwala  SI  et al.  Natural history and patterns of current practice in heart failure. J Am Coll Cardiol. 1993;22 (suppl A) 14A- 19AArticle
8.
The SOLVD Investigators, Effect of enalapril on mortality and the development of heart failure in asymptomatic patients with reduced left ventricular ejection fraction. N Engl J Med. 1992;327685- 691Article
9.
The SOLVD Investigators, Effect of enalapril on survival in patients with reduced left ventricular ejection fractions and congestive heart failure. N Engl J Med. 1991;325293- 302Article
10.
Eichhorn  EJTandon  PKDiBianco  R  et al.  Clinical and prognostic significance of serum magnesium concentration in patients with severe chronic congestive heart failure: the PROMISE study. J Am Coll Cardiol. 1993;21634- 640Article
11.
Packer  MCarver  JRRodeheffer  RJ  et al.  Effect of oral milrinone on mortality in severe chronic heart failure. N Engl J Med. 1991;3251468- 1475Article
12.
Pfeffer  MABraunvald  EMoyé  LA  et al.  Effect of captopril on mortality and morbidity in patients with left ventricular dysfunction after myocardial infarction. N Engl J Med. 1992;327669- 677Article
13.
Jaeger  AAHlatky  MAPaul  SMGortner  SR Functional capacity after cardiac surgery in elderly patients. J Am Coll Cardiol. 1994;24104- 108Article
14.
Stewart  ALGreenfield  SHays  RD  et al.  Functional status and well-being of patients with chronic conditions: results from the medical outcomes study. JAMA. 1989;262907- 913Article
15.
Rogers  WJJohnstone  DEYusuf  S  et al.  Quality of life among 5025 patients with left ventricular dysfunction randomized between placebo and enalapril: the studies of left ventricular dysfunction. J Am Coll Cardiol. 1994;23393- 400Article
16.
Ho  KKLAnderson  KMKannel  WBGrossman  WLevy  D Survival after the onset of congestive heart failure in Framingham Heart Study subjects. Circulation. 1993;88107- 115Article
17.
Cowley  AJSkene  AM Treatment of severe heart failure: quantity or quality of life? a trial of enoximone. Br Heart J. 1994;72226- 230Article
18.
Seneviratne  BMoore  GAWest  PD Effect of captopril on functional mitral regurgitation in dilated heart failure: a randomized double blind placebo controlled trial. Br Heart J. 1994;7263- 68Article
19.
Rector  TSJohnson  GDunkman  B  et al.  Evaluation by patients with heart failure of the effects of enalapril compared with hydralazine plus dinitrate on quality of life: V-HeFT II. Circulation. 1993;87 (suppl VI) VI71- VI77
20.
Stevenson  WGMiddlekauff  HRStevenson  LWSaxon  LAWoo  MAMoser  D Significance of aborted cardiac arrest and sustained ventricular tachycardia in patients referred for treatment therapy of advanced heart failure. Am Heart J. 1992;124123- 130Article
21.
Fonarow  GCChelimsky-Fallick  CStevenson  LW  et al.  Effect of direct vasodilation with hydralazine versus angiotensin-converting enzyme inhibition with captopril on mortality in advanced heart failure: the Hy-C trial. J Am Coll Cardiol. 1992;19842- 850Article
22.
White  MRouleau  JLRuddy  TDDeMarco  TMoher  DChatterjee  K Decreased coronary sinus oxygen content: a predictor of adverse prognosis in patients with severe congestive heart failure. J Am Coll Cardiol. 1991;181631- 1637Article
23.
Keogh  AMFreund  JBaron  DWHickie  JB Timing of cardiac transplantation in idiopathic dilated cardiomyopathy. Am J Cardiol. 1988;61418- 422Article
24.
The CONSENSUS Trial Study Group, Effects of enalapril on mortality in severe congestive heart failure. N Engl J Med. 1987;3161429- 1435Article
25.
Kelly  TLCremo  RNielsen  CShabetai  R Prediction of outcome in late-stage cardiomyopathy. Am Heart J. 1990;1191111- 1121Article
26.
Franciosa  JAWilen  MZiesche  SCohn  JN Survival in men with severe chronic left ventricular failure due to either coronary heart disease or idiopathic dilated cardiomyopathy. Am J Cardiol. 1983;51831- 836Article
27.
Keogh  AMBaron  DWHickie  JB Prognostic guides in patients with idiopathic or ischemic dilated cardiomyopathy assessed for cardiac transplantation. Am J Cardiol. 1990;65903- 908Article
28.
Middlekauff  HRStevenson  WGStevenson  LW Prognostic significance of atrial fibrillation in advanced heart failure: a study of 390 patients. Circulation. 1991;8440- 48Article
29.
Anderson  BWaagstein  F Spectrum and outcome of congestive heart failure in a hospitalized population. Am Heart J. 1993;126632- 640Article
30.
Smith  RFJohnson  GZiesche  SBhat  GBlankenship  KCohn  JN Functional capacity in heart failure: comparison of methods for assessment and their relation to other indexes of heart failure. Circulation. 1993;87 (suppl VI) VI88- VI93
31.
Wegner  NKMattson  MEFurberg  CDElinson  J Assessment of quality of life in clinical trials of cardiovascular therapies. Am J Cardiol. 1984;54908- 913Article
32.
Guyatt  GH Measurement of health-related quality of life in heart failure. J Am Coll Cardiol. 1993;22 (suppl A) 185A- 191AArticle
33.
Burns  RBMcCarthy  EPMoskowitz  MA  et al.  Outcomes for older men and women with congestive heart failure. J Am Geriatr Soc. 1997;45276- 280
34.
Murphy  DJCluff  LE SUPPORT: Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments: study design. J Clin Epidemiol. 1990;43 (suppl) 1S- 123SArticle
35.
Hamel  MBGoldman  LTeno  J  et al.  Identification of comatose patients at high risk for death or severe disability: SUPPORT investigators: Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatment. JAMA. 1995;2731842- 1848Article
36.
Covinsky  KEGoldman  LCook  EF  et al.  The impact of serious illness on patients' families: SUPPORT investigators: Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatment. JAMA. 1994;2721839- 1844Article
37.
Knaus  WAHarrell  FE  JrLynn  J  et al.  The SUPPORT prognostic model: objective estimates of survival for seriously ill hospitalized adults: Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatment. Ann Intern Med. 1995;122191- 203Article
38.
Tsevat  JCook  EFGreen  ML  et al.  Health values of the seriously ill. Ann Intern Med. 1995;122514- 520Article
39.
Phillips  RSWenger  NSTeno  J  et al.  Choices of seriously ill patients about cardiopulmonary resuscitation: correlates and outcomes. Am J Med. 1996;100128- 137Article
40.
Murphy  DJKnaus  WALynn  J Study population in SUPPORT: patients (as defined by disease categories and mortality projections), surrogates, and physicians. J Clin Epidemiol. 1990;43 (suppl) 11S- 28SArticle
41.
Phillips  RSKnaus  WA Patient characteristics in SUPPORT: sociodemographics, admission diagnosis, co-morbidities and acute physiology score. J Clin Epidemiol. 1990;43 (suppl) 29S- 31SArticle
42.
Phillips  RSGoldman  LBergner  M Patient characteristics in SUPPORT: activity status and cognitive function. J Clin Epidemiol. 1990;43 (suppl) 33S- 36SArticle
43.
Oye  RKLandefeld  CSJayes  RL Outcomes in SUPPORT. J Clin Epidemiol. 1990;43 (suppl) 83S- 87SArticle
44.
Landefeld  CSPhillips  RSBergner  M Patient characteristics in SUPPORT: functional status. J Clin Epidemiol. 1990;43 (suppl) 37S- 39SArticle
45.
Tsevat  JDawson  NVMatchar  DB Assessing quality of life and preferences in the seriously ill using utility theory. J Clin Epidemiol. 1990;43 (suppl) 73S- 77SArticle
46.
Kreling  BRobinson  DKBergner  M Data collecting strategies in SUPPORT. J Clin Epidemiol. 1990;43 (suppl) 5S- 9SArticle
47.
Phillips  RSMurphy  DJGoldman  LKnaus  WA Patient characteristics in SUPPORT: disease specific clinical data. J Clin Epidemiol. 1990;43 (suppl) 41S- 45SArticle
48.
Knaus  WAWagner  DPDraper  EA  et al.  APACHE III. Crit Care Med. 1989;17 (suppl 12) S176- S221Article
49.
Knaus  WAWagner  DPDraper  EA  et al.  APACHE III prognostic system: risk prediction of hospital mortality for critically ill hospitalized adults. Chest. 1991;1001619- 1636Article
50.
Teasdale  GMurray  GParker  LJennett  B Adding up the Glasgow Coma Score. Acta Neurochir Suppl (Wien). 1979;28 (1) 13- 16
51.
Hlatky  MABoineau  REHigginbotham  MB  et al.  A brief self-administered questionnaire to determine functional capacity (the Duke Activity Status Index). Am J Cardiol. 1989;64651- 654Article
52.
Nelson  CLHerndon  JEMark  DBPryor  DBCaliff  RMHlatky  MA Relation of clinical and angiographic factors to functional capacity as measured by the Duke Activity Status Index. Am J Cardiol. 1991;68973- 975Article
53.
Bergner  MBobbitt  RACarter  WBGilson  BS The Sickness Impact Profile: development and final revision of a health status measure. Med Care. 1981;19787- 805Article
54.
Katz  SFord  ABMoskowitz  RWJackson  BAJaffe  W Studies of illness in the aged: the index of ADL: a standardized measure of biological and psychosocial function. JAMA. 1963;185914- 919Article
55.
Katz  SAkpom  CA A measure of primary sociobiological function. Int J Health Serv. 1976;6493- 508Article
56.
Guyatt  GHFeeny  DHPatrick  DL Measuring health-related quality of life. Ann Intern Med. 1993;118622- 629Article
57.
Stewart  ALHays  RDWare  JE The MOS Short-term General Health Survey: reliability and validity in a patient population. Med Care. 1988;26724- 735Article
58.
Revicki  DAKaplan  RM Relationship between psychometric and utility-based approaches to the measurement of health-related quality of life. Qual Life Res. 1993;2477- 487Article
59.
Tsevat  JGoldman  LLamas  GA  et al.  Functional status versus utilities in survivors of myocardial infarction. Med Care. 1991;291153- 1159Article
60.
Cullen  DJCivetta  JMBriggs  BAFerrara  LC Therapeutic intervention scoring system: a method for quantitative comparison of patient care. Crit Care Med. 1974;257- 60Article
61.
Keene  ARCullen  DJ Therapeutic intervention scoring system: update 1983. Crit Care Med. 1983;111- 3Article
62.
Teno  JMHakim  RBKnaus  WA  et al.  Preferences for cardiopulmonary resuscitation: physician-patient agreement and hospital resource use: the SUPPORT investigators. J Gen Intern Med. 1995;10179- 186Article
63.
Wu  AWDamiano  AMLynn  J  et al.  Predicting future functional status for seriously ill hospitalized adults: the SUPPORT prognostic model. Ann Intern Med. 1995;122342- 350Article
64.
Fletcher  AMcLoone  PBulpitt  C Quality of life on angina therapy: a randomized controlled trial of transdermal glyceryl trinitrate against placebo. Lancet. 1988;24- 7Article
65.
Miranda  DR Quality of life after cardiopulmonary resuscitation. Chest. 1994;106524- 530Article
66.
Tsevat  JGoldman  LSoukup  JR  et al.  Stability of time-tradeoff utilities in survivors of myocardial infarction. Med Decis Making. 1993;13161- 165Article
67.
Fryback  DGDasbach  EJKlein  R  et al.  The Beaver Dam Health Outcomes Study: initial catalog of health-state quality factors. Med Decis Making. 1993;1389- 102Article
68.
Hlatky  MACharles  EDNobrega  F  et al.  Initial functional and economic status of patients with multivessel coronary artery disease randomized in the bypass angioplasty revascularization investigation (BARI). Am J Cardiol. 1995;7534C- 41CArticle
69.
Kubo  SHGollub  SBourge  R  et al.  Beneficial effects of pimobendan on exercise tolerance and quality of life in patients with heart failure: results of a multicenter trial. Circulation. 1992;85942- 949Article
70.
Rector  TSCohn  JN Assessment of patient outcome with the Minnesota Living With Heart Failure questionnaire: reliability and validity during a randomized, double-blind, placebo-controlled trial of pimobendan. Am Heart J. 1992;1241017- 1027Article
71.
Rector  TSKubo  SHCohn  JN Validity of the Minnesota Living With Heart Failure questionnaire as a measure of therapeutic response to enalapril or placebo. Am J Cardiol. 1993;711106- 1107Article
72.
US Bureau of the Census, Statistical Abstract of the United States: 1994. 114th ed. Washington, DC US Bureau of the Census1994;
73.
Layde  PMBroste  SKDesbiens  N  et al.  Generalizability of clinical studies conducted at tertiary care medical centers: a population-based analysis. J Clin Epidemiol. 1996;49835- 841Article
Original Investigation
May 25, 1998

Outcomes of Acute Exacerbation of Severe Congestive Heart FailureQuality of Life, Resource Use, and Survival

Author Affiliations

From the Departments of Medicine at the following institutions: MetroHealth Medical Center, Case Western Reserve University, Cleveland (Drs Jaagosild and Dawson, and Mr Thomas) and the University of Cincinnati Medical Center, Cincinnati (Dr Tsevat), Ohio; University of California Medical Center, Los Angeles (Dr Wenger); University of Virginia School of Medicine, Charlottesville (Drs Knaus and Connors); Duke University Medical Center, Durham, NC (Dr Califf); University of California, San Franciscov (Dr Goldman); and Marshfield Medical Research Foundation, Marshfield Clinic, Marshfield, Wis (Dr Vidaillet).

Arch Intern Med. 1998;158(10):1081-1089. doi:10.1001/archinte.158.10.1081
Abstract

Background  Congestive heart failure (CHF) is a common disease with high health care costs and high mortality rates. Knowledge of the health-related quality of life outcomes of CHF may guide decision making and be useful in assessing new therapies for this population.

Methods  A prospective cohort study was conducted involving 1390 adult patients hospitalized with an acute exacerbation of severe CHF (New York Heart Association class III-IV). Demographic data and health-related quality of life were determined by interview; physiologic status and cost and intensity of care were determined from hospital charts.

Results  The median (25th, 75th percentiles) age of patients was 68.0 (58.2, 76.9) years; 61.7% were male. Survival was 93.4% at discharge from the index hospitalization, 72.9% at 180 days, and 61.5% at 1 year. Of patients interviewed at 180 days, the median health rating on a scale of 0 to 100 (0 indicates death; 100, excellent health) was 60 (interquartile range, 50-80), and 59.7% were independent in their activities of daily living. Overall quality of life was reported to be good, very good, or excellent in 58.2% at 180 days. Patients with worse functional capacity were more likely to die. Health perceptions among the patients with available interview data improved at 60 and 180 days after acute exacerbation of severe CHF.

Conclusions  Patients hospitalized for acute exacerbation of severe CHF have a generally poor 6-month survival, but survivors retain relatively good functional status and have good health perceptions. Furthermore, health perceptions improve after the acute exacerbation.

CONGESTIVE HEART failure (CHF) is a common disease in the United States, with a prevalence of 7.4 per 1000 men and 4.7 per 1000 women (age-adjusted to the US 1991 population).1 In aggregate, there are an estimated 1 to 2 million adults with CHF at any time in this country,2 and the prevalence is on the rise.3 Hospitalization rates for CHF also have been increasing.3 Despite the high cost of health care for patients with CHF, survival rates are poor. Knowledge of the health-related quality of life (HRQL) outcomes of severe CHF may guide decision making and be useful in assessment of new therapies for this population.

Most previous studies reporting outcomes of CHF were performed in stable patients1,419 or involved small sample sizes.2027 Two larger studies28,29 investigated outcomes of patients hospitalized with CHF, but did not report HRQL outcomes. Recently, there has been an increase in interest in HRQL among patients with CHF.3033 Two large clinical trials used HRQL measurements as an end point to assess therapy for CHF.15,19 However, there have been no large prospective studies describing HRQL, change of HRQL in time, or survival among adults hospitalized due to severe CHF.

Our purposes were to describe patients whose primary reason for hospitalization was acute exacerbation of severe CHF and to determine the outcomes of these patients in terms of mortality, HRQL, and use of resources.

SUBJECTS AND METHODS

The Study to Understand Prognosis and Preferences for Outcomes and Risks of Treatments (SUPPORT) was a prospective 5-center study of the prognoses, preferences, and decision making of seriously ill hospitalized adults, their surrogate decision makers, and their physicians. Phase I of the study described the process of decision making and developed models to predict outcomes. Phase II was an interventional trial to evaluate the effect of prognostic information and enhanced communication. The study population, characteristics of patients and collaborating hospitals, data collection strategies, and statistical methods have been published previously.3447

STUDY POPULATION

From June 12, 1989, to June 11, 1991, and January 7, 1992, to January 24, 1994, all admissions to general medicine, oncology, and surgery floors and all transfers or admissions to intensive care units at the participating hospitals were screened by nurse abstractors. The study involved the following 5 teaching hospitals: Beth Israel Hospital, Boston, Mass; Duke University Medical Center, Durham, NC; MetroHealth Medical Center, Cleveland, Ohio; St Joseph's Hospital, Marshfield, Wis; and University of California Medical Center, Los Angeles. Inclusion and exclusion criteria for the study population have been published previously40 and are available from one of us (N.V.D.).

Of the 9105 patients enrolled in SUPPORT, 1404 patients were admitted with acute exacerbation of severe chronic CHF. Of those, 14 patients had incomplete documentation of inclusion criteria data and were excluded, yielding 1390 patients for this analysis.

Median (25th, 75th percentiles) follow-up was 493 (153, 973) days. At 60 days after study entry, interview data were not available for 237 patients (17.0%) who died before interview, 196 (14.1%) who were unable to communicate, 159 (11.4%) who refused to participate, and 89 (6.4%) for other reasons. At 180 days after study admission, 406 patients (29.2%) had not been interviewed because of death; 150 (10.8%), inability to communicate; 111 (8.0%), refusal; and 77 (5.5%), other reasons. Vital status at 1 year was available for all patients.

MEASUREMENTS

Patients' physiologic status was evaluated using the Acute Physiology Score component of the Acute Physiology and Chronic Health Evaluation III, which is an ordinal scale consisting of weights assigned to 17 physiologic measurements.41,48,49 The Acute Physiology Score has a possible range of scores from 0 to 252; increased scores are strongly associated with an increased risk for death. The Glasgow Coma Scale50 was used to assess patients' neurologic status.

Patients' activity status was measured using the modified Duke Activity Status Index (DASI).42,51,52 This measure of functional capacity gauges the patient's ability to perform common activities and uses the responses in a weighted score. The possible range is from 11 (unable to walk indoors) to 33 (able to do vigorous exercise or aerobics).51,52

The Sickness Impact Profile (SIP) is a measure of perceived health status, with a score ranging from 0 to 100. A higher score describes worse health. The SIP has been found to be valid and reliable53 and was used to provide a more detailed measure of health status at the 60-day interview.43

Patients' functional status, ie, their level of performance of basic activities of daily living (ADL), was measured using the modified Katz Index of Activities of Daily Living (Index of ADL).44,54,55 The Index of ADL is a scale from 0 to 7 whose grades reflect dependence in the following 7 primary self-care functions: bathing, dressing, toileting, transferring, continence, feeding, and walking (1 point for each dependency).54,55

Health perception was assessed using several instruments.29,45,56,57 First, patients rated their overall quality of life as excellent, very good, good, fair, or poor. They also rated their current state of health on a scale from 0 (death) to 100 (excellent health).45 Ratings worse than 0 were allowed but did not occur in our sample. Utility was measured by the time−tradeoff technique, which ascertains the amount of time in excellent health one would equate with living 1 year in the patient's current state of health.45 General health status scales and health utility may measure different attributes of health58 and have been found to be reliable14,57,59 and valid.45,57

Hospital resource use was assessed using the modified Therapeutic Intervention Scoring System (TISS).43,60,61 Higher TISS scores indicate higher intensity of hospital resource consumption. The total cost of care in 1993 dollars was estimated by converting total charge to total cost using each hospital's cost-charge ratio. For patients whose charge data were missing (0.9%), total costs were estimated using the product of average TISS score and length of stay adjusted for each study hospital (R2=0.84).43,62

DATA COLLECTION

Clinical data, including disease-specific information, were collected from hospital charts.41,46,47 Data about sociodemographics, HRQL, and cognitive status were collected by interview. Vital status was determined from follow-up interviews (with patient or surrogate). Hospital chart or National Death Index mortality data were collected if interview follow-up was not possible. According to protocol, interviews with patients and/or their surrogates (defined as the person who would make decisions if the patient were unable to do so) were performed when possible from days 2 to 6 after study admission and at 2 and 6 months after study admission. Early during hospitalization, physicians were asked to estimate their patients' probability of surviving 2 and 6 months. Because interview data were not available for every patient, and because analysis performed on subsets of a database may be biased, we used a published substitution strategy.34,63 Briefly, priority was given to patient response. When patient response was missing, a calibrated surrogate response (mean patient response for each level of surrogate response) was used. Patients' current state of health and time−tradeoff utility data were collected at admission only in phase I. Information bias was minimized by extensive training and supervision of chart abstractors and interviewers.46

DATA ANALYSES

Continuous and discrete variables are described using median (25th, 75th percentiles) and categorical data by percentages. Repeated measures analyses of variance (ANOVA) and ANOVA of contrast variables were used to describe change of HRQL in time. Wilcoxon 2-sample test was used for multiple pairwise comparisons to investigate how missing data influenced HRQL outcomes. The α level selection with Bonferroni correction (.05/16=.003) was used for multiple comparisons. All analyses were performed on a microcomputer using a commercially available statistical package (SAS for PC, Version 6.11, SAS Institute Inc, Cary, NC).

RESULTS
PATIENT CHARACTERISTICS AT STUDY ADMISSION

Median age of the 1390 study patients was 68.0 (58.2, 76.9) years. Median education was 12 (9, 13) years. Eight hundred fifty-eight patients (61.7%) were male. Additional available demographic data are given in the following tabulation:

Comorbid conditions were common, as seen in the following tabulation:

Data about the prevalence of hypertension were not gathered. The presumed cause of CHF was most often documented to be ischemia (45.3%), hypertension (17.3%), or toxicity (6.3%). A history of ventricular tachycardia or fibrillation was found in 16.1% of patients; 91.7% had a normal Glasgow Coma Scale score of 15. Of the 115 patients who did not have a normal Glasgow Coma Scale score, 60 patients (52.2%) had a score of 14; 13 (11.3%) had a score of 13; 21 (18.3%) had a score of 0; and 21 (18.3%) had scores ranging from 3 to 12. The admission physical examination reflected a population with the following multiple findings representing severe CHF: 78.5%, rales; 48.8%, elevated jugular venous pressure; and 57.0%, peripheral edema. Nonsinus rhythm was detected on an electrocardiogram in 28.0% of patients. On chest radiography, 25.0% of patients had signs of pulmonary edema, and 61.4% had cardiomegaly. Median Acute Physiology Score was 24 (16, 33).16,33 Of the 509 patients (36.6%) who had such information recorded in the chart, median left ventricular ejection fraction was 20% (15%, 29%) (Table 1). Medications used before study admission are presented in the following tabulation:

During study admission, 304 patients (21.9%) received intravenous non–digitalis inotropic medication. Before study entry, most patients were independent in their daily activities; 2 weeks before hospitalization, the median number of ADL dependencies was 0 (0, 2 [n=1136]), and the median DASI score was 16.5 (13.5, 21.0 [n=1148]). A typical patient with a DASI score of 16 would be able to walk indoors around the house and perform light work such as dusting and washing dishes but be unable to walk a block on level ground or climb a flight of stairs. The median probability of surviving 60 and 180 days as estimated by each patient's own physician was 84% (78%, 89%) and 74% (65%, 81%), respectively.

MEDICAL OUTCOMES AND RESOURCE USE

Median length of hospital stay was 8 (5, 12) days. Median TISS score was 13 (9, 18 [n=1365]). A typical patient with a TISS score of 13 would have, during 24 hours, a central vein catheter, chronic heparin infusion, additional scheduled intravenous medication, active diuresis for fluid overload, oxygen via nasal cannula, continuous electrocardiographic monitoring, vital sign checks every 2 hours, urinary catheter, and standard input and output measurement. The median cost of hospital care per person during the index admission was $6275 ($3468, $13366 [n=1303]). During the study admission, 239 patients (17.2%) had a do-not-resuscitate order documented in the chart. Six hundred nine patients (43.8%) had been in intensive care units. Median length of stay in an intensive care unit for these patients was 4 (3, 7) days.

Whereas 1299 patients (93.4%) survived their hospital stay, survival decreased to 1255 (90.3%) at 30 days, 1165 (83.8%) at 60 days, 1013 (72.9%) at 180 days, and 855 (61.5%) at 1 year. Patients who were discharged or died within 48 hours of study entry were not included in these analyses in accordance with study exclusion criteria. Of the 1279 patients who survived the index admission and had information available regarding disposition after discharge, 1184 (92.6%) returned home. The remaining patients were discharged to a nursing home (40 [3.1%]), a hospice program (6 [0.5%]), a rehabilitation hospital (29 [2.3%]), or another acute care hospital (20 [1.6%]).

HRQL OUTCOMES

Overall quality of life as assessed by patients (or their surrogates, if patient data were incomplete or missing) was reported to be good, very good, or excellent in 397 (35.7%) of 1112 patients at study admission, 447 (49.3%) of 907 patients 60 days after the index admission, and 442 (58.2%) of 760 patients 180 days after the index admission (Table 2). At study admission (phase I only), 60 days, and 180 days, median patient-rated health values were 54 (49, 70 [n=549]), 60 (50, 75 [n=869]), and 60 (50, 80 [n=734]), respectively. Frequencies of health rating values are presented in Table 2. Median numbers of months of excellent health patients were willing to accept rather than live a full year in their current state of health were 10 (7.5, 12) at study admission (n=562, phase I), 11 (9.3, 12) at 60 days (n=665), and 1110,12 at 180 days (n=615). The time−tradeoff utility can be calculated as follows at study admission: 10/12 (7.5/12, 12/12) or 0.83 (0.63, 1.00). More than one third of the patients (35.9% at 60 days and 37.6% at 180 days) were unwilling to give up any time in their current health state to live a shorter time in excellent health (Table 2). The frequency distribution of dependencies of ADL presented in Table 2 shows that 59.7% of patients with available information were independent in their ADL throughout 180 days of follow-up, with a median of 0 (0, 2 [n=909]) at 60 days and 0 (0, 1 [n=767]) at 180 days. Median SIP score was 16.3 (8.6, 26.2) at 60 days after study admission (n=620).

CHANGE OF HRQL IN TIME

Change of HRQL in time among patients depends on the following factors: (1) HRQL of individual patients may change; (2) change of HRQL of the group may be influenced by missing values; and (3) change may be due to chance.

Change of HRQL measurement values among the patients with available data at all 3 times is presented in Table 3. Health perceptions among the patients with available interview data improved at 60 and 180 days after acute exacerbation of severe CHF. We did not detect change in functional capacity as measured by the Index of ADL.

Table 4 presents how missing data influence the change of HRQL of the patients hospitalized for acute exacerbation of severe CHF. Patients with worse functional capacity (higher Index of ADL) at admission or at 60 days after hospitalization were more likely to die. There was a nonsignificant trend for worse health perceptions to be related to higher mortality rates throughout the study. At 60 days, lower time−tradeoff utility and worse overall quality of life were significantly (P≤.003) related to higher mortality rates. Patients who survived the interval (from admission to 60 days or from 60 to 180 days) and did not complete the interview after did not differ significantly by HRQL outcomes (measured in the previous interval) from patients who completed the interview.

COMMENT

Patients hospitalized for an acute exacerbation of severe CHF have a generally poor prognosis for survival and have substantial resource consumption; however, survivors have relatively good functional status and health perceptions. The knowledge that HRQL, particularly functional status, is relatively preserved among survivors of this population may be important to the patient and the health care provider for making health care decisions. Health perceptions (as assessed by general health rating, overall quality of life, and time−tradeoff utility) improve among survivors after acute exacerbation of CHF. Our study demonstrates that HRQL is measurable for large numbers of patients hospitalized with severe CHF and provides baseline HRQL data and change of HRQL in time for this population.

We found 90-day and 1-year survival to be 80.8% and 61.5%, respectively. The Framingham Heart Study16 evaluated survival data from diagnosis of clinical CHF (not related to hospitalization, data from 1950s-1980s) and found, for women and men, 90-day survival to be 72% and 73%, respectively, and 1-year survival to be 64% and 57%, respectively. Surprisingly, survival appears to be similar in the Framingham Heart Study and SUPPORT, despite very different inclusion criteria. Improved medical management of CHF is a possible explanation for the similar survival rates.

The SUPPORT patients remained relatively independent in their daily living; at 6 months, 59.7% of patients with complete data were independent in their basic activities of daily living and 15.8% were dependent in only 1 activity. We did not detect a change in functional capacity in time. This may have been related to the fact that the study admission baseline interview assessed patients' ADL status 2 weeks before hospital admission, so a possible change between in-hospital and postdischarge ADL status could have been missed.

Sixty days after study admission, patients in our study had a median SIP score of 16.3. By comparison, ambulatory patients with chronic stable angina (n=389; mean age, 60.4 years) had better perceived health status with a mean SIP score of 10.5.64 In another study, 6 months after discharge from an intensive care unit, 69 patients had an average SIP score of 10.7.65

In our study, 66.3% (at 60 days) and 59.8% (at 6 months) of the analyzed patients with severe CHF rated their health at 70 or lower, with the mean score of 61.6 at 60 days and 63.7 at 180 days. Survivors of myocardial infarction (n=80; mean age, 59.9 years) with left ventricular ejection fraction of less than 40% and New York Heart Association class I to III had mean health ratings ranging from 68 to 70.66 A random sample of the general population ages 55 to 74 years had a mean health rating of 75.1 (n=753).67 Stewart et al57 reported health perceptions of 11186 ambulatory patients (mean age, 47 years) on a scale of 0 to 100; 52% had scores of 70 or lower (mean=63.0; SD=26.8). Mean health perception scores (scale, 0-100) have been reported to be 74.6 in the general population (n=2008) in the Medical Outcomes Study57 and 59.2 in ambulatory patients with CHF (n=297).14 Although those studies14,57 used a slightly different method,57 the comparison suggests that health perceptions of our study patients may be somewhat lower than those of the general population but similar to perceptions found among ambulatory patients with CHF.

In our study, 35.7% (at admission), 49.3% (at 60 days), and 58.2% (at 180 days) of patients with complete data rated their overall quality of life as excellent, very good, or good. By contrast, of 934 patients with severe multivessel coronary artery disease (mean age, 62 years), 70% rated their overall health as excellent, very good, or good.68

Mean time−tradeoff utility scores for patients with CHF in SUPPORT were 0.76, 0.83, and 0.84 (at study admission, at 60 days, and at 180 days, respectively), which is comparable to the results among patients with milder CHF.49,66 Survivors of myocardial infarction (n=80; mean age, 59.9 years) with left ventricular ejection fraction of less than 40% (New York Heart Association class, I-III) had a mean time−tradeoff score of 0.87, which corresponds to 10.4 months in our study.66 The mean time−tradeoff score was 0.88 and did not change during the 112 years of follow-up in survivors of myocardial infarction.66 A random sample of the general population ages 55 to 74 years had a mean time-tradeoff score of 0.85 (n=738).67

Health perceptions (health rating, overall quality of life, and time−tradeoff utility) improved among survivors after acute exacerbation of CHF. This could be a reflection of recovering health status from an acute event or an improvement from a previously stable but lower level of health perception.

The Studies of Left Ventricular Dysfunction15 and Department of Veterans Affairs Cooperative Vasodilator–Heart Failure Trial II19 were 2 large clinical trials finding no substantial differences in HRQL measurements among patients receiving therapies for CHF previously shown to improve survival. Other studies17,18,6971 have found differences in HRQL of patients with CHF receiving different therapies.

Missing data are a common problem when using survey methods to measure HRQL.15,19,38,57 Consistent with other studies,15,38,57 we found that living patients who failed to complete the admission interviews were older (median age, 71 vs 66 years; P=.001 [Wilcoxon 2-sample test]), had worse Acute Physiology Scores (median score, 31 vs 28; P<.001 [Wilcoxon 2-sample test]), and had lower 180-day survival (67% vs 77%; P<.001 [χ2 test]). Most studies15,19,38,57,69 excluded patients with missing or incomplete data from analyses. This practice may create biased samples. To minimize bias, Stewart et al57 suggested imputation from other information. As described in the "Subjects and Methods" section, we substituted HRQL data to increase the available sample size and to decrease possible bias associated with the correlation of disease severity and missing data.

It is often difficult to compare HRQL of patients with CHF across studies because there is no agreement about strict criteria for CHF, and because the HRQL measures used are not always the same. The instruments used in this study (DASI, SIP, Index of ADL, general health status scales, and health utility) have been shown previously to be valid and reliable.14,45,5155,5759 The study population, however, was limited to patients with severe CHF. We do not know whether outcomes would be different in patients with less severe disease. In addition, only 5 large teaching hospitals participated in the study; therefore, the results may not be generalizable to patients seen in smaller or nonteaching hospitals or nursing homes or to patients with exacerbation of CHF who are not hospitalized. The racial distribution of the study patients, however, is similar to that of the general US population.72 A recent population-based study73 suggests that patients who were enrolled in SUPPORT tended to be younger and male, had fewer ADL impairments, and experienced lower mortality rates compared with patients with similar severity of disease from the same geographical area who were not enrolled into the study.

Our study provides insight into hospital resource use, HRQL, change of HRQL in time, and survival of a large patient population hospitalized for acute exacerbation of severe CHF. These data demonstrate that patients hospitalized with acute exacerbation of severe CHF have a generally poor prognosis for survival during the ensuing 6 months, but survivors have relatively good functional status and health perceptions. Furthermore, the health perceptions improve among survivors after acute exacerbation of CHF. Patients with worse functional capacity are more likely to die, however. The results of our study are more generalizable to those (generally younger) patients who receive a more aggressive approach (including hospitalization) for exacerbation of CHF.

Back to top
Article Information

Accepted for publication September 30, 1997.

Supported by the Robert Wood Johnson Foundation, Princeton, NJ.

The opinions and findings contained in this article are those of the authors and do not necessarily represent the views of the Robert Wood Johnson Foundation or its Board of Trustees.

Presented at the Society of General Internal Medicine National Meeting, Washington, DC, May 2, 1996.

Alfred F. Connors, Jr, MD, and Neal V. Dawson, MD, MetroHealth Medical Center, Cleveland, Ohio; Norman A. Desbiens, MD, Marshfield (Wis) Medical Research Foundation; William J. Fulkerson, Jr, MD, Duke University Medical Center, Durham, NC; Lee Goldman, MD, MPH, Beth Israel Hospital, Boston, Mass; William A. Knaus, MD, George Washington University Medical Center, Washington, DC; Joanne Lynn, MD, Dartmouth Medical School, Hanover, NH; and Robert K. Oye, MD, University of California at Los Angeles Medical Center.

National Coordinating Center

William A. Knaus, MD, George Washington University Medical Center, Washington, DC, and Joanne Lynn, MD, Dartmouth Medical School, Hanover, NH (co–principal investigators); Marilyn Bergner, PhD (deceased), and Anne Damiano, ScD, Johns Hopkins University, Baltimore, Md; Rosemarie Hakim, PhD, George Washington University Medical Center, Donald J. Murphy, MD, Presbyterian-St Lukes Medical Center, Denver, Colo; Joan Teno, MD, and Beth Virnig, PhD, Dartmouth Medical School; Douglas P. Wagner, PhD, George Washington University Medical Center; and Albert W. Wu, MD, MPH, and Yutaka Yasui, PhD, Johns Hopkins University (coinvestigators); Detra K. Robinson, MA, George Washington University Medical Center (chart abstraction supervisor); Barbara Kreling, BA, George Washington University Medical Center (survey coordinator); Jennie Dulac, BSN, RN, Dartmouth Medical School (intervention implementation coordinator); Rose Baker, MSHyg, George Washington University Medical Center (database manager); and Sam Holayel, BS, Thomas Meeks, BA, Mazen Mustafa, MS, and Juan Vegarra, BS (programmers).

National Statistical Center, Duke University Medical Center, Durham, NC

Carlos Alzola, MS, and Frank E. Harrell, Jr, PhD.

Beth Israel Hospital, Boston, Mass

Lee Goldman, MD, MPH (principal investigator); E. Francis Cook, ScD, Mary Beth Hamel, MD, Lynn Peterson, MD, Russell S. Phillips, MD, Joel Tsevat, MD, Lachlan Forrow, MD, Linda Lesky, MD, and Roger Davis, ScD (coinvestigators); Nancy Kressin, MS, and Jeanmarie Solzan, BA (interview supervisors); Ann Louise Puopolo, BSN, RN (chart abstractor supervisor); Laura Quimby Barrett, BSN, RN, Nora Bucko, BSN, RN, Deborah Brown, MSN, RN, Maureen Burns, BSN, RN, Cathy Foskett, BSN, RN, Amy Hozid, BSN, RN, Carol Keohane, BSN, RN, Colleen Martinez, BSN, RN, Dorcie McWeeney, BSN, RN, Debra Melia, BSN, RN, Shelley Otto, MSN, RN, Kathy Sheehan, BSN, RN, Alice Smith, BSN, RN, and Lauren Tofias, MS, RN (chart abstractors); Bernice Arthur, BA, Carol Collins, BA, Mary Cunnion, BA, Deborah Dyer, BA, Corinne Kulak, BS, Mary Michaels, BA, Maureen O'Keefe, BA, Marian Parker, AB, MBA, Lauren Tuchin, BA, Dolly Wax, BA, and Diana Weld, BA (interviewers); Liz Hiltunen, MS, RN, CS, Georgie Marks, MS, MEd, RN, Nancy Mazzapica, MSN, RN, and Cindy Medich, MS, RN (SUPPORT nurse clinicians); and Jane Soukup, MS (analyst/data manager).

Duke University Medical Center, Durham, NC

William J. Fulkerson, Jr, MD (principal investigator); Robert M. Califf, MD, Anthony N. Galanos, MD, Peter Kussin, MD, and Lawrence H. Muhlbaier, PhD (coinvestigators); Maria Winchell, MS (project director); Lee Mallatratt, RN (chart abstractor supervisor); Ella Akin, BA (interviewer supervisor); Lynne Belcher, RN, Elizabeth Buller, BSN, RN, Eileen Clair, RN, Laura Drew, BSN, RN, Libby Fogelman, BSN, RN, Dianna Frye, BSN, RN, Beth Fraulo, BSN, RN, Debbie Gessner, BSN, RN, Jill Hamilton, BSN, RN, Kendra Kruse, BSN, RN, Dawn Landis, BSN, RN, Louise Nobles, BSN, RN, Rene Oliverio, BSN, RN, and Carroll Wheeler, BSN, RN (chart abstractors); Nancy Banks, MA, Steven Berry, BA, Monie Clayton, Patricia Hartwell, MAT, Nan Hubbard, Isabel Kussin, BA, Barbara Norman, BA, Jackie Noveau, BSN, Heather Read, BA, and Barbara Warren, MSW (interviewers); Jane Castle, MSN, RN, Beth Fraulo, BSN, RN, Rene Oliverio, BSN, RN, and Kathy Turner, MSN, RN (SUPPORT nurse clinicians); and Rosalie Perdue (data manager).

MetroHealth Medical Center, Cleveland, Ohio

Alfred F. Connors, Jr, MD, and Neal V. Dawson, MD (co–principal investigators); Claudia Coulton, PhD, C. Seth Landefeld, MD, Theodore Speroff, PhD, and Stuart Youngner, MD (coinvestigators); Mary J. Kennard, MSN, and Mary Naccaratto, MSN (chart abstractor supervisors); Mary Jo Roach, PhD (interviewer supervisor); Maria Blinkhorn, RN, Cathy Corrigan, RNC, Elsie Geric, RN, Laura Haas, RN, Jennifer Harn, RN, Julie Jerdonek, RN, Marilyn Landy, RN, Elaine Marino, RN, Patti Olesen, RN, Sherry Patzke, RN, Linda Repas, RN, Kathy Schneeberger, RN, Carolyn Smith, RN, Colleen Tyler, RN, and Mary Zenczak, RN (chart abstractors); Helen Anderson, BA, Pat Carolin, Cindy Johnson, BA, Pat Leonard, BA, Judy Leuenberger, Linda Palotta, BA, and Millie Warren (interviewers); Jane Finley, RN, Toni Ross, RN, Gillian Solem, MSN, and Sue Zronek, RN (SUPPORT nurse facilitators); and Sara Davis, BS (data manager).

Marshfield Medical Research Foundation/St Joseph's Hospital, Marshfield, Wis

Norman A. Desbiens, MD (principal investigator); Steven Broste, MS, and Peter Layde, MD, MSc (co–principal investigators); Michael Kryda, MD, Douglas J. Reding, MD, and Humberto J. Vidaillet, Jr, MD (coinvestigators); Marilyn Follen, RN, MSN (project manager and chart abstractor supervisor); Patsy Mowery, BBA (interviewer supervisor); Barbara E. Backus, Debra L. Kempf, BSN, Jill M. Kupfer, Karen E. Maassen, LPN, Jean M. Rohde, LPN, Nancy L. Wilke, and Sharon M. Wilke, LPN (chart abstractors); Elizabeth A. Albee, BA, Barbara Backus, Angela M. Franz, BS, Diana L. Henseler, Juanita A. Herr, Irene Leick, Carol L. Lezotte, BS, and Laura Meddaugh (interviewers); Linda Duffy, RN, MSN, Debrah Johnson, RN, BSN, Susan Kronenwetter, RN, BSN, and Anne Merkel, RN, BSN (SUPPORT nurse facilitators).

University of California at Los Angeles Medical Center

Robert K. Oye, MD (principal investigator); Paul E. Bellamy, MD (co–principal investigator); Jonathan Hiatt, MD, and Neil S. Wenger, MD, MPH (coinvestigators); Margaret Leal-Sotelo, MSW (project director and interviewer supervisor); Darice Moranville-Hawkins, RN, MN, Patricia Sheehan, RN, Diane Watanabe, MS, and Myrtle C. Yamamoto, RN (chart abstractor supervisors); Allison Adema, RN, Ellen Adkins, RN, Ann Marie Beckson, RN, Mona Carter, RN, Ellen Duerr, RN, Ayam El-Hadad, RN, MN, Ann Farber, RN, MA, Ann Jackson, RN, John Justice, RN, and Agnes O'Meara, RN (chart abstractors); Lee Benson, Lynette Cheney, Carlo Medina, and Jane Moriarty (interviewers); Kay Baker, RN, MN, Cleine Marsden, RN, MN, and Kara Watne, RN, MPH (clinical nurse liaisons); and Diane Goya, MA (data manager).

Steering Committee

Alfred F. Connors, Jr, MD (chair), Norman Desbiens, MD, William J. Fulkerson, MD, Frank E. Harrell, Jr, PhD, William A. Knaus, MD, Joanne Lynn, MD, Robert K. Oye, MD, and Russell S. Phillips, MD.

National Advisory Committee

Charles C. J. Carpenter, MD (chair), Brown University/The Miriam Hospital, Providence, RI; Ronald A. Carson, PhD, University of Texas, Galveston; Don E. Detmer, MD, University of Virginia, Charlottesville; Donald E. Steinwachs, PhD, The Johns Hopkins University, Baltimore, Md; Vincent Mor, PhD, Brown University; Robert A. Harootyan, MS, MA, American Association of Retired Persons, Washington, DC; Alex Leaf, MD, Massachusetts General Hospital, Boston; Rosalyn Watts, EdD, RN, University of Pennsylvania, Philadelphia; Sankey Williams, MD, Hospital of the University of Pennsylvania; and David Ransohoff, MD, University of North Carolina at Chapel Hill.

Reprints: Neal V. Dawson, MD, Department of Medicine, MetroHealth Medical Center, 2500 MetroHealth Dr, Cleveland, OH 44109-1998.

References
1.
Ho  KKLPinsky  JLKannel  WBLevy  D The epidemiology of heart failure: the Framingham study. J Am Coll Cardiol. 1993;22 (suppl A) 6A- 13AArticle
2.
Schocken  DDArrieta  MILeaverton  PERoss  EA Prevalence and mortality rate of congestive heart failure in the United States. J Am Coll Cardiol. 1992;20301- 306Article
3.
Ghali  JKCooper  RFord  E Trends in hospitalization rates for heart failure in the United States, 1973-1986: evidence for increasing population prevalence. Arch Intern Med. 1990;150769- 773Article
4.
Doval  HCNul  DRGrancelli  HOPerrone  SVBortman  GRCuriel  R Randomized trial of low-dose amiodarone in severe congestive heart failure. Lancet. 1994;344493- 498Article
5.
Kennedy  HLBrooks  MMBarker  AH  et al.  Beta-blocker therapy in the cardiac arrhythmia suppression trial. Am J Cardiol. 1994;74674- 680Article
6.
The Acute Infarction Ramipril Efficacy (AIRE) Study Investigators, Effect of ramipril on mortality and morbidity of survivors of acute myocardial infarction with clinical evidence of heart failure. Lancet. 1993;342821- 828
7.
Bourassa  MGGurne  OBangdiwala  SI  et al.  Natural history and patterns of current practice in heart failure. J Am Coll Cardiol. 1993;22 (suppl A) 14A- 19AArticle
8.
The SOLVD Investigators, Effect of enalapril on mortality and the development of heart failure in asymptomatic patients with reduced left ventricular ejection fraction. N Engl J Med. 1992;327685- 691Article
9.
The SOLVD Investigators, Effect of enalapril on survival in patients with reduced left ventricular ejection fractions and congestive heart failure. N Engl J Med. 1991;325293- 302Article
10.
Eichhorn  EJTandon  PKDiBianco  R  et al.  Clinical and prognostic significance of serum magnesium concentration in patients with severe chronic congestive heart failure: the PROMISE study. J Am Coll Cardiol. 1993;21634- 640Article
11.
Packer  MCarver  JRRodeheffer  RJ  et al.  Effect of oral milrinone on mortality in severe chronic heart failure. N Engl J Med. 1991;3251468- 1475Article
12.
Pfeffer  MABraunvald  EMoyé  LA  et al.  Effect of captopril on mortality and morbidity in patients with left ventricular dysfunction after myocardial infarction. N Engl J Med. 1992;327669- 677Article
13.
Jaeger  AAHlatky  MAPaul  SMGortner  SR Functional capacity after cardiac surgery in elderly patients. J Am Coll Cardiol. 1994;24104- 108Article
14.
Stewart  ALGreenfield  SHays  RD  et al.  Functional status and well-being of patients with chronic conditions: results from the medical outcomes study. JAMA. 1989;262907- 913Article
15.
Rogers  WJJohnstone  DEYusuf  S  et al.  Quality of life among 5025 patients with left ventricular dysfunction randomized between placebo and enalapril: the studies of left ventricular dysfunction. J Am Coll Cardiol. 1994;23393- 400Article
16.
Ho  KKLAnderson  KMKannel  WBGrossman  WLevy  D Survival after the onset of congestive heart failure in Framingham Heart Study subjects. Circulation. 1993;88107- 115Article
17.
Cowley  AJSkene  AM Treatment of severe heart failure: quantity or quality of life? a trial of enoximone. Br Heart J. 1994;72226- 230Article
18.
Seneviratne  BMoore  GAWest  PD Effect of captopril on functional mitral regurgitation in dilated heart failure: a randomized double blind placebo controlled trial. Br Heart J. 1994;7263- 68Article
19.
Rector  TSJohnson  GDunkman  B  et al.  Evaluation by patients with heart failure of the effects of enalapril compared with hydralazine plus dinitrate on quality of life: V-HeFT II. Circulation. 1993;87 (suppl VI) VI71- VI77
20.
Stevenson  WGMiddlekauff  HRStevenson  LWSaxon  LAWoo  MAMoser  D Significance of aborted cardiac arrest and sustained ventricular tachycardia in patients referred for treatment therapy of advanced heart failure. Am Heart J. 1992;124123- 130Article
21.
Fonarow  GCChelimsky-Fallick  CStevenson  LW  et al.  Effect of direct vasodilation with hydralazine versus angiotensin-converting enzyme inhibition with captopril on mortality in advanced heart failure: the Hy-C trial. J Am Coll Cardiol. 1992;19842- 850Article
22.
White  MRouleau  JLRuddy  TDDeMarco  TMoher  DChatterjee  K Decreased coronary sinus oxygen content: a predictor of adverse prognosis in patients with severe congestive heart failure. J Am Coll Cardiol. 1991;181631- 1637Article
23.
Keogh  AMFreund  JBaron  DWHickie  JB Timing of cardiac transplantation in idiopathic dilated cardiomyopathy. Am J Cardiol. 1988;61418- 422Article
24.
The CONSENSUS Trial Study Group, Effects of enalapril on mortality in severe congestive heart failure. N Engl J Med. 1987;3161429- 1435Article
25.
Kelly  TLCremo  RNielsen  CShabetai  R Prediction of outcome in late-stage cardiomyopathy. Am Heart J. 1990;1191111- 1121Article
26.
Franciosa  JAWilen  MZiesche  SCohn  JN Survival in men with severe chronic left ventricular failure due to either coronary heart disease or idiopathic dilated cardiomyopathy. Am J Cardiol. 1983;51831- 836Article
27.
Keogh  AMBaron  DWHickie  JB Prognostic guides in patients with idiopathic or ischemic dilated cardiomyopathy assessed for cardiac transplantation. Am J Cardiol. 1990;65903- 908Article
28.
Middlekauff  HRStevenson  WGStevenson  LW Prognostic significance of atrial fibrillation in advanced heart failure: a study of 390 patients. Circulation. 1991;8440- 48Article
29.
Anderson  BWaagstein  F Spectrum and outcome of congestive heart failure in a hospitalized population. Am Heart J. 1993;126632- 640Article
30.
Smith  RFJohnson  GZiesche  SBhat  GBlankenship  KCohn  JN Functional capacity in heart failure: comparison of methods for assessment and their relation to other indexes of heart failure. Circulation. 1993;87 (suppl VI) VI88- VI93
31.
Wegner  NKMattson  MEFurberg  CDElinson  J Assessment of quality of life in clinical trials of cardiovascular therapies. Am J Cardiol. 1984;54908- 913Article
32.
Guyatt  GH Measurement of health-related quality of life in heart failure. J Am Coll Cardiol. 1993;22 (suppl A) 185A- 191AArticle
33.
Burns  RBMcCarthy  EPMoskowitz  MA  et al.  Outcomes for older men and women with congestive heart failure. J Am Geriatr Soc. 1997;45276- 280
34.
Murphy  DJCluff  LE SUPPORT: Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments: study design. J Clin Epidemiol. 1990;43 (suppl) 1S- 123SArticle
35.
Hamel  MBGoldman  LTeno  J  et al.  Identification of comatose patients at high risk for death or severe disability: SUPPORT investigators: Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatment. JAMA. 1995;2731842- 1848Article
36.
Covinsky  KEGoldman  LCook  EF  et al.  The impact of serious illness on patients' families: SUPPORT investigators: Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatment. JAMA. 1994;2721839- 1844Article
37.
Knaus  WAHarrell  FE  JrLynn  J  et al.  The SUPPORT prognostic model: objective estimates of survival for seriously ill hospitalized adults: Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatment. Ann Intern Med. 1995;122191- 203Article
38.
Tsevat  JCook  EFGreen  ML  et al.  Health values of the seriously ill. Ann Intern Med. 1995;122514- 520Article
39.
Phillips  RSWenger  NSTeno  J  et al.  Choices of seriously ill patients about cardiopulmonary resuscitation: correlates and outcomes. Am J Med. 1996;100128- 137Article
40.
Murphy  DJKnaus  WALynn  J Study population in SUPPORT: patients (as defined by disease categories and mortality projections), surrogates, and physicians. J Clin Epidemiol. 1990;43 (suppl) 11S- 28SArticle
41.
Phillips  RSKnaus  WA Patient characteristics in SUPPORT: sociodemographics, admission diagnosis, co-morbidities and acute physiology score. J Clin Epidemiol. 1990;43 (suppl) 29S- 31SArticle
42.
Phillips  RSGoldman  LBergner  M Patient characteristics in SUPPORT: activity status and cognitive function. J Clin Epidemiol. 1990;43 (suppl) 33S- 36SArticle
43.
Oye  RKLandefeld  CSJayes  RL Outcomes in SUPPORT. J Clin Epidemiol. 1990;43 (suppl) 83S- 87SArticle
44.
Landefeld  CSPhillips  RSBergner  M Patient characteristics in SUPPORT: functional status. J Clin Epidemiol. 1990;43 (suppl) 37S- 39SArticle
45.
Tsevat  JDawson  NVMatchar  DB Assessing quality of life and preferences in the seriously ill using utility theory. J Clin Epidemiol. 1990;43 (suppl) 73S- 77SArticle
46.
Kreling  BRobinson  DKBergner  M Data collecting strategies in SUPPORT. J Clin Epidemiol. 1990;43 (suppl) 5S- 9SArticle
47.
Phillips  RSMurphy  DJGoldman  LKnaus  WA Patient characteristics in SUPPORT: disease specific clinical data. J Clin Epidemiol. 1990;43 (suppl) 41S- 45SArticle
48.
Knaus  WAWagner  DPDraper  EA  et al.  APACHE III. Crit Care Med. 1989;17 (suppl 12) S176- S221Article
49.
Knaus  WAWagner  DPDraper  EA  et al.  APACHE III prognostic system: risk prediction of hospital mortality for critically ill hospitalized adults. Chest. 1991;1001619- 1636Article
50.
Teasdale  GMurray  GParker  LJennett  B Adding up the Glasgow Coma Score. Acta Neurochir Suppl (Wien). 1979;28 (1) 13- 16
51.
Hlatky  MABoineau  REHigginbotham  MB  et al.  A brief self-administered questionnaire to determine functional capacity (the Duke Activity Status Index). Am J Cardiol. 1989;64651- 654Article
52.
Nelson  CLHerndon  JEMark  DBPryor  DBCaliff  RMHlatky  MA Relation of clinical and angiographic factors to functional capacity as measured by the Duke Activity Status Index. Am J Cardiol. 1991;68973- 975Article
53.
Bergner  MBobbitt  RACarter  WBGilson  BS The Sickness Impact Profile: development and final revision of a health status measure. Med Care. 1981;19787- 805Article
54.
Katz  SFord  ABMoskowitz  RWJackson  BAJaffe  W Studies of illness in the aged: the index of ADL: a standardized measure of biological and psychosocial function. JAMA. 1963;185914- 919Article
55.
Katz  SAkpom  CA A measure of primary sociobiological function. Int J Health Serv. 1976;6493- 508Article
56.
Guyatt  GHFeeny  DHPatrick  DL Measuring health-related quality of life. Ann Intern Med. 1993;118622- 629Article
57.
Stewart  ALHays  RDWare  JE The MOS Short-term General Health Survey: reliability and validity in a patient population. Med Care. 1988;26724- 735Article
58.
Revicki  DAKaplan  RM Relationship between psychometric and utility-based approaches to the measurement of health-related quality of life. Qual Life Res. 1993;2477- 487Article
59.
Tsevat  JGoldman  LLamas  GA  et al.  Functional status versus utilities in survivors of myocardial infarction. Med Care. 1991;291153- 1159Article
60.
Cullen  DJCivetta  JMBriggs  BAFerrara  LC Therapeutic intervention scoring system: a method for quantitative comparison of patient care. Crit Care Med. 1974;257- 60Article
61.
Keene  ARCullen  DJ Therapeutic intervention scoring system: update 1983. Crit Care Med. 1983;111- 3Article
62.
Teno  JMHakim  RBKnaus  WA  et al.  Preferences for cardiopulmonary resuscitation: physician-patient agreement and hospital resource use: the SUPPORT investigators. J Gen Intern Med. 1995;10179- 186Article
63.
Wu  AWDamiano  AMLynn  J  et al.  Predicting future functional status for seriously ill hospitalized adults: the SUPPORT prognostic model. Ann Intern Med. 1995;122342- 350Article
64.
Fletcher  AMcLoone  PBulpitt  C Quality of life on angina therapy: a randomized controlled trial of transdermal glyceryl trinitrate against placebo. Lancet. 1988;24- 7Article
65.
Miranda  DR Quality of life after cardiopulmonary resuscitation. Chest. 1994;106524- 530Article
66.
Tsevat  JGoldman  LSoukup  JR  et al.  Stability of time-tradeoff utilities in survivors of myocardial infarction. Med Decis Making. 1993;13161- 165Article
67.
Fryback  DGDasbach  EJKlein  R  et al.  The Beaver Dam Health Outcomes Study: initial catalog of health-state quality factors. Med Decis Making. 1993;1389- 102Article
68.
Hlatky  MACharles  EDNobrega  F  et al.  Initial functional and economic status of patients with multivessel coronary artery disease randomized in the bypass angioplasty revascularization investigation (BARI). Am J Cardiol. 1995;7534C- 41CArticle
69.
Kubo  SHGollub  SBourge  R  et al.  Beneficial effects of pimobendan on exercise tolerance and quality of life in patients with heart failure: results of a multicenter trial. Circulation. 1992;85942- 949Article
70.
Rector  TSCohn  JN Assessment of patient outcome with the Minnesota Living With Heart Failure questionnaire: reliability and validity during a randomized, double-blind, placebo-controlled trial of pimobendan. Am Heart J. 1992;1241017- 1027Article
71.
Rector  TSKubo  SHCohn  JN Validity of the Minnesota Living With Heart Failure questionnaire as a measure of therapeutic response to enalapril or placebo. Am J Cardiol. 1993;711106- 1107Article
72.
US Bureau of the Census, Statistical Abstract of the United States: 1994. 114th ed. Washington, DC US Bureau of the Census1994;
73.
Layde  PMBroste  SKDesbiens  N  et al.  Generalizability of clinical studies conducted at tertiary care medical centers: a population-based analysis. J Clin Epidemiol. 1996;49835- 841Article
×