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Figure 1. 
Kaplan-Meier survival curve of patients after cardiopulmonary resuscitation (CPR). Patients were analyzed when advanced life support was successful. The first rapid decline in survival occurred when in the intensive care unit for less than 48 hours.

Kaplan-Meier survival curve of patients after cardiopulmonary resuscitation (CPR). Patients were analyzed when advanced life support was successful. The first rapid decline in survival occurred when in the intensive care unit for less than 48 hours.

Figure 2. 
Sickness Impact Profiles of 3 groups of cardiopulmonary resuscitation patients. The scores of survivors after cardiopulmonary resuscitation at the intensive care unit were set to 0. A mean standard score of 0.20 can be taken to indicate a small deviation from the reference data, 0.50 a moderate deviation. Results show only small deviations in quality of life between the various study groups.

Sickness Impact Profiles of 3 groups of cardiopulmonary resuscitation patients. The scores of survivors after cardiopulmonary resuscitation at the intensive care unit were set to 0. A mean standard score of 0.20 can be taken to indicate a small deviation from the reference data, 0.50 a moderate deviation. Results show only small deviations in quality of life between the various study groups.

Figure 3. 
Sickness Impact Profiles of 3 different patient populations. The scores of the reference group of elderly individuals visiting the general practitioner were set to 0. A mean standard score of 0.20 can be taken to indicate a small deviation from the reference data, 0.50 a moderate deviation, and 0.80 a substantial deviation. CPR indicates cardiopulmonary resuscitation.

Sickness Impact Profiles of 3 different patient populations. The scores of the reference group of elderly individuals visiting the general practitioner were set to 0. A mean standard score of 0.20 can be taken to indicate a small deviation from the reference data, 0.50 a moderate deviation, and 0.80 a substantial deviation. CPR indicates cardiopulmonary resuscitation.

Table 1. 
Association of Patient Characteristics With Quality of Life After CPR*
Association of Patient Characteristics With Quality of Life After CPR*
Table 2. 
Independent Patient Characteristics Explaining Quality of Life After CPR*
Independent Patient Characteristics Explaining Quality of Life After CPR*
1.
Levy  DECoronna  JJBurton  HSLapinski  RHFrydman  HPlum  F Predicting outcome from hypoxic-ischemic coma.  JAMA. 1985;2531420- 1426Google ScholarCrossref
2.
Edgren  EHedstrand  UKelsey  SSutton-Tyrrell  KSafar  P Assessment of neurological prognosis in comatose survivors of cardiac arrest: BRCT I Study Group.  Lancet. 1994;3431055- 1059Google ScholarCrossref
3.
Stiell  IGHebert  PCWells  GA  et al.  The Ontario trial of active compression-decompression cardiopulmonary resuscitation for in-hospital and prehospital cardiac arrest.  JAMA. 1996;2751417- 1423Google ScholarCrossref
4.
Spilker  B Introduction. Spilker  Bed Quality of Life Assessment in Clinical Trials. New York, NY Raven Press1990;3- 10Google Scholar
5.
Bayer  AJAng  BCPathy  MS Cardiac arrests in a geriatric unit.  Age Ageing. 1985;14271- 276Google ScholarCrossref
6.
Bedell  SEDelbanco  TLCook  EFEpstein  FM Survival after cardiopulmonary resuscitation in the hospital.  N Engl J Med. 1983;309569- 576Google ScholarCrossref
7.
Longstreth  WTJInui  TSCobb  LACopass  MK Neurologic recovery after out-of-hospital cardiac arrest.  Ann Intern Med. 1983;98588- 592Google ScholarCrossref
8.
Bergner  LBBergner  MHallstrom  APEisenberg  MSCobb  LA Health status of survivors of out-of-hospital cardiac arrest six months later.  Am J Public Health. 1984;74508Google ScholarCrossref
9.
Reis Miranda  D Quality of life after cardiopulmonary resuscitation.  Chest. 1994;106524- 530Google ScholarCrossref
10.
Bergner  MBobitt  RACarter  WBGilson  BS The Sickness Impact Profile: development and final revision of a health status measure.  Med Care. 1981;19787- 805Google ScholarCrossref
11.
Folstein  MFFolstein  SEMcHugh  PR "Mini-Mental State:" a practical method for grading the cognitive state of patients for the clinician.  J Psychiatr Res. 1975;12189- 198Google ScholarCrossref
12.
Barnes  GECurrie  RFSegall  A Symptoms of depression in a Canadian urban sample.  Can J Psychiatry. 1988;33386- 393Google Scholar
13.
Radloff  LS The CES-D scale: A self-report depression scale for research in the general population.  Appl Psychol Measure. 1977;1385- 401Google ScholarCrossref
14.
Rankin  J Cerebral vascular accidents in patients over the age of 60, II: prognosis.  Scott Med J. 1957;2200- 215Google Scholar
15.
Jacobs  HLuttik  ATouw-Otten  FKastein  Mde Melker  R Measuring impact of sickness in patients with nonspecific abdominal complaints in a Dutch family practice setting.  Med Care. 1992;30244- 551Google ScholarCrossref
16.
de Haan  RJLimburg  Mvan der Meulen  JHJacobs  HAaronson  NK Quality of life after stroke: impact of stroke type and lesion location.  Stroke. 1995;26402- 408Google ScholarCrossref
17.
Altman  DG Practical Statistics for Medical Research.  New York, NY Chapman & Hall1991;
18.
Kleinbaum  DGKupper  LLMuller  EM Applied Regression Analysis and Other Multivariable Methods.  Belmont, Calif Duxbury Press1988;
19.
Hosmer  DWLemeshow  S Applied Logistic Regression.  New York, NY John Wiley & Sons Inc1989;
20.
Cohen  J Statistical Power Analysis for the Behavioral Sciences.  Orlando, Fla Academic Press Inc1977;
21.
Rozenbaum  EAShenkman  L Predicting outcome of inhospital cardiopulmonary resuscitation.  Crit Care Med. 1988;16583- 586Google ScholarCrossref
22.
Gulati  RSBhan  GLHoran  MA Cardiopulmonary resuscitation of old people.  Lancet. 1983;2267- 269Google ScholarCrossref
23.
Blackhall  LJZiogas  AAzen  SP Low survival rate after cardiopulmonary resuscitation in a county hospital.  Arch Intern Med. 1992;1522045- 2048Google ScholarCrossref
24.
Sack  JBKesselbrenner  MBBregman  D Survival from in-hospital cardiac arrest with interposed abdominal counterpulsation during cardiopulmonary resuscitation.  JAMA. 1992;267379- 385Google ScholarCrossref
25.
Madl  CGrimm  GKramer  L  et al.  Early prediction of individual outcome after cardiopulmonary resuscitation.  Lancet. 1993;341855- 858Google ScholarCrossref
26.
Vitelli  CCooper  KRogatko  ABrennan  M Cardiopulmonary resuscitation and the patient with cancer.  J Clin Oncol. 1991;9111- 115Google Scholar
27.
Landry  FJParker  JMPhillips  YY Outcome of cardiopulmonary resuscitation in the intensive care setting.  Arch Intern Med. 1992;1522305- 2308Google ScholarCrossref
28.
Murphy  DJMurray  AMRobinson  BECampion  EW Outcomes of cardiopulmonary resuscitation in the elderly.  Ann Intern Med. 1989;111199- 205Google ScholarCrossref
29.
DeBard  ML Cardiopulmonary resuscitation: analysis of six years' experience and review of the literature.  Ann Emerg Med. 1981;10408- 416Google ScholarCrossref
30.
Longstreth  WTJCobb  LAFahrenbruch  CECopass  MK Does age affect outcomes of out-of-hospital cardiopulmonary resuscitation?  JAMA. 1990;2642109- 2110Google ScholarCrossref
31.
Woog  RHTorzillo  PJ In-hospital cardiopulmonary resuscitation: prospective survey of management and outcome.  Anaesth Intensive Care. 1987;15193- 198Google Scholar
32.
Murphy  DJBurrows  DSantilli  S  et al.  The influence of the probability of survival on patients' preferences regarding cardiopulmonary resuscitation.  N Engl J Med. 1994;330545- 549Google ScholarCrossref
Original Investigation
February 8, 1999

Quality of Survival After Cardiopulmonary Resuscitation

Author Affiliations

From the Resuscitation Committee (Drs de Vos and Koster), the Departments of Medical Psychology (Dr de Haes), Cardiology (Dr Koster), and Clinical Epidemiology and Biostatistics (Dr de Haan), Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands.

Arch Intern Med. 1999;159(3):249-254. doi:10.1001/archinte.159.3.249
Abstract

Background  Outcome of cardiopulmonary resuscitation (CPR) can be poor, in terms of life expectancy and quality of life.

Objectives  To determine the impact of patient characteristics before, during, and after CPR on these outcomes, and to compare results of the quality-of-life assessment with published studies.

Methods  In a cohort study, we assessed by formal instruments the quality of life, cognitive functioning, depression, and level of dependence of survivors after in-hospital CPR. Follow-up was at least 3 months after discharge from the hospital (tertiary care center).

Results  Of 827 resuscitated patients, 12% (n = 101) survived to follow-up. Of the survivors, 89% participated in the study. Most survivors were independent in daily life (75%), 17% were cognitively impaired, and 16% had depressive symptoms. Multivariate regression analysis showed that quality of life and cognitive function were determined by 2 factors known before CPR—the reason for admission and age. Factors during and after resuscitation, such as prolonged cardiac arrest and coma, did not significantly determine the quality of life or cognitive functioning of survivors. The quality of life of our CPR survivors was worse compared with a reference group of elderly individuals, but better than that of a reference group of patients with stroke. The quality of life did not importantly differ between the compared studies of CPR survivors.

Conclusions  Cardiopulmonary resuscitation is frequently unsuccessful, but if survival is achieved, a relatively good quality of life can be expected. Quality of life after CPR is mostly determined by factors known before CPR. These findings may be helpful in informing patients about the outcomes of CPR.

CARDIOPULMONARY resuscitation (CPR) can only be called successful if patients survive and their quality of life is acceptable. Neurologic impairments caused by the cardiac arrest can be a threat to this quality of life.1-3

Quality of life comprises at least physical, psychological, and social functioning.4 All these dimensions have been described in relation to CPR separately,2,3,5-9 but not in relation to each other. In view of the risks of resuscitation, it is important to get an overall insight into the quality of life after CPR and how this relates to the procedure.

The objective of this study was to determine the outcomes of CPR in terms of quality of life and cognitive functioning, and to relate important patient characteristics before, during, and after CPR to these outcomes. We aimed to widen this perspective by comparing the quality of life between different groups of CPR survivors and between different patient populations as known from the literature.

Patients and methods

This study was carried out at the Academic Medical Center in Amsterdam, the Netherlands (tertiary care hospital, 1000 beds, 26,000 admissions per year). Cardiopulmonary resuscitation was defined as either the application of artificial ventilation and external chest compression or immediate defibrillation. Survivors were identified through the database of calls for the resuscitation team between May 1988 and August 1995, in which patient and procedure variables were prospectively entered. The team is routinely called on to all wards and the emergency department. The coronary care unit calls if the resuscitation exceeds a few defibrillator shocks.

We included all consecutive survivors (age ≥18 years) discharged from the hospital, including those with an out-of-hospital onset of cardiac arrest. Patients with a survival of at least 3 months were studied. The study was approved by the hospital medical ethics committee.

Assessment instruments

The quality of life was evaluated by physical, psychological, and social functioning. Cognitive functioning, depression, and dependence in daily life were assessed in depth. Questionnaires were selected by their psychometric properties and use in other CPR studies. The quality of life was measured with the 136-item self-reporting Sickness Impact Profile (SIP) with 12 subscales and 3 aggregated scores (physical, psychosocial, and overall health).10 The SIP scores range from 0 to 100; higher scores indicate a worse quality of life. Perceived quality of life was expressed by the patients on a visual analog scale ranging from 0 (worst) to 10 (best) as an answer to the question "How do you rate your quality of life over the past 14 days?" Cognitive functioning was assessed with the 30-item Mini-Mental State Examination (MMSE).11 Patients were classified as cognitively impaired at a cutoff value of 23 or less.12 Depression was measured with the 20-item self-reporting Center for Epidemiologic Studies Depression Scale. Patients had depressive symptoms at a cutoff value of 16 or more.13 Dependence in daily life was assessed with the 6-point observer-rated Rankin Scale.14 The categories are no symptoms (0); minor symptoms that do not interfere with lifestyle (1); symptoms that lead to some restriction in lifestyle but do not interfere with the patient's capacity to look after himself or herself (2); symptoms that prevent a totally independent existence (3); symptoms that clearly prevent independent existence although constant attention is not needed (4); and a totally dependent patient requiring constant attention night and day (5).

Quality of life in perspective

We compared the quality of life of our study group with that of similar populations of CPR survivors, but after out-of-hospital cardiac arrest and cardiac arrest at the intensive care unit.9,10 A population of elderly people visiting the general practitioner and an age-corrected subsample of patients with stroke15,16 served as reference groups to indicate where the quality-of-life outcomes CPR survivors can be positioned between 2 relatively extreme health states of patients who are about the same age.

Statistical analysis

The characteristics before, during, and after CPR were associated with mortality as well as with the quality of life after survival calculating a χ2 for nominal variables and using the Student t test or analysis of variance for continuous variables. In case of skewed data or ordinal categories, we used the Mann-Whitney or Kruskall-Wallis test. A P≤.05 was considered statistically significant. The probability of survival was calculated and presented by a Kaplan-Meier survival curve17 where patients were censored at the time of the interview. All clinical characteristics before, during, and after CPR were entered in multivariate linear regression models (forward selection) to assess the independent effect on the quality-of-life dimensions. The strength of the relationship was expressed in partially explained variances (partial R2). The total explained variance was calculated by summarizing the partial R2.18

The MMSE and Center for Epidemiologic Studies Depression Scale scores were considered dichotomous according to their cutoff value. All characteristics before, during, and after CPR were entered in logistic regression analysis models (forward selection) to identify their independent effect on cognitive impairment and depression. The effect sizes of significant characteristics were expressed as odds ratios (95% confidence intervals).19

To compare the quality of life of the study group with a reference group, SIP scores were converted to mean standard scores ([mean scores of the study group − mean scores of the reference group]/SD of the reference group).20 According to this method, the scores of the reference group were set at 0. Standard scores indicate the difference in SDs between the study and reference groups. Given the similarity with the effect size calculations, a mean standard score of 0.20 can be taken to indicate a small deviation from the reference data; 0.50, a moderate deviation; and 0.80, a substantial deviation.

Results

During the study period 827 patients underwent CPR, 385 patients initially survived, 162 (20%) survived to discharge, of whom 5 were in a vegetative state. Of the 51 patients who died after discharge, 29 died in the first 6 months (Figure 1). Of 5 patients who were in a vegetative state at discharge, 4 died within 3 months. Ten patients were lost to follow-up. Death after discharge was significantly associated with age 70 years or older (P =.05) and dependency in daily life before CPR (P =.05).

Of 101 survivors, 90 (89%) participated in the interview: 50 men and 40 women with a mean (SD) age of 64 (13) years. The median time from CPR to interview was 15 months (range, 3-72 months). Survivors who refused to participate stated that they were in good health (n = 4) or bad health (n = 4), or would not answer any questions on their current health (n = 3). Of the participating survivors, 41 (46%) had ventricular fibrillation as initial rhythm and 84 (93%) had a circulatory arrest of cardiac origin and 6 (7%) of respiratory origin. Of 84 patients with a circulatory arrest of cardiac origin, 30 (36%) experienced an arrest because of a myocardial infarction and 32 (38%) because of a primary rhythm disturbance. Other causes of arrest were a variety of cardiac conditions, such as disturbances of the myocardial conduction system and acute heart failure.

Various quality-of-life dimensions

All 90 patients completed the SIP, 4 of whom needed the assistance of a relative. The mean (SD) dimension score for the subscale physical functioning was 13.3 (15.7); for the subscale psychosocial functioning, 10.5 (11.5); and for the total SIP, 12.8 (12). All defined patient characteristics as known before CPR were significantly associated with physical functioning (Table 1). Physical functioning tended to be more impaired in case of in-hospital resuscitation, prolonged coma, and an interview 6 months or less after resuscitation. Psychosocial functioning was significantly more impaired with a noncardiac reason for admission and tended to be associated with dependence in daily life before CPR, but this was not statistically significant. The overall quality of life (total SIP) was significantly more impaired in the case of patients aged 70 years or older and those with a noncardiac reason for admission. Prolonged coma also tended to result in a more impaired overall quality of life. The mean (SD) score for perceived quality of life as rated by the patients was 7 (2) on a scale of 0 to 10.

Cognition

The MMSE was completed by 88 patients, with a mean (SD) score of 27 (4.3); 2 refused to complete the MMSE. Fifteen patients (17%) were classified as cognitively impaired at the cutoff point of 23 or more. Cognitive dysfunctioning was significantly associated with age 70 years or older and with a noncardiac reason for admission. Duration of CPR and coma were not significantly associated with MMSE scores.

Depression

The Center for Epidemiologic Studies Depression Scale was completed by 86 patients. Four patients were not capable of completing the Center for Epidemiologic Studies Depression Scale. The mean (SD) score was 8 (8.1). At the cutoff point of 16 or more, 14 patients (16%) were classified as having depressive symptoms. No specific factor was significantly associated with depression.

Dependence in daily life

The Rankin Scale was scored for all patients. Daily life was little or not limited in 66 patients (74%) (Rankin Scale score ≤2). Twelve (13%) had restrictions in daily life (Rankin Scale score, 3), but were able to look after themselves. Twelve patients (13%) were partially or totally dependent (Rankin Scale score, 4). Patients aged 70 years or older and with a noncardiac admission (P =.05) were significantly associated with dependence in daily life after CPR.

Independent characteristics explaining quality of life

On entering all clinical characteristics in linear regression models, mainly the characteristics before CPR could explain the level of quality of life after CPR (Table 2). However, the variances explained were relatively low. An impaired physical functioning and dependence in daily life could be partially explained by multiple factors (noncardiac reason for admission, age, and duration of coma). An impaired psychosocial and total functioning could be explained by a single factor (noncardiac reason for admission). By logistic regression analysis, a noncardiac reason for admission was identified as the only independent risk factor for cognitive impairments (odds ratio, 10; 95% confidence intervals, 3.36). Multivariate analysis was not performed on perceived quality of life and depressive symptoms because no significant associated characteristic could be identified at the univariate level.

Quality-of-life differences between the patient populations

The comparison of the profile of our SIP scores with that of (1) survivors after out-of-hospital cardiac arrest10 and (2) survivors after cardiac arrest in the intensive care9 is shown in Figure 2. The quality of life of our study group did not importantly differ from the reference groups of survivors of out-of-hospital CPR and CPR while in the intensive care unit.

The comparison of the profile of SIP scores of our study group with that of (1) a population of 132 Dutch elderly people (age range, 61-75 years) visiting the general practitioner15 and (2) an age-corrected subsample of 441 Dutch patients with stroke (mean age, 64 years)16 is shown in Figure 3. The quality of life of CPR survivors was substantially worse (higher scores) compared with the elderly individuals, except for mobility, social interaction, alertness behavior, and communication, but better (lower scores) than that of patients with stroke, particularly in body care and movement, communication, and eating.

Comment

A commonly expressed fear is that CPR results in a poor quality of life, particularly the worst imaginable, a vegetative state. The results of our study indicate that quality of life after CPR in general is satisfactory. Of the survivors, 75% were independent in daily life and survivors themselves rated their quality of life at 7 on a scale of 10. The feared vegetative state occurred only in 3% of our patients and was followed by death within several months.

Comparing our quality-of-life outcomes with other studies is difficult because of methodological differences. Most studies involve a small number of patients,6,20-28 with a few exceptions,29-31 and outcomes are mainly assessed by clinical judgment21-23,26,27,30,31 and rarely by quantitative measurements.9,10 When no important methodological differences exist,9,10 our data suggest that across different studies, survivors after CPR have about the same quality of life, regardless of the conditions under which CPR took place. When the quality of life of our survivors of CPR is compared with a group of elderly patients who were studied with the same quantitative instruments, significant impairments in CPR survivors can be detected by all subscales of the SIP, but these impairments are of much smaller magnitude than the impairments of a group of stroke survivors. How much of the impairments after CPR can be attributed to the CPR itself and/or the underlying disease cannot be determined by our study. However, of all of the determinants of the quality of life studied, the admission diagnosis in the hospital was the most important factor that could explain the differences in the quality of life. This indicates that differences in disease leading to CPR, rather than differences in CPR and recovery itself, contribute to the quality of life after CPR. It is also important to notice that a prolonged duration of CPR did not have a negative influence on any of the dimensions of the quality of life after CPR. We expect that more information on the condition of the patient before CPR will lead to a more complete explanation of their quality of life after CPR.

The results of this study could have been biased by selection through mortality or patient participation. If only the most healthy patients survive or participate, it may be that the quality of life is overestimated and potential determinants of poor quality of life remain undetected. However, we have no clear evidence that participation biased our results—the few patients who refused to participate in our study were not characterized unanimously by a poor quality of life.

Patients who were interviewed within 6 months after discharge performed worse in physical and total functioning as measured with the SIP. This suggests a difference in physical functioning over time. It may imply that recovery may take more than 6 months, but also that the outcome quality of life after CPR depends on the timing of assessment. When investigating changes in the quality of life over time, a longitudinal study design is required, with repeated measures and control over mortality as a potential confounding factor.

We conclude that CPR is frequently unsuccessful, but if survival is achieved and the patient leaves the hospital, a fair to good quality of life can be expected. When deciding on a do-not-attempt resuscitation order, we recommend that one not only focus on a small probability of survival,32 but also consider the high probability of a good quality of life for the survivors.

Accepted for publication May 26, 1998.

This study was supported by grant 93.170 from the Netherlands Heart Foundation, The Hague.

Reprints: R. de Vos, RN, Academic Medical Center, University of Amsterdam, Division Operation Center H1-212, Meibergdreef 9, PO Box 22700, 1100 DE Amsterdam, the Netherlands (e-mail: r.vos@amc.uva.nl).

References
1.
Levy  DECoronna  JJBurton  HSLapinski  RHFrydman  HPlum  F Predicting outcome from hypoxic-ischemic coma.  JAMA. 1985;2531420- 1426Google ScholarCrossref
2.
Edgren  EHedstrand  UKelsey  SSutton-Tyrrell  KSafar  P Assessment of neurological prognosis in comatose survivors of cardiac arrest: BRCT I Study Group.  Lancet. 1994;3431055- 1059Google ScholarCrossref
3.
Stiell  IGHebert  PCWells  GA  et al.  The Ontario trial of active compression-decompression cardiopulmonary resuscitation for in-hospital and prehospital cardiac arrest.  JAMA. 1996;2751417- 1423Google ScholarCrossref
4.
Spilker  B Introduction. Spilker  Bed Quality of Life Assessment in Clinical Trials. New York, NY Raven Press1990;3- 10Google Scholar
5.
Bayer  AJAng  BCPathy  MS Cardiac arrests in a geriatric unit.  Age Ageing. 1985;14271- 276Google ScholarCrossref
6.
Bedell  SEDelbanco  TLCook  EFEpstein  FM Survival after cardiopulmonary resuscitation in the hospital.  N Engl J Med. 1983;309569- 576Google ScholarCrossref
7.
Longstreth  WTJInui  TSCobb  LACopass  MK Neurologic recovery after out-of-hospital cardiac arrest.  Ann Intern Med. 1983;98588- 592Google ScholarCrossref
8.
Bergner  LBBergner  MHallstrom  APEisenberg  MSCobb  LA Health status of survivors of out-of-hospital cardiac arrest six months later.  Am J Public Health. 1984;74508Google ScholarCrossref
9.
Reis Miranda  D Quality of life after cardiopulmonary resuscitation.  Chest. 1994;106524- 530Google ScholarCrossref
10.
Bergner  MBobitt  RACarter  WBGilson  BS The Sickness Impact Profile: development and final revision of a health status measure.  Med Care. 1981;19787- 805Google ScholarCrossref
11.
Folstein  MFFolstein  SEMcHugh  PR "Mini-Mental State:" a practical method for grading the cognitive state of patients for the clinician.  J Psychiatr Res. 1975;12189- 198Google ScholarCrossref
12.
Barnes  GECurrie  RFSegall  A Symptoms of depression in a Canadian urban sample.  Can J Psychiatry. 1988;33386- 393Google Scholar
13.
Radloff  LS The CES-D scale: A self-report depression scale for research in the general population.  Appl Psychol Measure. 1977;1385- 401Google ScholarCrossref
14.
Rankin  J Cerebral vascular accidents in patients over the age of 60, II: prognosis.  Scott Med J. 1957;2200- 215Google Scholar
15.
Jacobs  HLuttik  ATouw-Otten  FKastein  Mde Melker  R Measuring impact of sickness in patients with nonspecific abdominal complaints in a Dutch family practice setting.  Med Care. 1992;30244- 551Google ScholarCrossref
16.
de Haan  RJLimburg  Mvan der Meulen  JHJacobs  HAaronson  NK Quality of life after stroke: impact of stroke type and lesion location.  Stroke. 1995;26402- 408Google ScholarCrossref
17.
Altman  DG Practical Statistics for Medical Research.  New York, NY Chapman & Hall1991;
18.
Kleinbaum  DGKupper  LLMuller  EM Applied Regression Analysis and Other Multivariable Methods.  Belmont, Calif Duxbury Press1988;
19.
Hosmer  DWLemeshow  S Applied Logistic Regression.  New York, NY John Wiley & Sons Inc1989;
20.
Cohen  J Statistical Power Analysis for the Behavioral Sciences.  Orlando, Fla Academic Press Inc1977;
21.
Rozenbaum  EAShenkman  L Predicting outcome of inhospital cardiopulmonary resuscitation.  Crit Care Med. 1988;16583- 586Google ScholarCrossref
22.
Gulati  RSBhan  GLHoran  MA Cardiopulmonary resuscitation of old people.  Lancet. 1983;2267- 269Google ScholarCrossref
23.
Blackhall  LJZiogas  AAzen  SP Low survival rate after cardiopulmonary resuscitation in a county hospital.  Arch Intern Med. 1992;1522045- 2048Google ScholarCrossref
24.
Sack  JBKesselbrenner  MBBregman  D Survival from in-hospital cardiac arrest with interposed abdominal counterpulsation during cardiopulmonary resuscitation.  JAMA. 1992;267379- 385Google ScholarCrossref
25.
Madl  CGrimm  GKramer  L  et al.  Early prediction of individual outcome after cardiopulmonary resuscitation.  Lancet. 1993;341855- 858Google ScholarCrossref
26.
Vitelli  CCooper  KRogatko  ABrennan  M Cardiopulmonary resuscitation and the patient with cancer.  J Clin Oncol. 1991;9111- 115Google Scholar
27.
Landry  FJParker  JMPhillips  YY Outcome of cardiopulmonary resuscitation in the intensive care setting.  Arch Intern Med. 1992;1522305- 2308Google ScholarCrossref
28.
Murphy  DJMurray  AMRobinson  BECampion  EW Outcomes of cardiopulmonary resuscitation in the elderly.  Ann Intern Med. 1989;111199- 205Google ScholarCrossref
29.
DeBard  ML Cardiopulmonary resuscitation: analysis of six years' experience and review of the literature.  Ann Emerg Med. 1981;10408- 416Google ScholarCrossref
30.
Longstreth  WTJCobb  LAFahrenbruch  CECopass  MK Does age affect outcomes of out-of-hospital cardiopulmonary resuscitation?  JAMA. 1990;2642109- 2110Google ScholarCrossref
31.
Woog  RHTorzillo  PJ In-hospital cardiopulmonary resuscitation: prospective survey of management and outcome.  Anaesth Intensive Care. 1987;15193- 198Google Scholar
32.
Murphy  DJBurrows  DSantilli  S  et al.  The influence of the probability of survival on patients' preferences regarding cardiopulmonary resuscitation.  N Engl J Med. 1994;330545- 549Google ScholarCrossref
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