Quality of life before intensive care unit admission is a predictor of survival

Abstract

Introduction: Predicting whether a critically ill patient will survive intensive care treatment remains difficult. The advantages of a validated strategy to identify those patients who will not benefit from intensive care unit (ICU) treatment are evident. Providing critical care treatment to patients who will ultimately die in the ICU is accompanied by an enormous emotional and physical burden for both patients and their relatives. The purpose of the present study was to examine whether health-related quality of life (HRQOL) before admission to the ICU can be used as a predictor of mortality.

Methods: We conducted a prospective cohort study in a university-affiliated teaching hospital. Patients admitted to the ICU for longer than 48 hours were included. Close relatives completed the Short-form 36 (SF-36) within the first 48 hours of admission to assess pre-admission HRQOL of the patient. Mortality was evaluated from ICU admittance until 6 months after ICU discharge. Logistic regression and receiver operating characteristic analyses were used to assess the predictive value for mortality using five models: the first question of the SF-36 on general health (model A); HRQOL measured using the physical component score (PCS) and mental component score (MCS) of the SF-36 (model B); the Acute Physiology and Chronic Health Evaluation (APACHE) II score (an accepted mortality prediction model in ICU patients; model C); general health and APACHE II score (model D); and PCS, MCS and APACHE II score (model E). Classification tables were used to assess the sensitivity, specificity, positive and negative predictive values, and likelihood ratios.

Results: A total of 451 patients were included within 48 hours of admission to the ICU. At 6 months of follow up, 159 patients had died and 40 patients were lost to follow up. When the general health item was used as an estimate of HRQOL, area under the curve for model A (0.719) was comparable to that of model C (0.721) and slightly better than that of model D (0.760). When PCS and MCS were used, the area under the curve for model B (0.736) was comparable to that of model C (0.721) and slightly better than that of model E (0.768). When using the general health item, the sensitivity and specificity in model D (sensitivity 0.52 and specificity 0.81) were similar to those in model A (0.45 and 0.80). Similar results were found when using the MCS and PCS.

Conclusion: This study shows that the pre-admission HRQOL measured with either the one-item general health question or the complete SF-36 is as good at predicting survival/mortality in ICU patients as the APACHE II score. The value of these measures in clinical practice is limited, although it seems sensible to incorporate assessment of HRQOL into the many variables considered when deciding whether a patient should be admitted to the ICU.

Figure 1

Flow diagram of patient selection and inclusion. Follow up was lost in 40 patients, usually because the patients did not live in the area of the hospital (they were on vacation). Characteristics of those patients did not differ from those of the group analyzed in the study (data not shown). A large group of patients (n = 1,229) were admitted to the intensive care unit (ICU) for under 48 hours and hence were excluded from the final analysis. Patients who died within 48 hours of ICU admission (n = 44) were excluded. In some cases the patient had no close proxy (n = 36). Patients re-admitted to the ICU were excluded (n = 132) because it was possible that the first admission could have biased the proxy memories of the patient's pre-admission health-related quality of life (HRQOL). Proxies or the patients themselves refused informed consent (n = 98) mainly because they felt study participation to be too great a burden at that stressful moment. Patients transferred to other hospitals (n = 16) or with cognitive impairment (n = 60), or who did not speak sufficient Dutch (n = 12) were also excluded. Some patients were not included because of investigator absence (n = 49). LOS, length of stay.

Figure 2

Receiver operating characteristic analysis of pre-admission HRQOL and APACHE II scores in relation to mortality. A total of 451 critically ill patients were included in the analysis. Model A included the general health item of the 36-item Short-form (SF-36), age and sex. Model B included the physical component score (PCS), mental component score (MCS), age and sex. Model C included the Acute Physiology and Chronic Health Evaluation (APACHE) II score, age and sex. Model D included the general health item of the SF-36, APACHE II score, age and sex. Model E included PCS, MCS, APACHE II score, age and sex. CI, confidence interval; HRQOL, health-related quality of life; ROC, receiver operating characteristic.