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Comparative Study
. 2001 Sep;120(3):928-33.
doi: 10.1378/chest.120.3.928.

Predicting mortality in patients suffering from prolonged critical illness: an assessment of four severity-of-illness measures

Affiliations
Comparative Study

Predicting mortality in patients suffering from prolonged critical illness: an assessment of four severity-of-illness measures

S S Carson et al. Chest. 2001 Sep.

Abstract

Study objectives: Investigators have been using severity-of-illness indexes such as APACHE II (acute physiology and chronic health evaluation score II) to describe patients with prolonged critical illness. However, little is known about the utility of these indexes for this patient population. We evaluated the ability of four severity-of-illness indexes to predict mortality rates in 182 patients with prolonged critical illness.

Design: Retrospective inception cohort study.

Setting: A single, urban, long-term, acute-care hospital in Chicago.

Patients: One hundred eighty-two patients transferred from 37 acute-care hospital ICUs.

Measurements and results: We assessed four indexes: the acute physiology and chronic health evaluation II, the simplified acute physiology score II, the mortality prediction model II, and the logistic organ dysfunction system using variables measured on admission to the long-term acute-care hospital ICU. We found that none of these indexes distinguished well between the patients who lived and the patients who died (area under ROC [receiver operating characteristics] curve < 0.70 for all), nor did they assign correct probabilities of death to individual patients (Hosmer-Lemeshow goodness-of-fit statistics, p < 0.01 for all).

Conclusions: Investigators and clinicians should use caution in using severity-of-illness measures developed for acutely ill patients to describe critically ill patients admitted to long-term care units. As clinical practice and research focus more on these latter patients, development of adequately performing severity-of-illness measures appropriate to this patient population will be needed.

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