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Title: Predicting death and readmission after intensive care discharge
Authors: Campbell, Alison J.
Cook, Jonathan Alistair
Adey, Gillian
Cuthbertson, Brian
University of Aberdeen, School of Medicine & Dentistry, Division of Applied Health Sciences
Keywords: Complications
Intensive care
Statistical models
Issue Date: Jun-2008
Publisher: Oxford Journals
Citation: Campbell, A.J., Cook, J.A., Adey, G., and Cuthbertson, B.H. (2008). Predicting death and readmission after intensive care discharge. British Journal of Anaesthesia, 100(5), pp. 656-662.
Abstract: Background: Despite initial recovery from critical illness, many patients deteriorate after discharge from the intensive care unit (ICU). We examined prospectively collected data in an attempt to identify patients at risk of readmission or death after intensive care discharge. Methods: This was a secondary analysis of clinical audit data from patients discharged alive from a mixed medical and surgical (non-cardiac) ICU. Results: Four hundred and seventy-five patients (11.2%) died in hospital after discharge from the ICU. Increasing age, time in hospital before intensive care admission, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and discharge Therapeutic Intervention Scoring System (TISS) score were independent risk factors for death after intensive care discharge. Three hundred and eighty-five patients (8.8%) were readmitted to intensive care during the same hospital admission. Increasing age, time in hospital before intensive care, APACHE II score, and discharge to a high dependency unit were independent risk factors for readmission. One hundred and forty-three patients (3.3%) were readmitted within 48 h of intensive care discharge. APACHE II scores and discharge to a high dependency or other ICU were independent risk factors for early readmission. The overall discriminant ability of our models was moderate with only marginal benefit over the APACHE II scores alone. Conclusions: We identified risk factors associated with death and readmission to intensive care. It was not possible to produce a definitive model based on these risk factors for predicting death or readmission in an individual patient.
DOI: http://dx.doi.org10.1093/bja/aen069
ISSN: 0007-0912
Rights: This is a pre-copy-editing, author-produced PDF of an article accepted for publication in British Journal of Anaesthesia following peer review. The definitive publisher-authenticated version Campbell, AJ., Cook, JA., Adey, G. & Cuthbertson, B. (2008). 'Predicting death and readmission after intensive care discharge.' British Journal of Anaesthesia 100(5) pp. 656-662. is available online at: http://dx.doi.org10.1093/bja/aen069.
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