Predicting death and readmission after intensive care discharge.

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 s...

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Main Authors: Campbell, A, Cook, J, Adey, G, Cuthbertson, B
Format: Journal article
Language:English
Published: 2008
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author Campbell, A
Cook, J
Adey, G
Cuthbertson, B
author_facet Campbell, A
Cook, J
Adey, G
Cuthbertson, B
author_sort Campbell, A
collection OXFORD
description 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.
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spelling oxford-uuid:44bfd66c-c90d-45fd-b47e-dce9eadd756f2022-03-26T15:03:32ZPredicting death and readmission after intensive care discharge.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:44bfd66c-c90d-45fd-b47e-dce9eadd756fEnglishSymplectic Elements at Oxford2008Campbell, ACook, JAdey, GCuthbertson, B 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.
spellingShingle Campbell, A
Cook, J
Adey, G
Cuthbertson, B
Predicting death and readmission after intensive care discharge.
title Predicting death and readmission after intensive care discharge.
title_full Predicting death and readmission after intensive care discharge.
title_fullStr Predicting death and readmission after intensive care discharge.
title_full_unstemmed Predicting death and readmission after intensive care discharge.
title_short Predicting death and readmission after intensive care discharge.
title_sort predicting death and readmission after intensive care discharge
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