4.5 Article

Risk prediction of hospital mortality for adult patients admitted to Australian and New Zealand intensive care units: Development and validation of the Australian and New Zealand Risk of Death model

Journal

JOURNAL OF CRITICAL CARE
Volume 28, Issue 6, Pages 935-941

Publisher

W B SAUNDERS CO-ELSEVIER INC
DOI: 10.1016/j.jcrc.2013.07.058

Keywords

Mortality prediction; SMR; Intensive care; ANZROD

Funding

  1. ANZICS CORE
  2. ANZIC RC

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Purpose: The purpose of this study is to develop and validate a new mortality prediction model (Australian and New Zealand Risk of Death [ANZROD]) for Australian and New Zealand intensive care units (ICUs) and compare its performance with the existing Acute Physiology and Chronic Health Evaluation (APACHE) III-j. Materials and Methods: All ICU admissions from 2004 to 2009 were extracted from the Australian and New Zealand Intensive Care Society Adult Patient Database. Hospital mortality was modeled using logistic regression with training (two third) and validation (one third) data sets. Predictor variables included APACHE III score components, source of admission to ICU and hospital, lead time, elective surgery, treatment limitation, ventilation status, and APACHE III diagnoses. Model performance was assessed by standardized mortality ratio, Hosmer-Lemeshow C and H statistics, Brier score, Cox calibration regression, area under the receiver operating characteristic curve, and calibration curves. Results: There were 456605 patients available for model development and validation. Observed mortality was 11.3%. Performance measures (standardized mortality ratio, Hosmer-Lemeshow C and H statistics, and receiver operating characteristic curve) for the ANZROD and APACHE III-j model in the validation data set were 1.01, 104.9 and 111.4, and 0.902; 0.84, 1596.6 and 2087.3, and 0.885, respectively. Conclusions: The ANZROD has better calibration; discrimination compared with the APACHE III-j. Further research is required to validate performance over time and in specific subgroups of ICU population. (C) 2013 Elsevier Inc. All rights

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