• Paloma Ferrando-Vivas, Andrew Jones, Kathryn M Rowan, and David A Harrison.
• Intensive Care National Audit & Research Centre (ICNARC), London, UK.
• J Crit Care. 2017 Apr 1; 38: 335-339.

PurposeTo develop and validate an improved risk model to predict acute hospital mortality for admissions to adult critical care units in the UK.Materials And Methods155,239 admissions to 232 adult critical care units in England, Wales and Northern Ireland between January and December 2012 were used to develop a risk model from a set of 38 candidate predictors. The model was validated using 90,017 admissions between January and September 2013.ResultsThe final model incorporated 15 physiological predictors (modelled with continuous nonlinear models), age, dependency prior to hospital admission, chronic liver disease, metastatic disease, haematological malignancy, CPR prior to admission, location prior to admission/urgency of admission, primary reason for admission and interaction terms. The model was well calibrated and outperformed the current ICNARC model on measures of discrimination (area under the receiver operating characteristic curve 0.885 versus 0.869) and model fit (Brier's score 0.108 versus 0.115). On average, the new model reclassified patients into more appropriate risk categories (net reclassification improvement 19.9; P<0.0001). The model performed well across patient subgroups and in specialist critical care units.ConclusionsThe risk model developed in this study showed excellent discrimination and calibration and when validated on a different period of time and across different types of critical care unit. This in turn allows improved accuracy of comparisons between UK critical care providers.Copyright © 2016. Published by Elsevier Inc.

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