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OP72 Prospective External Validation of Risk Prediction Models for Acute Traumatic Brain Injury in UK Critical Care Units: The Rain Study
  1. DA Harrison1,
  2. KA Griggs1,
  3. M Gomes2,
  4. DK Menon3,
  5. KM Rowan1
  1. 1Clinical Trials Unit, Intensive Care National Audit & Research Centre (ICNARC), London, UK
  2. 2Department of Public Health & Policy, LSHTM, London, UK
  3. 3School of Clinical Medicine, University of Cambridge, Cambridge, UK


Background Acute traumatic brain injury (TBI) is the leading cause of death and disability in adults aged under 40 years. Statistical models have been developed to predict the risk of mortality or unfavourable outcome (death or severe disability) at six months following acute TBI but to date these risk prediction models have only been validated using existing data sources. The Risk Adjustment In Neurocritical care (RAIN) Study aimed to validate these risk prediction models among adults with acute TBI admitted to UK critical care units.

Methods Ten risk prediction models were identified: four for mortality at six months (the Hukkelhoven model and IMPACT Core, Extended and Lab models); and six for unfavourable outcome at six months (as mortality plus CRASH Basic and CT models). Risk factor data were collected from 67 UK critical care units (including 90% of regional neuroscience centres) from August 2009 to March 2011. Patients were followed up to six months for mortality by linkage with death registration and unfavourable outcome using the Glasgow Outcome Scale (Extended) administered by postal or telephone questionnaire.

The risk prediction models were validated for calibration (c index), discrimination (Hosmer-Lemeshow test and Cox calibration regression) and overall fit (Brier score). Missing data were handled with multiple imputation.

Results Data were collected for 2,975 eligible patients admitted to critical care following acute TBI. 97% of patients were followed-up for mortality and 81% for unfavourable outcome at six months. Following multiple imputation, mortality and unfavourable outcome at six months were 26% and 57%, respectively. Risk prediction models for mortality at six months had good discrimination (c index 0.75–0.78) and the Hukkelhoven and IMPACT Lab models were well calibrated, although the IMPACT Core and Extended models over-predicted mortality. The models for unfavourable outcome at six months had worse discrimination (c index 0.69–0.71) and all models substantially under-predicted risk of unfavourable outcome. The best performance overall was found for the IMPACT Lab model, which was the most complex model, incorporating laboratory measurements. Models of the next level of complexity (Hukkelhoven, CRASH CT, IMPACT Extended) all performed similarly.

Conclusion Risk prediction models for acute TBI had acceptable discrimination among a large, representative sample of patients admitted to UK critical care units. Calibration was good for mortality but poor for unfavourable outcome, and these models therefore require recalibration for use in this setting.

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