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This article is part of the supplement: 28th International Symposium on Intensive Care and Emergency Medicine .

Poster presentation

Novel models for the prediction of mortality after traumatic brain injury requiring intensive care

JA Hyam1, CA Welch2, DA Harrison2 and DK Menon3

1Charing Cross Hospital, London, UK.

2ICNARC, Case Mix Programme, London, UK.

3University of Cambridge, UK.

from 28th International Symposium on Intensive Care and Emergency Medicine
Brussels, Belgium. 18–21 March 2008

Critical Care 2008, 12(Suppl 2):P107doi:10.1186/cc6328

The electronic version of this abstract is the complete one and can be found online at: http://ccforum.com/content/12/S2/P107

Published: 13 March 2008

© 2008 BioMed Central Ltd

Introduction

Major head injury is a common reason for admission to the ICU. Knowledge of factors that predict mortality provides clues to the pathophysiology of head injury, how clinicians' interventions can be most effective, allows audit between different units or time points and provides objective data with which to communicate with patients' relatives. Several established risk prediction models exist in the ICU; however, they have been shown to have suboptimal discrimination and calibration in this patient group [1]. Our aim was therefore to develop a novel model to predict mortality specifically for head injury.

Methods

A literature review was undertaken to identify variables predictive for mortality after severe head injury. The ICNARC Case Mix Programme, containing multiple data from 374,594 admissions to 171 critical care units in England, Wales and Northern Ireland from 1995 to 2005, was searched for head injury patients with a primary diagnosis of 'primary brain injury', 'subdural haematoma, or 'extradural haematoma'. Each variable that could be supported by the database was entered into a stepwise logistic regression model with mortality as the outcome. Calibration of the risk prediction model was assessed by the area under the receiver operating characteristic curve, discrimination by the Hosmer–Lemeshow C statistic and overall fit by Brier's score.

Results

A total of 10,937 admissions with head injury were identified. A prediction model was constructed using 14 variables and shown to have a superior discrimination and calibration to APACHE II, SAPS II and MPM II. A simplified model consisting of only three variables also performed better than existing models.

Conclusion

We present two novel prediction models for mortality after head injury requiring intensive care. Both models, even the simplified model of only three variables, had superior discrimination and calibration to existing ICU risk-prediction models.

References

  1. Hyam JA, Welch CA, Harrison DA, Menon DK: Case mix, outcomes and comparison of risk prediction models for admissions to adult, general and specialist critical care units for head injury: a secondary analysis of the ICNARC Case Mix Programme Database.

    Crit Care 2006, 10(Suppl 2):S2. PubMed Abstract | BioMed Central Full Text OpenURL

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