Comparison of two prognostic models in trauma outcome

Author:

Cook A12ORCID,Osler T3,Glance L4,Lecky F5,Bouamra O6,Weddle J7,Gross B8,Ward J1,Moore F O1,Rogers F9,Hosmer D10

Affiliation:

1. Department of Surgery, Chandler Regional Medical Center, Chandler, Arizona, USA

2. Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, USA

3. Department of Surgery, University of Vermont, Burlington, Vermont, USA

4. Department of Anesthesiology, University of Rochester, Rochester, New York, USA

5. Department of Emergency Medicine, University of Sheffield, Sheffield, UK

6. Institute of Population Health, University of Manchester, Manchester, UK

7. Department of Surgery, Baylor University Medical Center at Dallas, Dallas, Texas, USA

8. College of Medicine, University of Vermont, Burlington, Vermont, USA

9. Department of Surgery, Lancaster General Hospital, Lancaster, Pennsylvania, USA

10. Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, Massachusetts, USA

Abstract

Abstract Background The Trauma Audit and Research Network (TARN) in the UK publicly reports hospital performance in the management of trauma. The TARN risk adjustment model uses a fractional polynomial transformation of the Injury Severity Score (ISS) as the measure of anatomical injury severity. The Trauma Mortality Prediction Model (TMPM) is an alternative to ISS; this study compared the anatomical injury components of the TARN model with the TMPM. Methods Data from the National Trauma Data Bank for 2011–2015 were analysed. Probability of death was estimated for the TARN fractional polynomial transformation of ISS and compared with the TMPM. The coefficients for each model were estimated using 80 per cent of the data set, selected randomly. The remaining 20 per cent of the data were used for model validation. TMPM and TARN were compared using calibration curves, measures of discrimination (area under receiver operating characteristic curves; AUROC), proximity to the true model (Akaike information criterion; AIC) and goodness of model fit (Hosmer–Lemeshow test). Results Some 438 058 patient records were analysed. TMPM demonstrated preferable AUROC (0·882 for TMPM versus 0·845 for TARN), AIC (18 204 versus 21 163) and better fit to the data (32·4 versus 153·0) compared with TARN. Conclusion TMPM had greater discrimination, proximity to the true model and goodness-of-fit than the anatomical injury component of TARN. TMPM should be considered for the injury severity measure for the comparative assessment of trauma centres.

Publisher

Oxford University Press (OUP)

Subject

Surgery

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