A new approach to outcome prediction in trauma: A comparison with the TRISS model

被引:108
作者
Bouamra, Omar [1 ]
Wrotchford, Alan
Hollis, Sally
Vail, Andy
Woodford, Maralyn
Lecky, Fiona
机构
[1] Univ Manchester, Hope Hosp, Trauma Audit & Res Network, Salford M6 8HD, Lancs, England
[2] Univ Lancaster, Med Stat Unit, Fylde Coll, Lancaster, England
来源
JOURNAL OF TRAUMA-INJURY INFECTION AND CRITICAL CARE | 2006年 / 61卷 / 03期
关键词
trauma; outcome; fractional polynomials; prediction; validation; INJURY SEVERITY SCORE; CARE; MORTALITY;
D O I
10.1097/01.ta.0000197175.91116.10
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
Background: The Trauma Audit & Research Network (TARN) has been using the TRISS methodology since 1989. Its database contains 200,000 hospital admissions from 110 hospitals over the country. To improve outcome prediction, a revision of the current model became necessary. Our model tried to overcome some of the concerns of the trauma community, namely missing data, functional form of the predictors, inclusion criteria and patient's death within 30 days. Methods: The data for modeling consisted of 100,399 anonymized hospital trauma admissions during the period 1996 to 2001. Cross validation was performed on this data set, and a multiple logistic regression model was derived using the prediction set and then its prediction ability was tested on the validation set. Fractional polynomials modeling showed that the linear functional form of the Injury Severity Score (ISS) in the model was not satisfactory. Using the Glasgow Coma Score (GCS) instead of the revised trauma score (RTS) has dramatically reduced the number of missing cases. Sex and its interaction with age have also been included in the model. The model was tested on different subsets of cases, traditionally excluded, such as children, those with penetrating injuries, and ventilated and transferred patients. The new model included all those subsets using age, a transformation of ISS, GCS, sex, and sex by age interaction as predictors. Results: The model has shown a good discriminant ability tested by the Area under the Receiver Operating Characteristic (AROC) curve. The values of the AROC for the new model were 0.947 (95% confidence interval [CI]: 0.943-0.951) on the prediction set and 0.952 (95% CI: 0.9460.957) on the validation set compared, respectively, with 0.937 (95% CI: 0.9320.943) and 0.941 (95% CI: 0.936-0.952) for TRISS. Conclusion: The new model has enabled us to include most of the cases that were excluded under the TRISSs inclusion criteria, less missing data are incurred and the predictive performance was significantly better than that of the TRISS model as shown by the AROC curves.
引用
收藏
页码:701 / 710
页数:10
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