Predicting outcome after traumatic brain injury: development of prognostic scores based on the IMPACT and the APACHE II.

Prediction models are important tools for heterogeneity adjustment in clinical trials and for the evaluation of quality of delivered care to patients with traumatic brain injury (TBI). We sought to improve the predictive performance of the IMPACT (International Mission for Prognosis and Analysis of Clinical Trials) prognostic model by combining it with the APACHE II (Acute Physiology and Chronic Health Evaluation II) for 6-month outcome prediction in patients with TBI treated in the intensive care unit. A total of 890 patients with TBI admitted to a large urban level 1 trauma center in 2009-2012 comprised the study population. The IMPACT and the APACHE II scores were combined using binary logistic regression. A randomized, split-sample technique with secondary bootstrapping was used for model development and internal validation. Model performance was assessed by discrimination (by area under the curve [AUC]), calibration, precision, and net reclassification improvement (NRI). Overall 6-month mortality was 22% and unfavorable neurological outcome 47%. The predictive power of the new combined IMPACT-APACHE II models was significantly superior, compared to the original IMPACT models (AUC, 0.81-0.82 vs. 0.84-0.85; p<0.05) for 6-month mortality prediction, but not for unfavorable outcome prediction (AUC, 0.81-0.82 vs. 0.83; p>0.05). However, NRI showed a significant improvement in risk stratification of patients with unfavorable outcome by the IMPACT-APACHE II models, compared to the original models (NRI, 5.4-23.2%; p<0.05). Internal validation using split-sample and resample bootstrap techniques yielded equivalent results, indicating low grade of overestimation. Our findings show that by combining the APACHE II with the IMPACT, improved 6-month outcome predictive performance is achieved. This may be applicable for heterogeneity adjustment in forthcoming TBI studies.