Classification accuracy of serum Apo A-I and S100B for the diagnosis of mild traumatic brain injury and prediction of abnormal initial head computed tomography scan.

The objective of the current study was to determine the classification accuracy of serum S100B and apolipoprotein (apoA-I) for mild traumatic brain injury (mTBI) and abnormal initial head computed tomography (CT) scan, and to identify ethnic, racial, age, and sex variation in classification accuracy. We performed a prospective, multi-centered study of 787 patients with mTBI who presented to the emergency department within 6 h of injury and 467 controls who presented to the outpatient laboratory for routine blood work. Serum was analyzed for S100B and apoA-I. The outcomes were disease status (mTBI or control) and initial head CT scan. At cutoff values defined by 90% of controls, the specificity for mTBI using S100B (0.899 [95% confidence interval (CI): 0.78-0.92]) was similar to that using apoA-I (0.902 [0.87-0.93]), and the sensitivity using S100B (0.252 [0.22-0.28]) was similar to that using apoA-I (0.249 [0.22-0.28]). The area under the receiver operating characteristic curve (AUC) for the combination of S100B and apoA-I (0.738, 95% CI: 0.71, 0.77), however, was significantly higher than the AUC for S100B alone (0.709, 95% CI: 0.68, 0.74, p=0.001) and higher than the AUC for apoA-I alone (0.645, 95% CI: 0.61, 0.68, p<0.0001). The AUC for prediction of abnormal initial head CT scan using S100B was 0.694 (95%CI: 0.62, 0.77) and not significant for apoA-I. At a S100B cutoff of <0.060 μg/L, the sensitivity for abnormal head CT was 98%, and 22.9% of CT scans could have been avoided. There was significant age and race-related variation in the accuracy of S100B for the diagnosis of mTBI. The combined use of serum S100B and apoA-I maximizes classification accuracy for mTBI, but only S100B is needed to classify abnormal head CT scan. Because of significant subgroup variation in classification accuracy, age and race need to be considered when using S100B to classify subjects for mTBI.