A prediction model of military combat and training exposures on VA service-connected disability: a CENC study. (6th December 2019) - Eggleston, B; Dismuke-Greer, CE; Pogoda, TK; Denning, JH; Eapen, BC; Carlson, KF; Bhatnagar, S; Nakase-Richardson, R; Troyanskaya, M; Nolen, T; Walker, WC
ABSTRACT: Background : Research has shown that number of and blast-related Traumatic Brain Injuries (TBI) are associated with higher levels of service-connected disability (SCD) among US veterans. This study builds and tests a prediction model of SCD based on combat and training exposures experienced during active military service. Methods : Based on 492 US service member and veteran data collected at four Department of Veterans Affairs (VA) sites, traditional and Machine Learning algorithms were used to identify a best set of predictors and model type for predicting %SCD ≥50, the cut-point that allows for veteran access to 0% co-pay for VA health-care services. Results : The final model of predicting %SCD ≥50 in veterans revealed that the best blast/injury exposure-related predictors while deployed or non-deployed were: 1) number of controlled detonations experienced, 2) total number of blast exposures (including controlled and uncontrolled), and 3) the total number of uncontrolled blast and impact exposures. Conclusions and Relevance : We found that the highest blast/injury exposure predictor of %SCD ≥50 was number of controlled detonations, followed by total blasts, controlled or uncontrolled, and occurring in deployment or non-deployment settings. Further research confirming repetitive controlled blast exposure as a mechanism of chronic brain insult should be considered.