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A prediction model of military combat and training exposures on VA service-connected disability
A CENC study
Eggleston, B., Dismuke-Greer, C. E., Pogoda, T. K., Denning, J. H., Eapen, B. C., Carlson, K. F., Bhatnagar, S., Nakase-Richardson, R., Troyanskaya, M., Nolen, T., & Walker, W. C. (2019). A prediction model of military combat and training exposures on VA service-connected disability: A CENC study. Brain Injury, 33(13-14), 1602-1614. https://doi.org/10.1080/02699052.2019.1655793
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.