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Health Services Research & Development

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Eggleston B, Dismuke-Greer CE, Pogoda TK, Denning JH, Eapen BC, Carlson KF, Bhatnagar S, Nakase-Richardson R, Troyanskaya M, Nolen T, Walker WC. A prediction model of military combat and training exposures on VA service-connected disability: a CENC study. Brain injury. 2019 Sep 2; 1-13.
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Abstract: : 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. : 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. : 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. : 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.

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