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.
Original language | English (US) |
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Pages (from-to) | 1602-1614 |
Number of pages | 13 |
Journal | Brain Injury |
Volume | 33 |
Issue number | 13-14 |
DOIs | |
State | Published - Dec 6 2019 |
Keywords
- Prediction
- concussion and traumatic brain injury
- disability
- military
- potential concussive event
- veteran
ASJC Scopus subject areas
- Neuroscience (miscellaneous)
- Developmental and Educational Psychology
- Clinical Neurology