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TruaceTracing the truth around AIWednesday, August 5, 2026
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TRV-2026-0652Certified recordPeer-reviewed

Long-term prediction of epilepsy following traumatic brain injury among veterans using routine clinical data

Objective Despite elevated risk for epilepsy following traumatic brain injury (TBI), there are limited tools to assess epilepsy risk following TBI using routine clinical data. The objective of this study was to develop and validate a machine learning approach to predict the onset of posttraumatic epilepsy (PTE) over varying time horizons following TBI, using only routine clinical data collected up to the month of TBI documentation. Methods This retrospective longitudinal cohort study included post-9/11 US vetera…

Health · G Space — documented gain · certified 2026-08-05 · v1 · article view · machine-readable

Current reading — gain

A random forest model using only routine preinjury clinical data predicted posttraumatic epilepsy onset up to 10 years after TBI in veterans, achieving AUC around 0.73-0.75 and identifying 17.5% of 5-year cases at 2.3% false positive rate.

What this doesn’t fix

Model development and validation was restricted to post-9/11 US veterans with TBI in Department of War and Veterans Health Administration records, limiting generalizability beyond this population and retrospective administrative data context.

Evidence

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Truvace Impact Record TRV-2026-0652, v1: “Long-term prediction of epilepsy following traumatic brain injury among veterans using routine clinical data.” Truvace, 2026-08-05. /record/TRV-2026-0652 (accessed at citation time). sha256 859bd6cb77dce5d2…

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