Evidence map›Paper›PMID 39729030›Full record

ArticleEpilepsia2025

Mediators of epilepsy risk after traumatic brain injury: A 20-year U.S. veteran cohort study.

Shashank Vadlamani, Mustafa Ozmen, James J Gugger, Amanda Cheney, Megan Amuan, Ramon Diaz-Arrastia, Mary Jo Pugh, Eamonn Kennedy

Abstract read
In one paragraph

Article in Epilepsia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Bayesian age-period-cohort analysis and trend prediction of epilepsy disease burden in China, 1990-2021.Epileptic disorders : international epilepsy journal with videotape · 2026
    Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Shashank VadlamaniVA Salt Lake City Health Care System, Informatics, Decision-Enhancement and Analytic Sciences Center, Salt Lake City, Utah, USA.ORCID https://orcid.org/0009-0005-6519-8673
Mustafa OzmenDivision of Epidemiology, University of Utah, Salt Lake City, Utah, USA.
James J GuggerDepartment of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Amanda CheneyDivision of Epidemiology, University of Utah, Salt Lake City, Utah, USA.
Megan AmuanVA Salt Lake City Health Care System, Informatics, Decision-Enhancement and Analytic Sciences Center, Salt Lake City, Utah, USA.
Ramon Diaz-ArrastiaDepartment of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Mary Jo PughVA Salt Lake City Health Care System, Informatics, Decision-Enhancement and Analytic Sciences Center, Salt Lake City, Utah, USA.ORCID https://orcid.org/0000-0003-4196-7763
Eamonn KennedyVA Salt Lake City Health Care System, Informatics, Decision-Enhancement and Analytic Sciences Center, Salt Lake City, Utah, USA.

Funding

Neuroimaging Phenotypes of Post-Traumatic EpilepsyK23NS135101 · NINDS · UNIVERSITY OF ROCHESTER · PI James J Gugger · 2024 to 2026
$664k
Congressionally Directed Medical Research Programs EP220089NINDS NIH HHS K23 NS135101
6 · The paper itself

Abstract

objectiveTraumatic brain injury (TBI) is a significant risk factor for epilepsy, but little work has explored whether risk of epilepsy after TBI may operate through intermediary mechanisms. The objective of this study was to statistically screen for potentially mediating effects among 64 comorbidities for epilepsy risk following TBI among Post-9/11 U.S. veterans.

methodsThis longitudinal matched cohort study used an established algorithm to identify veterans in Department of Defense (DoD) and Veterans Health Administration (VHA) records with a history of the primary exposure, TBI, between 2003 and 2023, who were demographically matched 1:1 with veterans without history of TBI exposure from the same cohort. In the observation time window after index date, mediation models estimated the proportion eliminated of the total TBI-epilepsy relationship by other factors. Cox proportional hazard models were implemented for 64 comorbidities determined using International Classification of Diseases, Ninth/Tenth Revision (ICD-9/10) codes, each individually tested for the potential mediation of epilepsy onset after date of first TBI (index date), adjusting for demographic and military covariates. Age-stratified mediation analyses were conducted. Biologically plausible mechanisms were investigated.

resultsAmong N = 292 200 veterans in the TBI and matched groups, 8458 (2.9%) had an epilepsy diagnosis that met study criteria between 2003 and 2023. The adjusted hazard ratio (HR, 95% CI) for epilepsy given TBI was 6.76 [6.33-7.21]. The median duration between TBI documentation and epilepsy diagnosis was 3.3 years. In the observation time after index date (median duration: 12.2 years), Cox proportional hazard models identified the primary meditators of epilepsy risk after TBI as post-concussive symptoms (10.3%), cognitive dysfunction (7.0%), suicidal ideation/attempt (5.1%), overdose and drug abuse (3.8%-4.8%), and stroke (3.8%). SIGNIFICANCE: This study identified neurological conditions and symptoms that may play an intermediary role in the TBI-epilepsy relationship. Specific changes in health status after TBI may present useful targets for future trials and experimental approaches of PTE prevention.

Indexed as

Brain Injuries, TraumaticEpilepsyVeteransAdultCohort StudiesComorbidityFemaleHumansLongitudinal StudiesMaleMiddle AgedProportional Hazards ModelsRisk FactorsUnited Statesepilepsymediationpost‐traumatic epilepsytraumatic brain injuryveteran

Identifiers

PMID39729030
PMCPMC11997920

What Socratic holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.