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Record W4408156492 · doi:10.3390/neurosci6010021

Association Between Stroke and Traumatic Brain Injury: A Systematic Review and Meta-Analysis

2025· review· en· W4408156492 on OpenAlexaboutno aff
Mohammed Maan Al‐Salihi, Maryam Sabah Al-Jebur, Ahmed Abd Elazim, Ram Saha, Ahmed Saleh, Farhan Siddiq, Ali Ayyad, Adnan I. Qureshi

Bibliographic record

VenueNeuroSci · 2025
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsTraumatic brain injuryStroke (engine)MedicineInternal medicineCochrane LibraryHazard ratioSubgroup analysisMeta-analysisOdds ratioConfidence intervalPhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

Background: Stroke and traumatic brain injury (TBI) represent two major health concerns worldwide. There is growing evidence suggesting a potential association between TBI and stroke. In this systematic review and meta-analysis, we aim to explore the association between TBI and stroke risk, with a specific focus on overall stroke risk and subgroup variations based on stroke type, severity, and the post-TBI time period. Methods: PubMed, Web of Science (WOS), Scopus, and Cochrane Library were systematically searched for studies exploring the link between stroke and TBI. The pooled hazard ratios (HRs) with a 95% confidence interval (CI) were calculated. The Comprehensive Meta-Analysis (CMA) software was used for the analysis. Subgroup analyses were conducted based on stroke type, TBI severity, and post-TBI phase. The Newcastle–Ottawa Scale (NOS) was utilized for the quality assessment. Results: We included a total of 13 observational studies, with data from 8 studies used for quantitative analysis. A history of TBI was associated with a significantly higher odds of stroke compared to controls (HR = 2.3, 95% CI (1.79 to 2.958), p < 0.001). The risk was greater for hemorrhagic stroke (HR = 4.8, 95% CI (3.336 to 6.942), p < 0.001) than for ischemic stroke (HR = 1.56, 95% CI (1.28 to 1.9), p < 0.001). Both moderate-to-severe TBI (HR = 3.64, 95% CI (2.158 to 6.142), p < 0.001) and mild TBI (HR = 1.81, 95% CI (1.17 to 2.8), p = 0.007) were associated with a significantly higher risk of stroke. The risk was also higher in the early post-TBI phase (1–30 days) (HR = 4.155, 95% CI (2.25 to 7.67), p < 0.001) compared to later phases (HR = 1.68, 95% CI (1.089 to 2.59), p = 0.019) from 30 days to 1 year and (HR = 1.87, 95% CI (1.375 to 2.544), p < 0.001) after 1 year. Conclusions: This systematic review confirms a significant association between TBI and an increased risk of stroke, regardless of TBI severity, type, or timing of stroke. The findings highlight the need for early monitoring and advocating preventive strategies for stroke in patients with a history of TBI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.032
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0190.040
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.235
GPT teacher head0.453
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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