ArticleInternational journal of emergency medicine2024
Peri-injury symptomatology as predictors of brain computed tomography (CT) scan abnormalities in mild traumatic brain injury (mTBI).
Article in International journal of emergency medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Concussion and Head Injuries in Soccer: Research Trends, Knowledge Structure, and Emerging Themes.Orthopedic reviews · 2026Article
- Predictors of skull fracture and intracerebral pathology after pediatric traumatic brain injury.Orthopedic reviews · 2025Article
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Authors and funding
4 authors.
Funding
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Abstract
objectiveThis study aimed to identify predictors of brain CT abnormalities in patients who sustained a mild traumatic brain injury (mTBI).
methodsRetrospective observational cohort of adult patients with mTBI (Glasgow Coma Score 13-15) that occurred within the preceding 24 h.
results2548 (91%) of the cohort had a brain CT and 698 (27%) demonstrated abnormal findings. The most frequently observed CT abnormalities were bleeding (638, 25%) and fractures (190, 7.4%). Multivariate logistic regression analysis revealed several significant predictors associated with the presence of brain CT abnormalities including older age [P < 0.0001], male sex [P < 0.0001], loss of consciousness [P = 0.0041], associated vomiting [P = 0.0011], alteration of consciousness (AOC) [P = 0102], and GCS score [P < 0.0001]. This was a robust model with an R² of 14.2%.
conclusionIn this retrospective analysis, older age, male sex, the presence of loss of consciousness or alteration in consciousness, lower GCS score, and associated vomiting were found to be significant predictors of having an abnormal brain CT. These findings highlight the importance of considering these factors when determining the necessity of brain CT scans in patients with mTBI and suggest that existing clinical decision rules may be limited. These findings may also help to inform clinical decision rules. Early identification of individuals at a higher risk of CT abnormalities may assist in appropriate management and allocation of healthcare resources.
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