The International Incidence of Traumatic Brain Injury: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Understanding the epidemiology of traumatic brain injury (TBI) is essential to shape public health policy, implement prevention strategies, and justify allocation of resources toward research, education, and rehabilitation in TBI. There is not, to our knowledge, a systematic review of population-based studies addressing the epidemiology of TBI that includes all subtypes. We performed a comprehensive systematic review and meta-analysis of the worldwide incidence of TBI. METHODS: A search was conducted on May 23, 2014, in Medline and EMBASE according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Abstracts were screened independently and in duplicate to identify original research. Study quality and ascertainment bias were assessed in duplicate using a previously published tool. Demographic data and incidence estimates from each study were recorded, along with stratification by age, gender, year of data collection, and severity. RESULTS: The search strategy yielded 4944 citations. Two hundred and sixteen articles met criteria for full-text review; 144 were excluded. Hand searching resulted in ten additional articles. Eighty-two studies met all eligibility criteria. The pooled annual incidence proportion for all ages was 295 per 100,000 (95% confidence interval: 274-317). The pooled incidence rate for all ages was 349 (95% confidence interval: 96.2-1266) per 100,000 person-years. Incidence proportion and incidence rate were examined to see if associated with age, sex, country, or severity. CONCLUSIONS: We conclude that most TBIs are mild and most TBIs occur in males among the adult population. The incidence of TBI varies widely by ages and between countries. Despite being an important medical, economic, and social problem, the global epidemiology of TBI is still not well-characterized in the current literature. Understanding the incidence of TBI, particularly mild TBI, remains challenging because of nonstandardized reporting among neuroepidemiological studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.062 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.047 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".