Systematic Review of Sex and Gender Effects in Traumatic Brain Injury: Equity in Clinical and Functional Outcomes
Bibliographic record
Abstract
Background: Although traumatic brain injury (TBI) is a leading cause of death and disability in male and female patients worldwide, little is known about the effect of sex and gender on TBI outcomes. Objectives: This systematic review summarizes the evidence on the effect of sex and gender on core TBI outcomes. Methods: All English-language studies from six literature databases that addressed core outcomes in adults with TBI and included sex or gender, TBI severity, and age in their analyses were considered eligible. Two reviewers extracted data, and two reviewers assessed study quality using tools recommended by the National Institutes of Health. The results were sorted according to time post-injury, injury severity, gender equity ranking of the study's country of origin, and outcomes studied. The results from the included studies were grouped based on the approach taken in reporting their respective findings. Results and Limitations: Of 172 articles assessed, 58 studies were selected, comprising 1, 265, 955 participants with TBI (67% male across all studies) of all injury severities. All studies were conducted in countries with a very high or high human development index, while the Gender Inequality Index (GII) varied. While the heterogeneity across studies limited any meaningful conclusions with respect to the role of sex and gender, we did observe that as gender equality ranking improved, differences between male and female participants in outcomes would diminish. Inclusion of social equity parameters in the studies was limited. Conclusions and Implications: The non-uniform findings observed bring forth the need to develop and use a comprehensive and consistent methodology in the study of sex and gender post-TBI, incorporating social equity parameters to uncover the potential social underpinnings of gender effects on health and functional outcomes. Systematic Review Registration: CRD42018098697.
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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 | 0.022 | 0.107 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".