Role of sex and gender in concussion outcome differences among patients presenting to the emergency department: a systematic review
Bibliographic record
Abstract
OBJECTIVE: This systematic review aimed to identify research involving adults presenting to the emergency department (ED) with a concussion to document the reporting of sex and/or gender according to the Canadian Institutes of Health Research (CIHR) guidelines, the prevalence of sex and gender-based analysis (SGBA) and to summarise sex and/or gender-based differences in ED presentation, management and outcomes. DESIGN: Systematic review. METHODS: Electronic databases and grey literature were searched to identify studies that recruited adult patients with concussion from the ED. Two independent reviewers identified eligible studies, assessed quality and extracted data. A descriptive summary of the evidence was generated, and sex and/or gender reporting was examined for accuracy according to standardised criteria. RESULTS: Overall, 126 studies were included in the analyses. A total of 80 (64%) studies reported sex and/or gender as demographic information, of which 51 (64%) included sex and/or gender in their analysis; however, 2 (3%) studies focused on an SGBA. Sex was more accurately reported in alignment with CIHR definitions than gender (94% vs 12%; p<0.0001). In total, 25 studies used an SGBA for outcomes of interest. Males and females experience different causes of concussion, 60% of studies documented that females had less frequent CT scanning while in the ED, and 57% of studies reported that postconcussion syndrome was more prevalent in females and women. CONCLUSION: This systematic review highlighted that sex is reported more accurately than gender, approximately half of studies did not report either sex and/or gender as demographic information, and one-third of studies did not include SGBA. There were important sex and gender differences in the cause, ED presentation, management and outcomes of concussions. PROSPERO REGISTRATION NUMBER: CRD42021258613.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".