Systematic Incorporation of Sex‐Specific Information Into Clinical Practice Guidelines for the Management of ST‐Segment–Elevation Myocardial Infarction: Feasibility and Outcomes
Why this work is in the frame
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Bibliographic record
Abstract
Background Clinical practice guideline ( CPG ) developers have yet to endorse a consistent and systematic approach for considering sex-specific cardiovascular information in CPG s. This article describes an initiative led by the Canadian Cardiovascular Society to determine the feasibility and outcomes of a structured process for considering sex in a CPG for the management of ST-segment-elevation myocardial infarction. Methods and Results A sex and gender champion was appointed to the guideline development committee. The feasibility of tailoring the CPG to sex was ascertained by recording (1) the male-female distribution of the study population, (2) the adequacy of sex-specific representation in each study using the participation/prevalence ratio, and (3) whether data were disaggregated by sex. The outcome was to determine whether recommendations for CPG s based on an assessment of the evidence should differ by sex. In total, 175 studies were included. The mean percentage of female participants reported in the studies was 24.5% ( SD : 6.6%; minimum: 0%; maximum: 51%). The mean participation/prevalence ratio was 0.62 ( SD : 0.16; minimum: 0.00; maximum: 1.19). Eighteen (10.2%) studies disaggregated the data by sex. Based on the participation/prevalence ratio and the sex-specific analyses presented, only 1 study provided adequate evidence to confidently inform the applicability of the CPG recommendations to male and female patients. Conclusions Implementing a systematic process for critically appraising sex-specific evidence for CPG s was straightforward and feasible. Inadequate enrollment and reporting by sex hindered comprehensive sex-specific assessment of the quality of evidence and strength of recommendations for a CPG on the management of ST-segment-elevation myocardial infarction.
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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 | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it