Gender Differences in International Cardiology Guideline Authorship: A Comparison of the US, Canadian, and European Cardiology Guidelines From 2006 to 2020
Bibliographic record
Abstract
Background Women continue to be underrepresented in cardiology and even more so in leadership positions. We evaluated the trends and gender differences in the guideline writing groups of the American College of Cardiology/American Heart Association (ACC/AHA), Canadian Cardiovascular Society (CCS), and European Society of Cardiology (ESC) guidelines from 2006 to 2020. Methods and Results We extracted all guidelines authors from 2006 to 2020, assessed their gender from publicly available profiles, and compared differences based on subspecialties and specific societies. Stratified and trend analyses were performed using χ 2 and average annual percentage change/average 5 year percentage change. A total of 80 ACC/AHA (1288 authors [28% women]), 64 CCS (988 authors [26% women]), and 59 ESC (1157 authors [16% women]) guidelines were analyzed. A significant increase in inclusion of women was seen in ACC/AHA (12.6% [2006] to 42.6% [2020]; average annual percentage change, 6.6% [2.3% to 11.1%]; P =0.005) and ESC (7.1% [2006] to 25.8% [2020]; average annual percentage change, 6.6% [0.2% to 13.5%]; P =0.04), but the trend remained similar in CCS (20.6% [2006] to 36.3% [2020]; average annual percentage change, −0.1% (−3.7% to 3.5%); P =0.94), guideline authors. More women were coauthors in the ACC/AHA and ESC guidelines when women were chairs of guidelines. There was a persistent disparity of women among guideline authors for general cardiology and all subspecialties, except for pediatric cardiology and heart failure guidelines. The appointment of women authors as a chair was significantly low in all societies (22.4% [ACC/AHA], 16.9% [CCS], and 7.2% [ESC]; P =0.008). Conclusions There is a significant disparity in the inclusion of women on all national guideline committees, in addition to serving as a chair of cardiology guidelines. Further advocacy is required to promote equity, diversity, and inclusion in our cardiology guidelines globally.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".