Sex‐ and Gender‐Based Reporting in Antihypertensive Medication Literature Informing Hypertension Guidelines
Bibliographic record
Abstract
BACKGROUND: Hypertension is the leading modifiable cardiovascular risk factor with recognized sex- and gender-based differences. We assessed the incorporation of sex and gender reporting in the antihypertensive medication literature informing hypertension guidelines. METHODS AND RESULTS: Literature cited in the International Society of Hypertension (2020), European Society of Cardiology/European Society of Hypertension (2018), American College of Cardiology/American Heart Association (2017), Latin American Society of Hypertension (2017), Pan-African Society of Cardiology (2020), and Hypertension Canada (2020) guidelines was systematically reviewed. Observational studies, randomized controlled trials, and systematic reviews involving antihypertensive medications were included. Studies with participants of a single sex, guidelines, and commentaries were excluded. Data on study participation-to-prevalence ratio by sex, analysis of baseline demographics and study outcomes by sex, and stratification of adverse events by sex were extracted. Of 1659 unique citations, 331 studies met inclusion criteria. Of those, 81% reported the sex of participants, and 22% reported a male-to-female participation-to-prevalence ratio of 0.8 to 1.2. Three percent of studies stratified baseline characteristics by sex, and 20% considered sex during analysis through statistical adjustment or stratification. Although 32% of studies reported adverse events, only 0.6% stratified adverse events by sex. Most (58%) studies reporting sex/gender used sex and gender terms interchangeably. CONCLUSIONS: Incorporation of sex- and gender-based considerations in study population, analysis, or reporting of results and adverse events is not common in the antihypertensive medication literature informing international hypertension guidelines. Greater attention to sex- and gender-based factors in research is required to optimally inform management of hypertension.
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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 | 0.174 | 0.554 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.037 | 0.029 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.003 | 0.006 |
| 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".