Adherence to guideline‐recommended care of late‐onset hypertension in females versus males: A population‐based cohort study
Bibliographic record
Abstract
BACKGROUND: Sex-based disparities in cardiovascular outcomes may be improved with appropriate hypertension management. OBJECTIVE: To compare the evidence-based evaluation and management of females with late-onset hypertension compared to males in the contemporary era. METHODS: Design: Retrospective population-based cohort study. SETTING: Ontario, Canada. PARTICIPANTS: Residents aged ≥66 years with newly diagnosed hypertension between January 1, 2010, and December 31, 2017. EXPOSURE: Sex (female vs. male). OUTCOMES AND MEASURES: We used Poisson and logistic regression to estimate adjusted sex-attributable differences in the performance of guideline-recommended lab investigations. We estimated adjusted differences in time to the prescription of, and type of, first antihypertensive medication prescribed between females and males, using Cox regression. RESULTS: Among 111,410 adults (mean age 73 years, 53% female, median follow-up 6.8 years), females underwent a similar number of guideline-recommended investigations (adjusted incidence rate ratio, 0.997 [95% confidence interval [CI] 0.99-1.002]) compared to males. Females were also as likely to complete all investigations (0.70% females, 0.77% males; adjusted odds ratio, 0.96 [95% CI 0.83-1.11]). Females were slightly less likely to be prescribed medication (adjusted hazard ratio [aHR] 0.98 [95% CI 0.96-0.99]) or, among those prescribed, less likely to be prescribed first-line medication (aHR, 0.995 [95% CI 0.994-0.997]). CONCLUSIONS: Compared to males, females with late-onset hypertension were equally likely to complete initial investigations with comparable prescription rates. These findings suggest that there may be no clinically meaningful sex-based differences in the initial management of late-onset hypertension to explain sex-based disparities in cardiovascular outcomes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".