Pharmacoepidemiologic study of association between apparent treatment resistant hypertension, cardiovascular disease and interaction effect by sex and age
Bibliographic record
Abstract
Objective-Despite gender neutral guidelines, prior studies suggest that women have lower rates of hypertension control and these differences may vary with age.Accordingly, we compared rates of hypertension control between women and men as a function of age.Methods-Within 3 integrated healthcare systems in the Cardiovascular Research Network, we studied all patients seen from 2001-2007 with incident hypertension.Within 1-year of cohort entry, patient's hypertension was categorized as: 1) controlled based upon achieving guidelinerecommended BP levels, 2) recognized if hypertension was diagnosed or a hypertension medication dispensed, and 3) treated based on hypertension medications dispensed.Multivariable logistic regression models assessed the association between gender and 1-year hypertension outcomes, adjusted for patient characteristics.Results-Among the 152,561 patients with incident hypertension, 55.6% were women.Compared to men, women were older, had more kidney disease and more blood pressure measures during follow-up.Overall, men tended to have lower rates of hypertension control compared to women (41.2% vs. 45.7%,adjusted OR 0.93, 96% CI 0.91-0.95).A significant gender by age interaction was found with men aged 18-49 having 17% lower odds of hypertension control and men aged ≥ 65 having 12% higher odds of hypertension control compared to women of similar ages (p<0.001).Conclusions-In this incident hypertension cohort, younger men and older women had lower rates of hypertension control compared to similarly aged peers.Future studies should investigate why gender differences vary by age in order to plan appropriate means of improving hypertension management regardless of gender or age.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".