Antihypertensive therapy and risk of cardiovascular disease in diabetic subjects
Bibliographic record
Abstract
Objective. This study was designed to assess the association between cardiovascular disease and the use of antihypertensive drugs in a diabetic population. Design and setting. We conducted a case-control study nested within a cohort of 2499 subjects over 45 years old with diabetes and hypertension in Saskatchewan. Outcomes. The main outcome measure was first hospitalization for cardiovascular disease. Exposure definition. The main exposure of interest was current use of antihypertensive drugs, defined as drug dispensing within 90 days of the index date. Statistical analysis. Relative risks were calculated with 95% confidence intervals using conditional logistic regression models. Full multivariate models, adjusting for all potential confounding covariates, were performed. Results. Compared with diuretics, current use of calcium antagonists was associated with a 1.90-fold increase in risk of cardiovascular disease (RR 1.90; 95% Cl = 1.25--2.91). The current use of beta-blockers was not associated with an increase in morbidity. The risk of cardiovascular disease for angiotensin-converting enzyme inhibitors (ACE-I) relative to diuretics was found to be increased only in the subgroup of patients currently exposed to other antihypertensive drugs, including peripheral vasodilators, centrally-acting alpha 2 agonists, and a-blockers (RR 1.6; 95% Cl = 1.19--2.18). Conclusion. Results of this research agree with the findings from several observational studies and clinical trials. However, factors influencing selective prescribing practices could not be completely accounted for and may partially explain our results.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".