Antihypertensive drugs : patterns of use and biases in the estimation of myocardial infarction risk
Bibliographic record
Abstract
In this thesis, we addressed different issues related to drug exposure as it may bear on the estimates of risk in the context of hypertension treatment. A cohort of 19,501 subjects initiating therapy for uncomplicated hypertension was identified from Saskatchewan Health databases. In a first study aimed at documenting the equivalence of the angiotensin-converting-enzyme (ACE) inhibitors, we found that medical visits and hospitalizations following treatment initiation were lower among patients initially dispensed enalapril and lisinopril relative to captopril. Baseline characteristics could not be ruled out as possible explanations but variability in the outcomes suggest that ACE inhibitors may not be equivalent in all respects. Due to concerns about the appropriateness of using initial treatment as the exposure, patterns of use of antihypertensive were examined longitudinally in the second manuscript using the same cohort. ACE inhibitors, followed by calcium antagonists and beta-blockers, were the most commonly prescribed agents to initiate therapy for hypertension. Compliance with therapy was found to decrease over time with only 28% of patients still being compliant after seven years. In addition, 89% of patients underwent at least one modification to therapy, interrupted treatment being the most frequently encountered. Important differences were also found across agents with regard to compliance, type and timing of treatment modifications. The third manuscript reports on a case-control study assessing the association between antihypertensive drug use and the risk of myocardial infarction (MI). Overall, 812 cases of MI were identified using hospital discharge data and death certificates. Four controls were matched to each case on entry date and time at risk of an event. Compared with beta-blockers, current use of calcium antagonists was associated with an increased risk of MI (RR = 2.3; 95% Cl = 1.7--3.1). The risk ratio for ACE inhibitors was 1.3 (95% Cl = 1.0
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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 | 0.100 | 0.276 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".