The Association Between Market Availability and Adherence to Antihypertensive Medications: An Observational Study
Bibliographic record
Abstract
BACKGROUND: High adherence to angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) reported in observational studies has frequently been attributed to improved tolerability. However, these agents are also relatively new to the market compared to other antihypertensive medications. We aimed to determine if an association exists between adherence and market availability of a specific antihypertensive agent. METHODS: This retrospective cohort study used administrative data from Saskatchewan, Canada. Subjects were ≥40 years of age and received a new antihypertensive medication between 1994 and 2002. The primary outcome was the proportion of subjects achieving optimal adherence (≥80%) at 1 year, stratified by antihypertensive medication class and the year of availability. Adherence was measured using the cumulative mean gap ratio. RESULTS: A total of 36,214 subjects met the inclusion criteria. Optimal adherence was observed in 4987 of 8623 (57.8%) subjects receiving ACEIs and 1013 of 1600 (63.3%) subjects receiving ARBs, but adherence appeared inconsistent when examined within each antihypertensive class. A pattern of increasing mean adherence was observed according to availability in the ACEI subgroup (Spearman r = 0.82; P = 0.007) but not the ARB subgroup (Spearman r = 0.41; P = 0.49). However, the association between availability and optimal adherence converged when ARB and ACEI users were combined (Spearman r = 0.85, P < 0.001). CONCLUSIONS: Optimal adherence with ACEIs and ARBs compared to other antihypertensive agents may be associated with their relative availability. To what extent optimal adherence is also associated with improved tolerability, as currently believed, remains to be determined.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".