Adherence to statins, beta-blockers and angiotensin-converting enzyme inhibitors following a first cardiovascular event: a retrospective cohort study.
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Population studies of statin adherence are generally restricted to one to two years of follow-up and do not analyze adherence to other drugs. OBJECTIVES: To report long-term adherence rates for statins, angiotensin-converting enzyme (ACE) inhibitors and beta-blockers in patients who recently experienced a first cardiovascular event. METHODS: Linked administrative databases in the province of Saskatchewan were used in this retrospective cohort study. Eligible patients received a new statin prescription within one year of their first cardiovascular event between 1994 and 2001. Adherence to statins, beta-blockers and ACE inhibitors was assessed from the first statin prescription to a subsequent cardiovascular event. RESULTS: Of 1221 eligible patients, the proportion of patients adherent to statin medications dropped to 60.3% at one year and 48.8% at five years. The decline in the proportion of adherent patients was most notable during the first two years (100% to 53.7%). Several factors were associated with statin adherence, including age (P = 0.012), number of physician service days (P = 0.037), chronic disease score (P = 0.032), beta-blocker adherence (P < 0.001) and ACE inhibitor adherence (P < 0.001). Adherence to beta-blockers and ACE inhibitors was very similar to adherence to statin medications at each year of follow-up. CONCLUSIONS: Patients who exhibit optimal adherence over one to two years after their initial cardiovascular event generally remain adherent over subsequent years. Also, adherence to beta-blockers and ACE inhibitors is significantly associated with statin adherence in a subset of patients; however, overall adherence to all three drugs was similarly poor.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it