Abstract 15622: Impact of Cardiac Rehabilitation on Six-Month Adherence to Cardiovascular Pharmacotherapy: Insights From the Ami-Optima 2 Study
Bibliographic record
Abstract
Introduction: It remains unclear whether cardiac rehabilitation (CR) can enhance adherence to cardiovascular (CV) medications. We aim to determine the impact of CR on 6-month adherence to CV pharmacotherapy. Methods: We conducted a prospective observational cohort study of patients hospitalized for acute coronary syndromes (ACS) in Quebec, Canada, during 2016-2018. The primary endpoint was 6-month adherence to all of these drugs (dual anti-platelets, beta-blockers, hypocholesterolemiants, angiotensin pathway inhibitors). The secondary endpoints were adherence to each individual class of CV medication. Adherence was determined by measuring the proportion of days covered (PDC) (evaluated by pharmacies refills). PDC was measured both as continuous and categorical variables. Suboptimal adherence was defined as PDC< 80%. We used inverse probability weighting to adjust for various factors which may have influenced the referral for CR and confounded the impact of CR on 6-month adherence (age, sex, coronary angioplasty, marital status, education, and occupation). All patients signed informed consent. Results: We enrolled 318 patients. Their mean age was 66±12 years; 30% were females. Of these patients, 152 undertook CR and 166 received standard follow-up. The mean age was 68 and 64 years, respectively. The proportions of females were similar in both groups. Overall PDC were 96%±13% vs 93%±17%; 7.2% and 11.2% patients had 6-month suboptimal adherence, respectively in patients who had CR vs patients without CR. After inverse weighting adjustment, CR was independently associated with improved adherence only with hypocholesterolemiants (Table 1). Conclusion: CR was not associated with improved 6-month overall adherence. However, patients who undertook CR were more adherent to hypocholesterolemiants than patients who did not undergo CR. CR programs should reinforce further to patients the importance of adherence to all ACS medications.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".