Adherence to Medication According to Sex and Age in the CHARM Programme
Bibliographic record
Abstract
AIMS: Although many patients with heart failure have incomplete adherence to prescribed medications, predisposing factors remain unclear. This analysis investigates factors associated with adherence, with particular emphasis on age and sex. METHODS AND RESULTS: A multivariable regression analysis of 7599 heart failure patients from the CHARM trial was done to evaluate factors associated with adherence. Adherence was measured as the proportion of time patients took more than 80% of study medication. The mean age was 66 years (SD 11) and 31.5% (n = 2400) were women. Women were slightly less adherent than men (87.3 vs. 89.8%, P = 0.002), even in adjusted, multivariable models (treatment, P = 0.006; placebo P = 0.004; and overall P < 0.001). However, all-cause mortality was lower in women (21.5%) than in men (25.3%) (adjusted hazard ratio, 0.77; 95% CI, 0.69-0.86; P < 0.001), but patients with a low adherence regardless of sex had a higher mortality. Age, severity of heart failure, number of medications, and smoking status were not associated with adherence. CONCLUSION: Women, particularly those <75 years of age, were less likely to be adherent in this large sample of patients with symptomatic heart failure. Understanding factors associated with adherence may provide opportunities for intervention.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".