The use of cholesterol-lowering medications after coronary revascularization.
Bibliographic record
Abstract
BACKGROUND: In clinical trials, cholesterol-lowering medications have been proven to decrease mortality and morbidity and are strongly recommended as secondary prevention for patients with established coronary artery disease. Whether physicians and patients follow this recommendation is unknown. Our objective was to determine the rate at which patients fill at least one prescription for cholesterol-lowering medications after coronary revascularization. METHODS: Using the computerized administrative databases of the Régie de l'assurance maladie du Québec, we identified all elderly patients (older than 65 years) who had a coronary revascularization procedure (percutaneous coronary intervention or coronary artery bypass graft) between Apr. 1, 1995, and Dec. 31, 1997, and who survived until hospital discharge. We also determined the percentage of these patients who filled one or more prescriptions for cholesterol-lowering drug therapy before Dec. 31, 1999, or death, whichever date came first. We used multivariate logistic regression models to examine the independent associations between filling a prescription for a cholesterol-lowering drug, patient characteristics and the type and year of coronary revascularization. RESULTS: We identified 11 958 elderly patients who had a coronary revascularization between Apr. 1, 1995, and Dec. 31, 1997. During a follow-up period that averaged 3 years, 4443 (37.2%) patients did not fill a prescription for a cholesterol-lowering medication. Patients who were male, of advanced age, who had diabetes or congestive heart failure were less likely to fill a prescription for a cholesterol-lowering medication. Patients whose initial revascularization procedure was coronary artery bypass grafting were also less likely than those who had angioplasty to start cholesterol-lowering medication (relative risk [RR] 0.77, 95% confidence interval [CI] 0.73 - 0.81). Use of cholesterol lowering medications before the revascularization procedure was very strongly associated with future drug use (RR 7.20, 95% CI 6.83-7.58). INTERPRETATION: In this population-based study of revascularized patients, we observed a substantial underutilization of cholesterol-lowering medications after revascularization. Our observations suggest an important role for continuity of care in the treatment of cardiovascular patients undergoing revascularization procedures.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".