Parabolas of medication use and discontinuation after myocardial infarction—are we closing the treatment gap?
Bibliographic record
Abstract
PURPOSE: Little is known on the use of evidence-based medications in patients with acute myocardial infarction (AMI) across all ages. We undertook this study to describe the patterns of prescription and discontinuation of anti-platelet agents, beta-blockers, angiotensin converting enzyme (ACE) inhibitors and/or angiotensin receptor blockers (ARBs) and statins in all patients post-AMI. METHODS: Using population-based administrative databases, patients with an AMI between 1999 and 2004 (21 494 men and 13 241 women) were identified. Rates of prescriptions after discharge and time to discontinuation of the study drugs were computed for various age groups. RESULTS: The proportion of patients prescribed a study drug increased throughout the study period. In 2003-2004, 90% of patients were prescribed an anti-platelet agent, 77% a beta-blocker, 72% a statin and 70% an ACE inhibitor and/or an ARB within 30 days of discharge from their AMI. However, the rates of discontinuation increased significantly during follow-up and, in men, reached 27% by 2 years and 42% by 5 years for beta-blockers. The rates of discontinuation of all four study drugs had a parabolic shape with the youngest and oldest patients having the highest rates. CONCLUSIONS: The use of evidence-based drugs for patients after AMI is increasing. However, efforts aimed at closing the treatment gap may be mitigated by high rates of discontinuation, especially in patients at the extremes of the age spectrum.
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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 | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".