Use of evidence-based therapies after discharge among elderly patients with acute myocardial infarction
Bibliographic record
Abstract
BACKGROUND: Postdischarge use of evidence-based drug therapies has been proposed as a measure of quality of care for myocardial infarction patients. We examined trends in the use of evidence-based drug therapies after discharge among elderly patients with myocardial infarction. METHODS: We performed a cross-sectional study in a retrospective population-based cohort that was created using linked administrative databases. We included patients aged 65 years and older who were discharged from hospital with a diagnosis of myocardial infarction between Apr. 1, 1992, and Mar. 31, 2005. We determined the annual percentage of patients who filled a prescription for statins, beta-blockers and angiotensin-modifying drugs within 90 days after discharge. RESULTS: The percentage of patients who filled a prescription for a beta-blocker increased from 42.6% in 1992 to 78.1% in 2005. The percentage of patients who filled a prescription for an angiotensin-modifying drug increased from 42.0% in 1992 to 78.4% in 2005. The percentage of patients who filled a prescription for a statin increased from 4.2% in 1992 to 79.2% in 2005. In 2005, about half of the hospitals had rates of use for each of these therapies that were less than 80%. The temporal rate of increase in statin use after discharge was slower among noncardiologists than among cardiologists (3.5%-2.8% slower). The rate of increase was 4.8% slower for among physicians with low volumes of myocardial infarction patients than among those with high volumes of such patients and was 5.7% greater at teaching hospitals compared with nonteaching hospitals. INTERPRETATION: Use of statins, beta-blockers and angiotensin-modifying drugs increased from 1992 to 2005. The rate of increase in the use of these medications after discharge varied across physician and hospital characteristics.
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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 | 0.007 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".