Adherence to Guidelines for Cardiac Catheterization Referrals and Secondary Prevention Strategies in Patients with Non-ST Segment Elevation Acute Coronary Syndromes
Bibliographic record
Abstract
Summary Background: Previous studies have demonstrated higher referral rates for invasive procedures among patients admitted with acute coronary syndromes (ACS) to hospitals with catheterization facilities compared to those without. Studies have also reported underuse of evidence-based medical therapies and cardiac rehabilitation programs post myocardial infarction. We evaluated referral patterns for cardiac catheterization and use of secondary prevention strategies in current practice. Methods: We conducted a retrospective study of 397 patients with non-ST segment elevation ACS, comparing angiography referrals at a hospital with on-site catheterization facilities (Site A, n = 194) versus a hospital without (Site B, n = 203). We also recorded the use of secondary prevention strategies including discharge medications, referrals to smoking cessation programs and cardiac rehabilitation. Results: There was no significant effect of on-site angiography on the decision to manage patients invasively (adjusted OR for on-site angiography 1.49 95% CI 0.92-2.44, p = .11), or wait times for cardiac catheterization (Site A 1.9 days vs. Site B 2.2 days, difference -0.3 days, 95% CI -0.83 to 0.55, p = .70). However, at the time of hospital discharge, less than 70% of patients were prescribed dual antiplatelet therapy and only 13% of patients were referred for cardiac rehabilitation. Conclusion: These observations suggest that in contemporary practice in a Southern Ontario community, the availability of on-site percutaneous coronary intervention does not influence referral rates or wait times for cardiac catheterization. However we did observe significant underuse of cardiac rehabilitation programs and certain medical therapies. This suggests that despite improvements in access to invasive procedures, there remain important gaps in secondary prevention of coronary artery disease, which represent opportunities to improve quality of care in these patients.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".