Follow-up Dosing of Guideline-Indicated Medications After Myocardial Infarction: Insights from the Acute Myocardial Infarction Quality Assurance (AMIQA) Canada Study
Bibliographic record
Abstract
Background: Achieving the target doses of indicated medications after myocardial infarction (MI) is associated with improved outcomes and is a marker of the quality of care. We studied the use and follow-up dosing of core cardiac medications among patients with MI complicated by depressed left ventricular ejection fraction (LVEF). Our objective was to determine whether adherence to evidence-based medication dosing is associated with receipt of follow-up LVEF imaging or progression of LVEF within 6 months of follow-up care. Methods: The Acute Myocardial Infarction Quality Assurance (AMIQA) Canada study enrolled 501 patients (mean age 63 years; 22.6% female) with acute MI and LVEF ≤ 45%, from 14 Canadian centres. Patients were followed for 6 months to determine their adherence to post-MI follow-up recommendations. We assessed use and dosing of beta-blockers, angiotension-converting enzyme inhibitors, angiotensin II receptor blockers, mineralocorticoid receptor antagonists (MRAs), and statins, and compared changes in LVEF among those taking ≥50% vs < 50% of the target dose in the follow-up period. Results: < 0.001). Receiving ≥ 50% of the target dose was not associated with changes in LVEF. Conclusions: Except for statins, most patients were not receiving target doses of indicated medications after MI with reduced LVEF. Follow-up dosing was not associated with LVEF reassessment or improvement in LVEF. Future quality-improvement initiatives may require distinct strategies for improving adherence to recommendations for medication dosing vs follow-up imaging.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".