Abstract P155: Risk for Recurrent Events Among Patients Receiving Intensive Medical Management Following Myocardial Infarction
Bibliographic record
Abstract
Background: Randomized trials have shown that several medications reduce the risk for recurrent coronary heart disease (CHD) events following myocardial infarction (MI). Knowing the risk for recurrent events among patients receiving intensive medical management following MI can inform patient-physician shared decision making. Objective: To estimate the risk for CHD events among patients receiving intensive medical management following an MI hospitalization. Methods: We identified US adults 18-64 years with commercial health insurance in Marketscan who had an MI hospitalization (defined by an ICD-9 code of 410.x0 or 410.x1 in the primary discharge diagnosis position) in 2014-2015. Intensive medical management was defined as filling a high-intensity statin, renin-angiotensin system inhibitor, beta-blocker and antiplatelet agent within 30 days following hospital discharge for MI. Patients receiving intensive medical management were matched 1:2 by age, sex and calendar year to randomly selected controls from the general population and followed for recurrent MI and CHD events (i.e., MI or coronary revascularization). Results: Among MI patients (n=17,643, mean age 55 years, 74% male), 29.6% received intensive medical management. After adjustment for comorbid conditions, intensive medical management was more common among men (relative risk [95% CI] 1.14 [1.07, 1.20]), those who received a stent during their MI hospitalization (2.54 [2.37, 2.73]) and those who received cardiologist care (1.17 [1.11, 1.22]) and cardiac rehabilitation (1.14 [1.08, 1.20]) after hospital discharge. The risk for recurrent MI and CHD events was higher among MI patients receiving intensive medical management compared to controls, overall and when restricted to MI patients with high medication adherence ( Table ). Conclusion: MI patients receiving intensive medical management have a substantial residual risk for recurrent CHD events.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".