Abstract 18092: Statin Use After an Acute In-Hospital Myocardial Infarction Among Medicare Beneficiaries
Bibliographic record
Abstract
Background: American Heart Association (AHA) guidelines recommend all patients are discharged on a statin following a coronary heart disease (CHD) event. Many patients have an acute myocardial infarction (AMI) while hospitalized for another reason but the use of statins upon discharge in this population has not been well studied. Methods: Using the Medicare 5% national random sample, we identified beneficiaries who had a hospital discharge diagnosis for AMI or who underwent coronary artery bypass graft (CABG) surgery or percutaneous coronary intervention (PCI) in 2007-2009. Medicare requires the primary diagnosis code to represent the initial reason for hospitalization; secondary discharge diagnosis codes capture complications including in-hospital AMI. Beneficiaries taking and not taking statins prior to their hospitalization were analyzed separately. Filling a statin prescription within 90 days after hospital discharge was identified using Medicare Part D claims. Results: Of 5,810 and 8,517 Medicare beneficiaries taking and not taking statins prior to their CHD-related hospitalization, 84% and 55% filled a statin within 90 days of discharge, respectively. The proportion of beneficiaries filling a statin following discharge was substantially lower among those with a secondary versus primary discharge diagnosis of AMI, or PCI or CABG (Table). After multivariable adjustment, beneficiaries with a secondary discharge diagnosis of AMI were 41% (risk ratio = 0.59, 95% CI: 0.54 - 0.65) and 11% (risk ratio = 0.89; 95% CI: 0.82 - 0.97) less likely to fill a statin compared to those with a primary discharge diagnosis of AMI. Conclusion: A high percentage of Medicare beneficiaries with in-hospital AMIs do not fill statins following hospital discharge. Reasons why patients with in-hospital AMIs do fill statins following discharge need to be identified.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".