Statin Use Following Hospitalization Among Medicare Beneficiaries With a Secondary Discharge Diagnosis of Acute Myocardial Infarction
Bibliographic record
Abstract
BACKGROUND: Patients with coronary heart disease are recommended to use statins following hospital discharge. Acute myocardial infarction (AMI) is a common complication of hospitalization, but the use of statins following discharge among patients who were not initially hospitalized for AMI has not been assessed adequately. METHODS AND RESULTS: Using the Medicare 5% national random sample, we determined statin use among beneficiaries who were hospitalized and who had a secondary discharge diagnosis of AMI and among beneficiaries who had a primary discharge diagnosis of AMI, coronary artery bypass grafting, or percutaneous coronary intervention in 2007-2009. Statin use was defined by a pharmacy (Medicare Part D) claim within 90 days following discharge. Of 8175 Medicare beneficiaries who did not take statins prior to hospitalization, 31.2% with AMI as a secondary discharge diagnosis, 60.5% with AMI as the primary discharge diagnosis, 67.6% with coronary artery bypass grafting, and 63.9% with a percutaneous coronary intervention initiated statins. After multivariable adjustment, the risk ratio for statin initiation comparing beneficiaries with a secondary versus primary discharge diagnosis of AMI was 0.59 (95% CI 0.54 to 0.65). Among 5468 Medicare beneficiaries taking statins prior to hospitalization, statin use following discharge was lower for those with AMI as a secondary discharge diagnosis (71.8%) compared with their counterparts with AMI, coronary artery bypass grafting, and percutaneous coronary intervention (84.1%, 83.8%, and 87.3%, respectively) as the primary discharge diagnosis. CONCLUSION: Medicare beneficiaries with a secondary hospital discharge diagnosis of AMI were less likely to fill statins compared with those with other coronary heart disease 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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".