Abstract 3584: The Prevalence and Factors Associated With 1-Year Angina among Post-MI Patients
Bibliographic record
Abstract
Background: A primary goal of in-hospital treatment and outpatient care following myocardial infarction (MI) is the eradication of angina. However, the prevalence of angina and the factors associated with angina in the year after MI are unknown. Methods: The primary outcome of the PREMIER multi-center prospective study was presence of angina, as measured by the Seattle Angina Questionnaire (SAQ), 1 year after MI hospitalization. Multivariable regression modeling identified the socio-demographic factors, clinical history, MI presentation, inpatient therapies and complications, and outpatient treatment characteristics associated with 1-year angina, adjusted for site. . Results: Of 1957 patients in the cohort, 83 patients (4.2%) reported daily or weekly angina, and 306 patients (15.6%) reported less than weekly angina 1 year after their index MI. After multivariable analysis (figure ), angina 1 year after an index MI was associated with younger age, non-white race, baseline angina, history of CABG surgery, no inpatient revascularization, recurrent rest angina during MI hospitalization, persistent smoking after MI hospitalization, outpatient revascularization after MI hospitalization, and depressive symptoms (either as an inpatient or during the year after MI hospitalization). Conclusions: Angina 1 year after MI hospitalization is associated with several modifiable factors, including persistent smoking and depressive symptoms in the year after MI discharge. Recognition of these relationships will be important in monitoring and treating at-risk patients for post-MI angina.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".