Trends in Recurrent Coronary Heart Disease After Myocardial Infarction Among US Women and Men Between 2008 and 2017
Bibliographic record
Abstract
Background: Rates for recurrent coronary heart disease (CHD) events have declined in the United States. However, few studies have assessed whether this decline has been similar among women and men. Methods: Data were used from 770 408 US women and 700 477 US men <65 years of age with commercial health insurance through MarketScan and ≥66 years of age with government health insurance through Medicare who had a myocardial infarction (MI) hospitalization between 2008 and 2017. Women and men were followed up for recurrent MI, recurrent CHD events (ie, recurrent MI or coronary revascularization), heart failure hospitalization, and all-cause mortality (Medicare only) in the 365 days after MI. Results: From 2008 to 2017, age-standardized recurrent MI rates per 1000 person-years decreased from 89.2 to 72.3 in women and from 94.2 to 81.3 in men (multivariable-adjusted P interaction by sex <0.001). Recurrent CHD event rates decreased from 166.3 to 133.3 in women and from 198.1 to 176.8 in men ( P interaction <0.001). Heart failure hospitalization rates decreased from 177.4 to 158.1 in women and from 162.9 to 156.1 in men ( P interaction=0.001). All-cause mortality rates decreased from 403.2 to 389.5 in women and from 436.1 to 417.9 in men ( P interaction=0.82). In 2017, the multivariable-adjusted rate ratios comparing women with men were 0.90 (95% CI, 0.86–0.93) for recurrent MI, 0.80 (95% CI, 0.78–0.82) for recurrent CHD events, 0.99 (95% CI, 0.96–1.01) for heart failure hospitalization, and 0.82 (95% CI, 0.80–0.83) for all-cause mortality. Conclusions: Rates of recurrent MI, recurrent CHD events, heart failure hospitalization, and mortality in the first year after an MI declined considerably between 2008 and 2017 in both men and women, with proportionally greater reductions for women than men. However, rates remain very high, and rates of recurrent MI, recurrent CHD events, and death continue to be higher among men than women.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".