Impact of Sex on Long-term Mortality From Acute Myocardial Infarction vs Unstable Angina
Bibliographic record
Abstract
BACKGROUND: Patient sex has been shown to differentially affect mortality from unstable angina (UA) and acute myocardial infarction (AMI). However, to our knowledge, no prior population-based studies have examined both cohorts simultaneously to explain this intriguing variation. Hence, we undertook to explore and explain sex differences in 5-year mortality after UA and AMI. METHODS: We used an administrative database of 22 967 patients with AMI and 8441 patients with UA discharged from acute care hospitals in Alberta between April 1, 1993, and March 31, 2000. RESULTS: Women were older with more baseline comorbidities, more frequently had a diagnosis of UA, and had 30% lower relative odds of undergoing revascularization than men. Kaplan-Meier estimates of 5-year mortality were similar between sexes after UA (women vs men, 21.6% vs 19.5%; P =.09) but markedly higher for women after AMI (38.5% vs 26.6%, P<.001). After adjustment for baseline characteristics and revascularization, the hazard ratios (95% confidence intervals) for women vs men were 0.81 (0.72-0.92) after UA and 0.99 (0.93-1.05) after AMI. Only women younger than 65 years were at a significantly higher risk after AMI. The reasons for this difference in sex-related outcomes between UA and AMI may relate to greater disparities in the AMI cohort with respect to age, comorbidities, neighborhood incomes, and referrals to cardiovascular specialists. CONCLUSIONS: Relative to UA, AMI has a more serious impact on women than men, such that women have a survival advantage when afflicted with UA but lose that advantage with AMI. Additional investigation into the causes, treatment, and policy implications of the age-sex interaction is warranted.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".