Abstract 6083: Sex Differences in 1-Year Mortality Following Acute Coronary Syndromes
Bibliographic record
Abstract
Background : There is conflicting information whether sex modulates mortality following acute coronary syndromes (ACS). We investigated the relationships between sex, other clinical characteristics and 1-year mortality across the spectrum of ACS using a large database. Methods : Data from 6 ACS trials encompassing 1993 to 2006 were pooled. Of 81,010 patients, 21,409 (26%) were women. The ACS spectrum included 57,113 (24% women) STEMI, 13,376 (29% women) NSTEMI and 10,523 (39% women) unstable angina (UA). We compared 1-year mortality of women versus men in those surviving at least 30 days post ACS after multivariable adjustment using previously validated STEMI and NSTEMI/UA mortality models and coronary anatomy, Results : In the combined ACS population, women had higher unadjusted risk (HR 1.26, 95% CI 1.16 –1.36) compared with men. A significant interaction between sex and type of ACS was detected (P<0.001). Women had an increased unadjusted 1-year mortality risk in STEMI (HR 1.43, 95% CI 1.30 –1.58) and NSTEMI (HR 1.17, 95% CI 0.98 –1.39) but a decreased risk in UA (HR 0.84, 95% CI 0.69 –1.02) compared with men. After adjustment for baseline characteristics (age, heart rate, systolic blood pressure, weight, race, Killip class, smoking status, and history of diabetes, heart failure, myocardial infarction or bypass surgery) women had a lower risk of 1-year mortality for each type of ACS (STEMI, HR 0.86, 95% CI 0.77– 0.96; NSTEMI, HR 0.81, 95% CI 0.67– 0.97; and UA, HR 0.65, 95% CI 0.53– 0.79). After further adjustment for in-hospital procedures and coronary anatomy, hazard ratios were unchanged and mortality at 1-year remained lower for women in all ACS types. Conclusions : Sex-based differences exist in unadjusted 1-year mortality following ACS and vary by type of clinical syndrome. Adjustment for baseline differences, in-hospital procedures and coronary anatomy reveal that women are actually at lower risk for 1-year mortality compared with men across the spectrum of ACS.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".