Sex Differences in Acute Coronary Syndrome Symptom Presentation in Young Patients
Bibliographic record
Abstract
IMPORTANCE: Little is known about whether sex differences in acute coronary syndrome (ACS) presentation exist in young patients and what factors determine absence of chest pain in ACS presentation. OBJECTIVES: To evaluate sex differences in ACS presentation and to estimate associations between sex, sociodemographic, gender identity, psychosocial and clinical factors, markers of coronary disease severity, and absence of chest pain in young patients with ACS. DESIGN, SETTING, PARTICIPANTS: We conducted a prospective cohort study of 1015 patients (30% women) 55 years or younger, hospitalized for ACS and enrolled in the GENESIS PRAXY (Gender and Sex Determinants of Cardiovascular Disease: From Bench to Beyond Premature Acute Coronary Syndrome) study (January 2009-September 2012). MAIN OUTCOMES AND MEASURES: The McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey was administered during hospitalization. RESULTS: The median age for both sexes was 49 years. Women were more likely to have non-ST-segment elevation myocardial infarction (37.5 vs 30.7; P = .03) and present without chest pain compared with men (19.0% vs 13.7%; P = .03). Patients without chest pain reported fewer symptoms overall and no discernable pattern of non-chest pain symptoms was found. In the multivariate model, being a woman (odds ratio [OR], 1.95 [95% CI, 1.23-3.11]; P = .005) and tachycardia (OR, 2.07 [95% CI, 1.20-3.56]; P = .009) were independently associated with ACS presentation without chest pain. Patients without chest pain did not differ significantly from those with chest pain in terms of ACS type, troponin level elevation, or coronary stenosis. CONCLUSIONS AND RELEVANCE: Chest pain was the most common ACS symptom in both sexes. Although women were more likely to present without chest pain than men, absence of chest pain was not associated with markers of coronary disease severity. Strategies that explicitly incorporate assessment of common non-chest pain symptoms need to be evaluated.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".