Sex differences in prodromal symptoms in acute coronary syndrome in patients aged 55 years or younger
Bibliographic record
Abstract
BACKGROUND: Studies suggest that young women are at highest risk for failing to recognise early symptoms of acute coronary syndrome (ACS). OBJECTIVES: To examine sex differences in prodromal symptoms occurring days and weeks prior to the acute presentation of ACS. We also examined health-seeking behaviours and prehospital management in young patients. METHODS: Prospective cross-sectional analysis of 1145 patients (368 women) hospitalised for ACS, aged ≤55 years, from the GENdEr and Sex DetermInantS of Cardiovascular Disease: From Bench to Beyond Premature Acute Coronary SYndrome cohort study (January 2009-April 2013). Prodromal symptoms were determined using the McSweeney Acute and Prodromal Myocardial Infarction Symptom questionnaire. Health-seeking behaviour and prehospital care were determined by questionnaires. RESULTS: The median age was 49 years. The prevalence of prodromal symptoms was high and more women reported symptoms than men (85% vs 72%, p<0.0001). Symptoms were similar between sexes and included unusual fatigue, sleep disturbances, anxiety and arm weakness/discomfort. Chest pain was less common in both sexes (24%). Women were more likely to seek care (49% vs 42%, p=0.04). Among those who sought care, women were more likely to use an ambulance for their ACS compared with men (52% vs 39%). Cardiovascular risk-reduction therapy use was low (≤40%) in all patients and less than half perceived their care provider suspected a cardiac source. CONCLUSIONS: Prior to ACS, women were more likely to experience prodromal symptoms and seek medical attention than men. Prehospital care was generally similar between sexes but demonstrated underutilisation of risk-reduction therapies in at-risk young adults.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".