Gender differences in symptoms of myocardial ischaemia
Bibliographic record
Abstract
AIMS: Better understanding of symptoms of myocardial ischaemia is needed to improve timeliness of treatment for acute coronary syndromes (ACS). Although researchers have suggested sex differences exist in ischaemic symptoms, methodological issues prevent conclusions. Using percutaneous coronary intervention (PCI) balloon inflation as a model of myocardial ischaemia, we explored sex differences in reported symptoms of ischaemia. METHODS AND RESULTS: Patients having non-emergent PCI, but not haemodynamic instability or left bundle branch block or non-acute coronary occlusion, were prospectively recruited. Pre-procedure, descriptions of pre-existing symptoms were obtained using open-ended questioning. Inflation was maintained for 2 min or until moderate discomfort or clinical instability occurred. During inflation, subjects were exhaustively questioned about their symptoms. Concurrent ECG data were collected. The final sample was 305 [39.7% women; mean age 63.9 (± 10.6)]. No sex differences were found in rates of chest or typical ischaemic discomfort, regardless of ischaemic status. Women were significantly more likely to report throat/jaw discomfort [odds ratio: 2.91; 95% confidence interval: 1.58-5.37] even after statistical adjustment for clinical and demographic variables. CONCLUSION: This prospective study with ECG-affirmed ischaemia found no statistically significant differences in women's and men's rates of chest and other typical symptoms during ischaemia, although women were more likely to experience throat and jaw discomfort. Currently both popular press and some patient education materials suggest women experience myocardial ischaemia differently from men. Steps to ensure women and health professionals are alert for the classic symptoms of myocardial ischaemia in women, as well as men, may be 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.006 | 0.001 |
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".