The Importance of Nontraditional and Sex-Specific Risk Factors in Young Women With Vasomotor Nonobstructive vs Obstructive Coronary Syndromes
Bibliographic record
Abstract
Background: Heart disease is the leading cause of premature death for women in Canada. Ischemic heart disease is categorized as myocardial infarction (MI) with no obstructive coronary artery disease (MINOCA), ischemia with no obstructive coronary arteries (INOCA), and atherosclerotic obstructive coronary artery disease (CAD) with MI (MI-CAD) or without MI (non-MI-CAD). This study aims to study the prevalence of traditional and nontraditional ischemic heart disease risk factors and their relationships with (M)INOCA, compared to MI-CAD and non-MI-CAD in young women. Methods: olumbia (SAVEBC). Univariable and multivariable regression models were applied to investigate associations of risk factors with odds of (M)INOCA, MI-CAD, and non-MI-CAD. Results: A total of 254 women enrolled between 2015 and 2022 were analyzed, as follows: 77 with INOCA and 37 with MINOCA from the registry, and 66 with non-MI-CAD and 74 with MI-CAD from the study. Regression analyses demonstrated that migraines and preeclampsia or gestational hypertension were the most significant risk factors, with a higher likelihood of being associated with premature (M)INOCA, relative to obstructive CAD. Conversely, the presence of diabetes and a current or previous smoking history had the highest likelihood of being associated with premature CAD. Conclusions: The risk factor profiles of patients with premature (M)INOCA, compared to obstructive CAD, have significant differences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".