Societal, occupational, and economic considerations for women with (M)INOCA: a narrative review
Bibliographic record
Abstract
Cardiovascular disease is one of the leading causes of mortality in women, despite underrepresentation in the medical literature. Women have higher rates of ischemia and no obstructive coronary artery disease (INOCA) and myocardial infarction with no obstructive coronary artery disease (MINOCA) compared to men. The aim of this review is to describe the occupational, economic, and psychosocial factors which disproportionately impact women with (M)INOCA. Relevant databases including MEDLINE, EMBASE, and CINAHL were searched using keywords related to ischemic heart disease, nonobstructive coronary syndromes, (M)INOCA, women's health, questionnaires and surveys, cohort studies, workplace outcomes, and health costs. This narrative review includes key findings from 50 articles that fit the inclusion criteria. Sex-based differences among patients with nonobstructive coronary syndromes are discussed in the context of health care service utilization, working status, and job characteristics. Despite lower mortality rates, nonobstructive coronary syndromes are associated with a large burden of clinical, functional, and economic implications. Women face significant morbidity, productivity losses, and early exit from the workforce. Existing literature focuses on ischemic heart disease as an entity without specific attention to (M)INOCA, and recent health economic studies are lacking. Despite growing recognition of (M)INOCA endotypes and improved diagnostic modalities, its economic and societal impacts remain under-researched, highlighting the need for validated tools to measure work impairment. Collaborative efforts including workplace and employer participation are needed to address work-related outcomes. Researchers and institutions need to consider the interplay of sex-based differences and societal impacts on women. Int J Occup Med Environ Health. 2025;38(3):207-221.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".