Sex Differences in Mental Stress–Induced Myocardial Ischemia in Young Survivors of an Acute Myocardial Infarction
Bibliographic record
Abstract
OBJECTIVES: Emotional stress may disproportionally affect young women with ischemic heart disease. We sought to examine whether mental stress-induced myocardial ischemia (MSIMI), but not exercise-induced ischemia, is more common in young women with previous myocardial infarction (MI) than in men. METHODS: We studied 98 post-MI patients (49 women and 49 men) aged 38 to 60 years. Women and men were matched for age, MI type, and months since MI. Patients underwent technetium-99m sestamibi perfusion imaging at rest, after mental stress, and after exercise/pharmacological stress. Perfusion defect scores were obtained with observer-independent software. A summed difference score (SDS), the difference between stress and rest scores, was used to quantify ischemia under both stress conditions. RESULTS: Women 50 years or younger, but not older women, showed a more adverse psychosocial profile than did age-matched men but did not differ for conventional risk factors and tended to have less angiographic coronary artery disease. Compared with age-matched men, women 50 years or younger exhibited a higher SDS with mental stress (3.1 versus 1.5, p = .029) and had twice the rate of MSIMI (SDS ≥ 3; 52% versus 25%), whereas ischemia with physical stress did not differ (36% versus 25%). In older patients, there were no sex differences in MSIMI. The higher prevalence of MSIMI in young women persisted when adjusting for sociodemographic and life-style factors, coronary artery disease severity, and depression. CONCLUSIONS: MSIMI post-MI is more common in women 50 years or younger compared with age-matched men. These sex differences are not observed in post-MI patients who are older than 50 years.
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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 | 0.000 | 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) | 0.002 | 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".