Sex Differences in Hemodynamic and Microvascular Mechanisms of Myocardial Ischemia Induced by Mental Stress
Bibliographic record
Abstract
OBJECTIVE: To investigate sex-specific vascular mechanisms for mental stress-induced myocardial ischemia (MSIMI). APPROACH AND RESULTS: Baseline data from a prospective cohort study of 678 patients with coronary artery disease underwent myocardial perfusion imaging before and during a public speaking stressor. The rate-pressure product response was calculated as the difference between the maximum value during the speech minus the minimum value during rest. Peripheral vasoconstriction by peripheral arterial tonometry was calculated as the ratio of pulse wave amplitude during the speech over the resting baseline; ratios <1 indicate a vasoconstrictive response. MSIMI was defined as percent of left ventricle that was ischemic and as a dichotomous variable. Men (but not women) with MSIMI had a higher rate-pressure product response than those without MSIMI (6500 versus 4800 mm Hg bpm), whereas women (but not men) with MSIMI had a significantly lower peripheral arterial tonometry ratio than those without MSIMI (0.5 versus 0.8). In adjusted linear regression, each 1000-U increase in rate-pressure product response was associated with 0.32% (95% confidence interval, 0.22-0.42) increase in inducible ischemia among men, whereas each 0.10-U decrease in peripheral arterial tonometry ratio was associated with 0.23% (95% confidence interval, 0.11-0.35) increase in inducible myocardial ischemia among women. Results were independent of conventional stress-induced myocardial ischemia. CONCLUSIONS: Women and men have distinct cardiovascular reactivity mechanisms for MSIMI. For women, stress-induced peripheral vasoconstriction with mental stress, and not increased hemodynamic workload, is associated with MSIMI, whereas for men, it is the opposite. Future studies should examine these pathways on long-term outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".