Cardiovascular Reactivity to Mental Stress and Adverse Cardiovascular Outcomes in Patients With Coronary Artery Disease
Bibliographic record
Abstract
Background Acute psychological stress may induce physiological changes predisposing individuals to adverse health outcomes through hemodynamic and vascular effects. We studied the association between the aggregated stress‐induced changes in hemodynamic and vascular function tests with adverse cardiovascular outcomes in patients with coronary artery disease, after adjusting for sociodemographic and clinical factors. Methods and Results Individuals with stable coronary artery disease from 2 prospective cohort studies were studied. Hemodynamic reactivity, changes in endothelial function, and vasoconstriction during mental stress were evaluated using changes in rate‐pressure product, brachial artery flow‐mediated vasodilation, and peripheral arterial tonometry, respectively. A cardiovascular reactivity risk score was calculated by allotting 0 to 3 points for each quartile of increasing abnormality for each of the 3 reactivity responses and summing the quartile points from the MIPS (Mental Stress Ischemia Prognosis Study) to yield a cardiovascular reactivity risk score ranging from 0 to 9. The outcome was a composite of cardiovascular death, nonfatal myocardial infarction, and heart failure hospitalizations during follow‐up. A total of 629 participants were included. After adjustment for demographic and traditional risk factors, a blunted hemodynamic response, a greater decrease in flow‐mediated vasodilation, and a greater degree of peripheral vasoconstriction to mental stress were all independently associated with a higher risk of adverse outcomes in both cohorts. By adding the cardiovascular reactivity risk score, the C‐statistic increased significantly by 10% ( P <0.001). Conclusions Among individuals with stable coronary artery disease, a risk score derived from cardiovascular reactivity to mental stress was predictive of adverse cardiovascular outcomes beyond traditional cardiovascular risk factors.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".