Abstract P294: Greater Peripheral Vasoconstriction During Mental Stress Predicts Adverse Cardiovascular Outcomes
Bibliographic record
Abstract
Introduction: Peripheral arterial vasoconstriction during mental stress (MS) has been associated with mental stress-induced myocardial ischemia, which in turn has been linked with worse cardiovascular outcomes. It is unknown whether the magnitude of peripheral vasoconstriction with MS is predictive of long term outcomes. Hypothesis: We hypothesized that greater peripheral arterial vasoconstriction during MS would be associated with adverse events among patients with coronary artery disease (CAD). Methods: Four hundred sixty-three patients with stable CAD and normal left ventricular function, (age 63±9, 75% male, 27% Black, EF 60±8 %) underwent MS testing with a standardized public speaking stressor. Digital pulse wave amplitude was continuously measured at baseline and during MS using peripheral arterial tonometry (PAT), and the PAT ratio of pulse wave amplitude (during mental stress/ baseline) was calculated. Cox proportional hazard models were calculated to examine the association between the PAT ratio and outcomes. Results: Median PAT ratio during MS was 0.68, indicating 32% average constriction with MS compared to rest. Subjects with greater peripheral constriction [low ( Conclusion: Greater peripheral arterial vasoconstriction with MS is associated with a higher risk of adverse cardiovascular outcomes in patients with CAD.
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 | 0.000 | 0.001 |
| 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) | 0.005 | 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".