Abstract 17545: Vasoconstriction During Mental Stress Predicts Severity of Mental Stress Induced Myocardial Ischemia
Bibliographic record
Abstract
Background: Evidence supports that peripheral vasoconstriction during mental stress predicts mental stress induced ischemia (MSIMI). However, whether a dose response relationship exists with ischemia severity has not been evaluated; additionally, whether peripheral vascular function during the recovery phase is also related to MSIMI is not known. Hypothesis: We hypothesized that increased digital microvascular constriction during both mental stress and recovery are predictive of increased severity of mental stress ischemia. Methods: We evaluated 204 patients with stable CAD with high quality vascular data using a standardized mental stress test using a public speaking task. Peripheral artery tonometry (PAT) (Itamar Inc) was used to assess digital microvascular tone. Vasoconstriction was calculated as the ratio of pulse wave amplitude during speech/recovery and the last 3 minutes of baseline, with lower ratio indicating more vasoconstriction. 99mTc sestamibi myocardial perfusion imaging was performed at rest and with mental stress. A summed difference score (SDS) quantifying severity of reversible perfusion defects (inducible ischemia) comparing rest and stress images was computed using a standard 17-segment model. Four categories of increasing severity were based on cut points of 0, 3, and 6. Results: The mean (SD) age was 64 (8), 16% were women, and 28% were African American. Each category of increase in ischemia severity was associated with a 10% (p=0.04) decrease in speech PAT ratio (Figure) and 11% (p=0.02) decrease in recovery PAT ratio. After multivariable adjustment for sociodemographics, traditional risk factors, medical history, medication use, and psychological risk factors, the associations persisted, with B=-11%, p=0.02 for speech PAT ratio, and B=-8%, p=0.04 for recovery ratio. Conclusion: Peripheral vasoconstriction during mental stress speech as well as recovery predicts MSI severity in a dose-response relationship.
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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) | 0.005 | 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".