Brachial Artery Constriction during Brachial Artery Reactivity Testing Predicts Major Adverse Clinical Outcomes in Women with Suspected Myocardial Ischemia: Results from the NHLBI-Sponsored Women’s Ischemia Syndrome Evaluation (WISE) Study
Bibliographic record
Abstract
BACKGROUND: Limited brachial artery (BA) flow-mediated dilation during brachial artery reactivity testing (BART) has been linked to increased cardiovascular risk. We report on the phenomenon of BA constriction (BAC) following hyperemia. OBJECTIVES: To determine whether BAC predicts adverse CV outcomes and/or mortality in the women's ischemic Syndrome Evaluation Study (WISE). Further, as a secondary objective we sought to determine the risk factors associated with BAC. METHODS: We performed BART on 377 women with chest pain referred for coronary angiography and followed for a median of 9.5 years. Forearm ischemia was induced with 4 minutes occlusion by a cuff placed distal to the BA and inflated to 40mm Hg > systolic pressure. BAC was defined as >4.8% artery constriction following release of the cuff. The main outcome was major adverse events (MACE) including all-cause mortality, non-fatal MI, non-fatal stroke, or hospitalization for heart failure. RESULTS: BA diameter change ranged from -20.6% to +44.9%, and 41 (11%) women experienced BAC. Obstructive CAD and traditional CAD risk factors were not predictive of BAC. Overall, 39% of women with BAC experienced MACE vs. 22% without BAC (p=0.004). In multivariate Cox proportional hazards regression, BAC was a significant independent predictor of MACE (p=0.018) when adjusting for obstructive CAD and traditional risk factors. CONCLUSIONS: BAC predicts almost double the risk for major adverse events compared to patients without BAC. This risk was not accounted for by CAD or traditional risk factors. The novel risk marker of BAC requires further investigation in women.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| 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".