Impaired Peripheral Microvascular Function and Risk of Major Adverse Cardiovascular Events in Patients With Coronary Artery Disease
Bibliographic record
Abstract
Objective: In patients with stable coronary artery disease (CAD), the risk of major adverse cardiovascular events (MACE) remains elevated despite treatment. The role of microvascular dysfunction on MACE beyond traditional risk indicators and inflammation is not well established. We examined whether peripheral microvascular dysfunction is associated with MACE in patients with CAD. Approach and Results: Microvascular function was measured with the Reactive Hyperemia Index (RHI) using digital peripheral arterial tonometry in 546 patients with CAD, who were followed 7 years for incident MACE. The primary end point included cardiovascular death or myocardial infarction; the secondary end point included cardiovascular death, myocardial infarction, or heart failure hospitalization. Hazard models for competing risk were used to estimate the association between RHI and MACE adjusting for age, sex, race, traditional risk factors, medications, and CAD severity. We also examined the association of baseline interleukin-6, C-reactive protein, monocyte chemoattractant protein-1, and matrix metallopeptidase-9 with RHI. Mean age was 62±9 years. Mean RHI was 2.1±0.63. After adjustment, for each 1-SD decrease in RHI, there was a 40% increase in the primary end point (hazard ratio, 1.4 [95% CI, 1.1–1.9], P =0.01) and a similar increase in the secondary end point (HR, 1.3 [95% CI, 1.1–1.7], P =0.006). Inflammatory biomarker levels were associated with greater RHI impairment ( P <0.05) but did not affect the relationship between RHI and MACE. Conclusions: Peripheral microvascular dysfunction is associated with increased risk of MACE in patients with stable CAD, implicating the role of microvascular disease in the pathogenesis of adverse outcomes in patients with CAD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".