Arterial stiffness assessment in coronary microvascular dysfunction and heart failure with preserved ejection fraction: An initial report from the WISE-CVD continuation study
Bibliographic record
Abstract
Heart failure with preserved ejection fraction (HFpEF) is the most common cardiac complication in patients with coronary microvascular dysfunction (CMD), yet its underlying pathways remain unclear. Aortic pulse-wave velocity (aPWV) is an indicator of large artery stiffness and a predictor for cardiovascular disease. However, aPWV in CMD and HFpEF is not well characterized and may provide understanding of disease progression. Among participants without obstructive coronary artery disease, we evaluated 51 women with suspected CMD and 20 women and men with evidence of HFpEF. All participants underwent aPWV measurement (SphygmoCor, Atcor Medical) with higher aPWV indicating greater vascular stiffness. Cardiac magnetic resonance imaging (CMRI) assessed left ventricular (LV) ejection fraction, CMD via myocardial perfusion reserve index (MPRI), and ventricular remodeling via LV mass-volume ratio. . Statistical analysis was performed using Wilcoxon rank sum tests, Pearson correlations and linear regression analysis. Compared to the suspected CMD group, the HFpEF participants were older (65 ± 12 vs 56 ± 11 yrs., p = 0.002) had higher BMI (31.0 ± 4.3 vs 27.8 ± 6.7 kg/m2, p = 0.013), higher aPWV (10.5 ± 2.0 vs 8.0 ± 1.6 m/s, p = 0.05) and lower MPRI (1.5 ± 0.3 vs1.8 ± 0.3, p = 0.02), but not remodeling. In a model adjusted for cardiovascular risk factors, the HFpEF group had a lower LVEF (estimate −4.78, p = 0.0437) than the suspected CMD group. HFpEF participants exhibit greater arterial stiffness and lower myocardial perfusion reserve, with lower LVEF albeit not remodeling, compared to suspected CMD participants. These findings suggest arterial stiffness may contribute to progression from CMD to HFpEF. Prospective work is needed and ongoing.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".