In patients without significant stenosis, SEVR ≤151.67% diagnosed CMD with 60.6% sensitivity, 88.2% specificity, and was linked to 13.88-fold increased CMD risk.
Does noninvasive subendocardial viability ratio (SEVR) accurately diagnose coronary microvascular dysfunction in patients with non-obstructive coronary artery disease?
Noninvasive measurement of subendocardial viability ratio (SEVR) provides good diagnostic accuracy for identifying coronary microvascular dysfunction in patients with non-obstructive coronary artery disease.
Tasa de eventos absoluta: 0% vs 0%
Abstract Background Coronary microvascular disease (CMD) is increasingly recognized as a critical contributor to myocardial ischemia. Subendocardial viability ratio (SEVR), derived from pulse wave analysis, provides a noninvasive assessment of myocardial oxygen supply-demand balance. While previous studies have suggested associations between SEVR and coronary blood flow, its applicable value in directly evaluating coronary microvascular function remains underexplored. Purpose This study aims to investigate the association between SEVR and coronary microvascular function, and to evaluate the diagnostic accuracy of SEVR for CMD in patients without significant functional stenosis. Methods This study enrolled patients undergoing coronary angiography and had no significant functional stenosis (coronary angiography-derived fractional flow reserve caFFR 0.80). Coronary microvascular function was assessed using coronary angiography-derived index of microcirculatory resistance (caIMR), with CMD defined as caIMR ≥25. SEVR was measured noninvasively via high-fidelity carotid tonometry as the ratio of diastolic pressure-time index to systolic pressure-time index (Figure 1A). Stepwise multivariable linear regression was used to identify independent predictors of caIMR. The diagnostic accuracy of SEVR for CMD was assessed by ROC curve analysis. Optimal cutoff values were determined by maximizing Youden's J statistic. Univariate and multivariate logistic regression analyses stratified by SEVR thresholds further assessed CMD prediction accuracy. Results A total of 134 patients was included (mean age 63.4±8.9 years, 29.9% female), and 66 patients (49.3%) had CMD. The mean SEVR was 161.66±29.60%, with significantly lower SEVR in CMD versus non-CMD patients (147.38±29.09% vs 175.52±22.85%; P0.001). SEVR exhibited significant inverse correlation with caIMR (Figure 1B). SEVR was the only independent predictor of caIMR beyond caFFR (β=-0.08, P=0.001) (Figure 2A). ROC curve analysis revealed SEVR's discriminative capacity for CMD (AUC 0.797, 95%CI 0.720-0.873) (Figure 2B), with optimal cutoff ≤151.67% yielding 60.6% sensitivity, 88.2% specificity, 83.3% positive predictive value and 69.8% negative predictive value. Multivariable logistic regression adjusting for age, sex, BMI, hypertension, dyslipidemia, diabetes, B-type natriuretic peptide and estimated glomerular filtration rate demonstrated that SEVR 151.67% was independently associated with 13.88-fold increased CMD likelihood (adjusted OR 13.88, 95%CI 5.55-39.17; P0.001) (Figure 2C). Conclusion In patients without significant functional stenosis, SEVR independently associates with coronary microvascular function assessed by caIMR. Patients with low SEVR have a significantly higher risk of CMD compared to those with high SEVR. SEVR serves as an extremely valuable non-invasive indicator diagnosing CMD. Further validation of the application value of SEVR in assessing coronary microvascular function is needed.Figure 1 (A) and (B) Figure 2 (A), (B) and (C)
Xie et al. (Sat,) reported a other. In patients without significant stenosis, SEVR ≤151.67% diagnosed CMD with 60.6% sensitivity, 88.2% specificity, and was linked to 13.88-fold increased CMD risk.
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