Soluble Vascular Cell Adhesion Molecule-1 as an Inflammation-Related Biomarker of Coronary Slow Flow.

Background: Coronary slow flow (CSF) is an angiographic entity characterized by delayed coronary opacification with no evident obstructive lesion in the epicardial coronary artery. Several studies have shown that the occurrence and development of CSF may be closely related to inflammation. Soluble vascular cell adhesion molecule-1 (sVCAM-1) is a biomarker related to inflammation. The aim of this study was to evaluate the correlation between plasma soluble VCAM-1 level and CSF occurrence and thus the predictive value of VCAM-1 for CSF. Methods: Forty-six CSF patients and thirty control subjects were enrolled. Corrected thrombolysis in myocardial infarction frame count (cTFC) was used to diagnose CSF. Functional status and quality of life were determined by the Seattle Angina Questionnaire (SAQ). Echocardiography was used to evaluate the systolic and diastolic function of the left ventricle (LV) and right ventricle (RV). The plasma levels of sVCAM-1, IL-6, and TNF-α were quantified by enzyme-linked immunosorbent assay. Results: Compared with the control group, the physical limitation score by the SAQ, the LV global longitudinal strain (GLS), mitral E, and mitral E/A decreased in patients with CSF, while the plasma IL-6 and TNF-α levels increased. The plasma sVCAM-1 level in the CSF group was significantly higher than that in the control group (186.03 ± 83.21 vs. 82.43 ± 42.12 ng/mL, p < 0.001), positively correlated with mean cTFC (r = 0.57, p < 0.001), and negatively correlated with the physical limitation score (r = −0.32, p = 0.004). Logistic regression analyses confirmed that plasma sVCAM-1 level (OR = 1.07, 95%CI: 1.03−1.11) is an independent predictor of CSF, and the receiver operating characteristic curve analysis showed that plasma sVCAM-1 levels had statistical significance in predicting CSF (area under curve = 0.88, p < 0.001). When the sVCAM-1 level was higher than 111.57 ng/mL, the sensitivity for predicting CSF was 87% and the specificity was 73%. Conclusions: Plasma sVCAM-1 level can be used to predict CSF and was associated with the clinical symptoms of patients. It may serve as a potential biomarker for CSF in the future.