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Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
Published on: January 15, 2022
Clinical analysis of the risk factors of slow coronary flow
Shuang Xia1, Song-Bai Deng, Yang Wang
1Department of Cardiology, The Second Affiliated Hospital of Chongqing Medical University, 74 Lingjiang Road, Chongqing, China.
Abstract:
Slow coronary flow (SCF) phenomenon is a coronary microvascular disorder characterized by the delayed passage of contrast in the absence of obstructive epicardial coronary disease, and is an important clinical entity because it may be the cause of precordial pain when the body is at rest and/or during exercise. Although clinical and pathological features of SCF have been previously described, its etiopathogenesis remains unclear. The present study aims to investigate the risk factors of slow coronary flow, in order to provide the foundation for further exploration of potential mechanisms of SCF. A total of 47 consecutive patients with documented slow coronary flow, and 33 patients with normal coronary flow--as defined by TIMI frame count (TFC)--were recruited for this study. Clinical information was collected, and biochemical indicators including high-sensitivity C-reactive protein (hs-CRP), and a marker of systemic inflammation were detected. Logistic regression analysis was performed for statistical analysis. SCF patients had a higher level of serum uric acid (323.2 ± 79.3 vs. 282.8 ± 82.4 μmol/l, p = 0.03), 2-h postprandial blood glucose (8.6 ± 2.7 vs. 7.5 ± 1.8 mmol/l, p = 0.04), platelet count (165.9 ± 51.6 × 10(3) vs. 127.0 ± 32.0 × 10(3) cells/μl, p = 0.0003) and hs-CRP (3.4 ± 0.8 vs. 2.0 ± 0.9 mg/l, p < 0.0001) than those of patients in the control group. No marked differences in other variables were observed between the two groups. Logistic regression showed serum uric acid level (χ(2) = 3.84, β = 0.007, p = 0.049), 2-h postprandial blood glucose (χ(2) = 5.02, β = 0.277, p = 0.025) and blood platelet count (χ(2) = 12.16, β = 0.026, p = 0.001) were independent predictors of SCF. When hs-CRP was included in the multivariate model, hs-CRP (χ(2) = 21.19, β = 1.90, p < 0.0001) was the only independent predictor of SCF. These findings suggested that an elevation of serum uric acid level, 2-h postprandial blood glucose, and blood platelet count might be the causes of SCF, and inflammation was likely to be implicated in the causal pathway leading to SCF.
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