4.6 Article

Identification of predictors for the comprehensive clinical risk and severity of coronary lesions of acute coronary syndrome

Journal

FRONTIERS IN CARDIOVASCULAR MEDICINE
Volume 10, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fcvm.2023.1046895

Keywords

predictor; acute coronary syndrome; coronary artery disease; GRACE score; SYNTAX score

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This study analyzed the clinical data of 225 ACS patients using GRACE and SYNTAX scores, and identified AST, total cholesterol, RDW, and prealbumin as predictors for the severity of coronary lesions and comprehensive clinical risk.
BackgroundAcute coronary syndrome (ACS) is the most common cause of death in patients with coronary artery disease. The aim of the study was to identify the predictors of both comprehensive clinical risk and severity of coronary lesions by comprehensive use of GRACE and SYNTAX scores in patients with ACS.MethodsClinical data of 225 ACS patients who underwent coronary angiography between 2015 and 2016 were collected. Multiple logistic regression analysis (stepwise) was used to identify the predictors. The predictive ability of predictors and the model were determined using receiver operating characteristics analyses.ResultsMultivariable logistic regression analyses showed that high aspartate aminotransferase (AST) predicted the comprehensive clinical risk with odds ratios (ORs) and 95% confidence intervals (CIs) of 1.011 (1.002-1.021). High total cholesterol (TC) and red blood cell distribution width (RDW) predicted the severity of coronary lesions with ORs and 95% CIs of 1.517 (1.148-2.004) and 1.556 (1.195-2.028), respectively. Low prealbumin predicted both severity of coronary lesions and comprehensive clinical risk of ACS patients with ORs and 95% CIs of 0.743 (0.672-0.821) and 0.836 (0.769-0.909), respectively. The model with a combination of prealbumin and AST had the highest predictive efficacy for comprehensive clinical risk, and the combination of prealbumin, TC, and RDW had the highest predictive efficacy for the severity of coronary lesions. The sensitivity and specificity, and the optimal cut-off values of these four indexes were determined.ConclusionsFour predictors for the comprehensive clinical risk and severity of coronary lesions of ACS were identified, which provided important information for the early diagnosis and appropriate treatment of ACS.

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