MAR与ACS患者冠脉病变严重程度的相关性研究

Association between Monocyte-to-Albumin Ratio and Severity of Coronary Artery Disease in Patients with Acute Coronary Syndrome

摘要: 目的：探讨单核细胞/白蛋白比值(monocyte-to-albumin ratio, MAR)与急性冠脉综合征(acute coronary syndrome, ACS)患者冠脉病变严重程度的相关性，并评估其辅助分层评估的价值。方法：纳入4234例ACS患者，根据Gensini评分中位数将患者分为严重与非严重冠脉病变组。采用Spearman相关分析及单因素和多因素Logistic回归模型探讨MAR与冠脉病变严重程度的关系，并通过受试者工作特征(ROC)曲线评估MAR单独及联合传统危险因素对严重冠脉病变的预测效能。结果：严重冠脉病变组MAR水平显著高于非严重组(11.81 vs. 9.64, P < 0.001)，且MAR四分位数越高，Gensini评分越高(P for trend < 0.001)。多因素Logistic回归显示，MAR最高四分位组(Q4)的冠脉病变风险较Q1增加56% (OR = 1.562, 95% CI: 1.280~1.907, P < 0.001)。ROC分析表明，MAR联合传统危险因素可显著提升预测效能(AUC = 0.663 vs. 0.624, P < 0.001)。结论：MAR水平与ACS患者冠脉病变严重程度呈独立正相关，且联合传统危险因素后可提高严重冠脉病变的识别能力，提示其在临床辅助分层评估中具有潜在应用价值。

Abstract: Objective: To investigate the association between the monocyte-to-albumin ratio (MAR) and the severity of coronary artery disease (CAD) in patients with acute coronary syndrome (ACS), and to evaluate its potential value in assisting risk stratification. Methods: A total of 4234 ACS patients were enrolled. Patients were divided into severe and non-severe CAD groups based on the median Gensini score. Spearman correlation analysis and univariate and multivariate logistic regression models were used to explore the relationship between MAR and CAD severity. The predictive value of MAR alone and in combination with traditional risk factors for severe CAD was assessed using receiver operating characteristic (ROC) curve analysis. Results: MAR levels were significantly higher in the severe CAD group compared with the non-severe group (11.81 vs. 9.64, P < 0.001), and higher MAR quartiles were associated with higher Gensini scores (P for trend < 0.001). Multivariate logistic regression analysis showed that patients in the highest MAR quartile (Q4) had a 56% increased risk of severe CAD compared with those in the lowest quartile (Q1) (OR = 1.562, 95% CI: 1.280~1.907, P < 0.001). ROC analysis demonstrated that combining MAR with traditional risk factors significantly improved predictive performance (AUC = 0.663 vs. 0.624, P < 0.001). Conclusion: MAR is independently and positively associated with the severity of CAD in ACS patients. Incorporating MAR with traditional risk factors may enhance the identification of severe CAD, suggesting its potential value in clinical risk stratification.