作者：涂光，黄小密，曾艳芳，王能，童随阳，钱进

单位：

湖北医药学院附属随州医院心血管内科

Units：

Department of Cardiovascular Medicine, Suizhou Hospital Affiliated to Hubei University of Medicine, Suizhou 441300, China

关键词：

冠状动脉疾病; 冠状动脉慢血流; 中性粒细胞/高密度脂蛋白比值;

Keywords：

Coronary artery disease; Coronary slow flow; Neutrophils to high density liptein ratio

CLC：

DOI：

10.12114/j.issn.1008-5971.2023.00.025

Funds：

湖北省自然科学基金资助项目（2020CFB179）； 湖北省卫生健康委员会指导性项目（WJ2019F133）；

摘要：

目的 探讨中性粒细胞与高密度脂蛋白比值（NHR）对冠状动脉慢血流（CSF）的预测价值。方法回顾性选取2020年6月至2022年3月因胸痛于湖北医药学院附属随州医院行冠状动脉造影（CAG）检查的患者166例为研究对象，根据CAG检查结果将其分为CSF组83例和对照组83例。收集患者的临床资料，包括年龄、性别、吸烟史、饮酒史、高血压病史、糖尿病病史、BMI、淋巴细胞计数、血小板计数、超敏C反应蛋白、总胆固醇、三酰甘油、LDL-C、ALT、AST、尿素氮、血肌酐、血尿酸、同型半胱氨酸、空腹血糖、左心室射血分数（LVEF）、NHR。采用多因素Logistic回归分析探讨CSF的影响因素，绘制ROC曲线以评估NHR预测CSF的效能。结果 两组性别、有吸烟史者占比、BMI、三酰甘油、NHR比较，差异有统计学意义（P<0.05）。多因素Logistic回归分析结果显示，NHR是CSF的影响因素（P<0.05）。ROC曲线分析结果显示，NHR预测CSF的AUC为0.803[95%CI(0.734,0.861)]，最佳截断值为3.55，灵敏度为66.30%，特异度为80.70%。结论 NHR是CSF的独立影响因素，对CSF有一定的预测价值。

Abstract：

Objective To investigate the predictive value of neutrophils to high density liptein ratio (NHR) oncoronary slow flow (CSF) . Methods A total of 166 patients who underwent coronary angiography (CAG) due to chest pain inSuizhou Hospital Affiliated to Hubei University of Medicine from June 2020 to March 2022 were retrospectively selected as theresearch objects. According to the results of CAG, they were divided into the CSF group (n=83) and the control group (n=83) .Clinical data of patients were collected, including age, gender, history of smoking, history of drinking, history of hypertension,history of diabetes, BMI, lymphocyte count, platelet count, high-sensitivity C-reactive protein, total cholesterol, triglyceride,LDL-C, ALT, AST, blood urea nitrogen, serum creatinine, serum uric acid, homocysteine, fasting blood glucose, left ventricularejection fraction (LVEF) , NHR. Multivariate Logistic regression analysis was used to explore the influencing factors of CSF, andROC curve was drawn to evaluate the efficacy of NHR in predicting CSF. Results There were significant differences in gender,proportion of smokers, BMI, triglyceride and NHR between the two groups (P < 0.05) . Multivariate Logistic regression analysisshowed that NHR was an influencing factor for CSF (P < 0.05) . ROC curve analysis showed that the AUC of NHR in predictingCSF was 0.803 [95%CI (0.734, 0.861) ] , the best cut-off value was 3.55, the sensitivity was 66.30%, and the specificity was80.70%. Conclusion NHR is an independent influencing factor for the CSF and has a certain predictive value for the CSF.

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