王祥桧,葛文浪,宋思凡,等.中性粒细胞与高密度脂蛋白胆固醇比值对急性心肌梗死病人院内主要心血管不良事件的预测价值[J].安徽医药,2024,28(7):1333-1338. |
中性粒细胞与高密度脂蛋白胆固醇比值对急性心肌梗死病人院内主要心血管不良事件的预测价值 |
Value of neutrophil to high-density lipoprotein cholesterol ratio for predicting in-hospital major adverse cardiovascular events in patients with acute myocardial infarction |
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DOI:10.3969/j.issn.1009-6469.2024.07.013 |
中文关键词: 心肌梗死 中性粒细胞与高密度脂蛋白胆固醇比值 主要心血管不良事件 Gensini评分 左室射血分数 |
英文关键词: Myocardial infarction Neutrophil to HDL-C ratio Major adverse cardiovascular events Gensini score Left ventricular ejection fraction |
基金项目:江苏省自然科学基金项目( BK20211167) |
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中文摘要: |
目的探讨中性粒细胞与高密度脂蛋白胆固醇( HDL-C)的比值( NHR)对 AMI病人发生院内 MACE的预测价值以及 NHR与 Gensini评分量化的冠状动脉病变严重程度、左室射血分数( LVEF)量化的心脏泵功能的潜在关联。方法纳入 2018年 1月至 2022年 1月东南大学附属中大医院住院并接受冠状动脉造影的 546例 AMI病人。收集人口统计学数据、临床资料及计算 Gensini评分,依据住院期间是否发生 MACE,分为 MACE组( n=105)和非 MACE组( n=441)。使用受试者操作特征曲线(ROC曲线)检验 NHR预测院内 MACE的能力,并确定最佳截断值。使用多因素 logistic回归分析院内 MACE的影响因素,时,采用线性回归分析 NHR对 Gensini评分、 LVEF值的影响,并通过 Graphpad prism绘图进行可视化处理。院内 MACE定义同为:住院死亡、心源性休克、致血流动力学紊乱的恶性心律失常(包括室颤、持续性室速、高度及三度房室传导阻滞)等。结果MACE组的 NHR[13.64(9.89,18.19)]显著高于非 MACE组[7.73(5.83,10.07)]并且 NHR对 AMI病人院内 MACE具有较强的预测价值[AUC:0.84,95%CI:(0.79,0.88),P<0.001]调整混杂因素后,多因素二元,logistic回归分析显示 NHR是 AMI病人院内MACE的独立危险因素[OR:1.29,95%CI:(1.16,1.43),P<0.001]。线性回归分析显示 NHR与 AMI病人 Gensini评分呈显著正相关( P<0.001)与 LVEF呈显著负相关( P<0.001)。结论,本研究证实 NHR是 AMI病人院内 MACE的有力预测指标,是院内MACE的独立危险,因素之一,与 Gensini评分量化的冠状动脉病变严重程度呈显著正相关,与 LVEF量化的心脏泵功能呈显著负相关,可用于早期识别 AMI病人院内 MACE的高危人群,辅助临床诊疗。 |
英文摘要: |
Objective To investigate the predictive value of the neutrophil to high-density lipoprotein cholesterol (HDL-C) ratio (NHR) for the occurrence of in-hospital major adverse cardiovascular event (MACE) in patients with acute myocardial infarction (AMI)and to explore the potential association of NHR with the severity of coronary artery disease as quantified by the Gensini score and withcardiac pump function as quantified by the left ventricular ejection fraction (LVEF).Methods This study included 546 patients withAMI who were hospitalized and underwent coronary angiography in the Affiliated Zhongda Hospital of Southeast University from January 2018 to January 2022. Demographic data, clinical data and Gensini score were collected and assigned into the MACE group (n= 105) and the non-MACE group (n=441) based on whether MACE occurred during hospitalization. The ability of NHR to predict MACEin the hospital was tested using the receiver operating characteristic (ROC) curve, and the best cutoff point was determined. Multivariate binary logistic regression was used to analyze the risk factors of MACE in the hospital. At the same time, linear regression was usedto analyze the impact of NHR on Gensini score and LVEF value, and Graphpad Prism was used for visualization. The in-hospital MACE criteria were generally defined as in-hospital death, cardiogenic shock, malignant arrhythmia causing hemodynamic disorder (includingventricular fibrillation, persistent ventricular tachycardia, high and third-degree atrioventricular block). Results The NHR of the MACE group [13.64 (9.89, 18.19)] was significantly higher than that of the non-MACE group [7.73 (5.83, 10.07)], and NHR had a strong predictive value for in-hospital MACE in AMI patients [AUC: 0.84, 95%CI: (0.79, 0.88),P<0.001]. After adjusting for confounding factors, multifactorial binary logistic regression analysis showed that NHR was an independent risk factor for in-hospital MACE in AMI patients [OR: 1.29, 95%CI: (1.16,1.43), P<0.001]. NHR was significantly positively associated with Gensini score in AMI patients (P<0.001), and NHR was significantly negatively associated with LVEF (P<0.001).Conclusions NHR is a powerful predictor of in-hospital MACE in AMI patients and is one of the independent risk factors for in-hospital MACE. It is significantly positively correlatedwith the severity of coronary artery disease quantified by the Gensini score and significantly negatively correlated with cardiac pumpfunction quantified by LVEF. It can be used to identify the high-risk group of in-hospital MACE in AMI patients at an early stage and assist in clinical diagnosis and treatment. |
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