收缩压变异性和心率变异性对维持性血液透析患者MACE发生风险的预测价值

目的 探讨收缩压变异性(SBPV)和心率变异性（HRV）对维持性血液透析（MHD）患者主要不良心血管事件(MACE)发生风险的预测价值。方法 纳入2017年3月—2018年3月在宜昌市中心人民医院肾病内科血液净化中心接受规律治疗的MHD患者120例，根据是否发生MACE分为MACE组（n=59）与无MACE组（n=61）。在患者行血液透析前佩戴Holter，收集24 h心电活动信息，计算均值（MEAN）、RR间期总体标准差（SDNN）、RR间期平均值的标准差（SDANN）和相邻RR间期差值的均方根（r-MSSD）。采用自动血压监测系统记录24 h血压变化，计算白昼收缩压变异性（dSBPV）、夜间收缩压变异性（nSBPV）和24 h收缩压变异性（24 h SBPV）。Logistic回归分析MHD患者MACE发生的危险因素。调整混杂因素后，采用Cox比例风险模型回归分析24 h SBPV和SDNN与MHD患者MACE发生的关系。绘制受试者工作特征（ROC）曲线，计算曲线下面积（AUC）、灵敏度、特异度，分析SDNN和收缩压变异性单独及联合对维持性MHD患者发生MACE的预测价值。根据SDNN和24 h SBPV水平将患者分成3组，绘制Kaplan-Meier生存曲线评价不同SDNN和收缩压变异性的MHD患者MACE发生情况。结果 与无MACE组相比，MACE组年龄较大，24 h SBPV、dSBPV、nSBPV较高，SDNN、SDANN较低，差异具有统计学意义（P＜0.05）。Logistic回归分析显示，年龄、Kt/V、24 h SBPV、dSBPV、nSBPV、SDNN、SDANN是MHD患者MACE发生的独立危险因素（P＜0.05）。调整混杂因素后，多因素COX比例风险模型回归分析，24 h SBPV为MHD患者发生MACE的危险因素，而SDNN为MHD患者发生MACE的保护性因素（P＜0.05）。SDNN与收缩压变异性联合预测MHD患者发生MACE的AUC为0.879，预测效能高于单项检测（P＜0.05）。组1随访期间累积MACE发生率显著低于组2和组3（19.15% vs 65.12%vs 73.33%，P＜0.001）。结论MHD不良预后患者中24 h SBPV升高，SDNN降低，24 h SBPV和SDNN单独预测MACE的具体价值尚可，两者联合预测效果更佳，可为临床上及早识别及干预MHD患者MACE发生提供参考依据

Predictive value of systolic blood pressure variability and heart rate variability on the risk of adverse cardiovascular events in maintenance hemodialysis patients

Objective To explore the predictive value of systolic blood pressure variability and heart rate variability on the risk of adverse cardiovascular events in maintenance hemodialysis (MHD) patients.Methods A total of 120 patients with MHD who received regular treatment at the Blood Purification Center of the Department of Nephropathy, Yichang Central People''s Hospital from March 2017 to March 2018 were included. They were divided into MACE group (n=59) and non-MACE group (n=61) according to the incidence of MACE. Holter was worn before the patient underwent hemodialysis. 24 h ECG activity information was collected, and MEAN value (MEAN), population standard deviation between RR intervals (SDNN), standard deviation of mean value between RR intervals (SDANN), and root mean square of the difference between adjacent RR intervals were calculated (r-MSSD). 24-hour blood pressure changes were recorded by an automatic blood pressure monitoring system, and daytime systolic blood pressure variability (dSBPV), nighttime systolic blood pressure variability (nSBPV) and 24-hour systolic blood pressure variability (24 h SBPV) were calculated. Logistic regression analysis of MACE risk factors in MHD patients. After adjusting confounding factors, COX proportional risk model was used to analyze the relationship between 24-h SBPV and SDNN and the occurrence of MACE in MHD patients. The receiver operating characteristic (ROC) curve was plotted, and the area under the curve (AUC), sensitivity, and specificity were calculated to analyze the predictive value of SDNN and systolic blood pressure variability alone and in combination for MACE in patients with maintenance MHD. According to the levels of SDNN and 24 h SBPV, the patients were divided into 3 groups. Kaplan-Meier survival curve was plotted to evaluate the occurrence of MACE in MHD patients with different SDNN and systolic blood pressure variability. Results Compared with the non MACE group, the MACE group was older, with higher 24 h SBPV, dSBPV, and nSBPV, and lower SDNN and SDANN, with statistically significant differences (P＜0.05). Logistic regression analysis showed that age, Kt/V, 24 h SBPV, dSBPV, nSBPV, SDNN, and SDANN were independent risk factors for the occurrence of MACE in MHD patients (P＜0.05). After adjusting for confounding factors, a multivariate Cox proportional hazards regression analysis showed that 24 h SBPV was a risk factor for MACE in MHD patients, while SDNN was a protective factor for MACE in MHD patients (P＜0.05). The combined prediction of SDNN and systolic blood pressure variability for MACE in MHD patients has an AUC of 0.879, with higher predictive power than single detection (P＜0.05). The cumulative incidence of MACE during follow-up in Group 1 was significantly lower than that in Group 2 and Group 3 (19.15% vs65.12% vs73.33%, P＜0.001).Conclusion In patients with poor prognosis of MHD, the levels of 24 h SBPV and SDNN are elevated. The specific value of 24 h SBPV and SDNN alone in predicting MACE is still acceptable, and the combined prediction effect of the two is better, which can provide reliable basis for early identification and intervention of MACE in MHD patients in clinical practice