Shirakawa Yuki, Niwano Shinichi, Oikawa Jun, Saito Daiki, Sato Tetsuro, Matsuura Gen, Arakawa Yuki, Kobayashi Shuhei, Nishinarita Ryo, Horiguchi Ai, Ishizue Naruya, Kishihara Jun, Fukaya Hidehira, Ako Junya
Department of Cardiovascular Medicine, Kitasato University School of Medicine.
Int Heart J. 2020 Sep 29;61(5):927-935. doi: 10.1536/ihj.20-152. Epub 2020 Sep 2.
We prospectively collected device and heart rate data through remote monitoring (RM) of patients with an implantable cardioverter defibrillator (ICD). The objective was to identify the predictors of lethal arrhythmic events (VT/VF).Thirty-three patients (mean age: 50 years) with ICDs [with functionality of heart rate variability (HRV) analysis] were divided into two groups [VT/VF (+), VT/VF (-) ]. Clinical, device (ventricular lead impedance; amplitude of ventricular electrogram), and HRV data were compared between the two groups. The NN interval-index (SDNNi) was calculated for every 5 minutes, and the mean, maximum, minimum, and standard deviation of SDNNi during the 24-hour period were used.During the observation period of 13 ± 10 months, 10 patients experienced VT/VF events. Total mean, max, and min SDNNi were higher in the VT/VF (+) than the VT/VF (-) group (132.9 ± 9.3 versus 93.5 ± 6.1, P = 0.0013; 214.6 ± 10.6 versus 167.0 ± 7.0, P = 0.0007; 71.2 ± 7.5 versus 43.9 ± 4.9, P = 0.0047). On logistic regression analysis, a total mean SDNNi of 100.1, max SDNNi of 185.0 and min SDNNi of 52.0 as cut-off values for prediction of a VT/VF event demonstrated significant receiver operating characteristic (ROC) curves (AUC = 0.86, P = 0.0007; AUC = 0.84, P = 0.0005; AUC = 0.78, P = 0.0030). The max ΔSDNNi, i.e., difference from baseline SDNNi, and min ΔSDNNi in 7 and 28 days preceding VT/VF events were significant predictors of VT/VF events.Time-domain HRV analysis through a RM system may help identify patients at high risk of lethal arrhythmic events; in addition, it may help predict the occurrence of lethal arrhythmic events in specific cases.
我们通过对植入式心脏复律除颤器（ICD）患者进行远程监测（RM），前瞻性地收集了设备和心率数据。目的是确定致死性心律失常事件（室性心动过速/心室颤动，VT/VF）的预测因素。33例（平均年龄：50岁）具有ICD[具备心率变异性（HRV）分析功能]的患者被分为两组[VT/VF（+）组、VT/VF（-）组]。比较了两组患者的临床、设备（心室导联阻抗；心室电图振幅）和HRV数据。每5分钟计算一次NN间期指数（SDNNi），并使用24小时期间SDNNi的平均值、最大值、最小值和标准差。在13±10个月的观察期内，10例患者发生了VT/VF事件。VT/VF（+）组的总平均、最大和最小SDNNi高于VT/VF（-）组（132.9±9.3对93.5±6.1，P = 0.0013；214.6±10.6对167.0±7.0，P = 0.0007；71.2±7.5对43.9±4.9，P = 0.0047）。逻辑回归分析显示，以总平均SDNNi为100.1、最大SDNNi为185.0和最小SDNNi为52.0作为预测VT/VF事件的截断值时，显示出显著的受试者工作特征（ROC）曲线（AUC = 0.86，P = 0.0007；AUC = 0.84，P = 0.0005；AUC = 0.78，P = 0.0030）。VT/VF事件前7天和28天的最大ΔSDNNi，即与基线SDNNi的差值，以及最小ΔSDNNi是VT/VF事件的显著预测因素。通过RM系统进行时域HRV分析可能有助于识别有致死性心律失常事件高风险的患者；此外，它可能有助于预测特定病例中致死性心律失常事件的发生。
