Seasonal trends in atrial fibrillation episodes and physical activity collected daily with a remote monitoring system for cardiac implantable electronic devices
Seasonal trends in atrial fibrillation episodes and physical activity collected daily with a remote monitoring system for cardiac implantable electronic devices
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DOI：
10.1016/j.ijcard.2017.02.074
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发表时间：
2017-05-01
影响因子：
3.5
通讯作者：
Ricci, Renato Pietro
中科院分区：
文献类型：
--
作者：
Censi, Federica;Calcagnini, Giovanni;Ricci, Renato Pietro
背景：心脏植入式电子设备的远程监测（RM）是一种理想的实验模型，用于评估从大量患者队列中自动收集的生理和临床数据的长期趋势。目的：我们研究了一组参加HomeGuide试验的患者的房颤（AF）和身体活动（PA）的数据，这些数据在3.5年的时间里每天传递。HomeGuide试验是一项先前进行的研究，对患者进行常规跟踪，每天使用RM系统传递临床和诊断数据。方法：我们选择988例患者（80%男性，平均年龄68±11岁），植入心脏起搏器（16%）或植入式除颤器，并配备心房传感和运动传感器。对远程传输的数据进行处理，以每日采样的集体时间序列的形式获得AF发病率和PA时间。结果：PA和AF的发病率均有明显的季节变化趋势，具有明显的年周期和负相关关系。在一阶自回归模型中，每日活动量对房颤发病率的回归系数为-0.64（标准误差0.18,p < 0.0001），而交叉相关系数在+/- 180天后达到最大值。冬季AF发病率比夏季高14.4%，PA发病率比夏季低14.7%（两组比较p < 0.0001）。功率谱分析显示PA序列具有周周期性（与节日休息相对应），但AF发病率不具有周周期性。结论：每天从一个相对较大的患者队列中收集的RM数据显示，AF发病率和PA在冬季和夏季具有明显的季节性趋势。(C) 2017 Elsevier B.V.版权所有
Background: Remotemonitoring (RM) of cardiac implantable electronic devices is an ideal experimental model to evaluate long-term trends of physiological and clinical data automatically collected from large patient cohorts.Objectives: We studied data of atrial fibrillation (AF) and physical activity (PA) transmitted daily during 3.5 years from a subgroup of patients enrolled in the HomeGuide trial, a previously conducted study on patients routinely followed with a RM system transmitting clinical and diagnostic data daily.Methods: We selected 988 patients (80% male, mean age 68 +/- 11) implanted with a pacemaker (16%) or an implantable defibrillator and provided with atrial sensing and movement sensors. Remotely transmitted data were processed in order to obtain AF incidence and time of PA in the form of collective time series daily sampled.Results: We found that both PA and AF incidence clearly showed seasonal trends with an annual period and inverse correlation. In a first-order autoregressive model the regression coefficient of daily activity to AF incidence was -0.64 (standard error, 0.18, p < 0.0001), while the cross-correlation coefficient reached its maximum values at +/- 180 day lags. AF incidence was 14.4% higher and PA was 14.7% lower in winters than in summers (p < 0.0001 for both comparisons). Power spectral analysis revealed weekly periodicity in the PA series (corresponding to festivity rest) but not in the AF incidence.Conclusions: RM data collected daily from a relatively large patient cohort revealed marked seasonal trends in AF incidence and PA with opposite behavior in winters and summers. (C) 2017 Elsevier B.V. All rights reserved.