Haigney Mark, Zareba Wojceich, La Rovere Maria Teresa, Grasso Ian, Mortara David
Uniformed Services University of the Health Sciences, Bethesda, MD, USA.
University of Rochester, Rochester, NY, USA.
J Electrocardiol. 2014 Nov-Dec;47(6):831-5. doi: 10.1016/j.jelectrocard.2014.08.002. Epub 2014 Aug 7.
Breathing is a critical component of cardiopulmonary function, but few tools exist to evaluate respiration in ambulatory patients. Holter monitoring allows accurate diagnosis of a host of cardiac issues, and several investigators have demonstrated the ability to detect respiratory effort on the electrocardiogram. In this study we introduce a myogram signal derived from 12-lead, high frequency Holter as a means of detecting respiratory effort. Using the combined myogram and ECG signal, four novel variables were created: total number of Cheyne-Stokes episodes; the BWRatio, the ratio of power (above baseline) measured one second after peak-to-peak respiratory power, an assessment of the "shape" of the respiratory effort; DRR, the change in RR interval centering around peak inspiration; and minutes of synchronized breathing, a fixed ratio of heart beats to respiratory cycles. These variables were assessed in 24-hour recordings from three cohorts: healthy volunteers (n=33), heart failure subjects from the GISSI HF trial (n=383), and subjects receiving implantable defibrillators with severely depressed left ventricular function enrolled in the M2Risk trial (n=470). We observed a statistically significant 6-fold increase in the number of Cheyne-Stokes episodes (p=0.01 by ANOVA), decreases in BWRatio (p<0.001), as well as decrease in DRR in heart failure subjects; only minutes of synchronized breathing was not significantly decreased in heart failure. This study provides "proof of concept" that novel variables incorporating Holter-derived respiration can distinguish healthy subjects from heart failure. The utility of these variables for predicting heart failure, arrhythmia, and death risk in prospective studies needs to be assessed.
呼吸是心肺功能的关键组成部分,但用于评估门诊患者呼吸功能的工具很少。动态心电图监测能够准确诊断一系列心脏问题,并且有几位研究人员已经证明了在心电图上检测呼吸努力的能力。在本研究中,我们引入了一种源自12导联高频动态心电图的肌电图信号,作为检测呼吸努力的一种手段。利用联合肌电图和心电图信号,创建了四个新变量:潮式呼吸发作的总数;BWRatio,即峰峰值呼吸功率后一秒测量的功率(高于基线)之比,用于评估呼吸努力的“形状”;DRR,以吸气峰值为中心的RR间期变化;以及同步呼吸分钟数,即心跳与呼吸周期的固定比值。在来自三个队列的24小时记录中评估了这些变量:健康志愿者(n = 33)、GISSI HF试验中的心力衰竭受试者(n = 383)以及参加M2Risk试验的左心室功能严重受损并接受植入式除颤器的受试者(n = 470)。我们观察到心力衰竭受试者的潮式呼吸发作次数在统计学上显著增加了6倍(方差分析p = 0.01),BWRatio降低(p < 0.001),DRR也降低;只有同步呼吸分钟数在心力衰竭患者中没有显著降低。这项研究提供了“概念验证”,即结合动态心电图衍生呼吸的新变量可以区分健康受试者和心力衰竭患者。这些变量在前瞻性研究中预测心力衰竭、心律失常和死亡风险的效用需要进行评估。