Defaye Pascal, Pépin Jean-Louis, Poezevara Yann, Mabo Philippe, Murgatroyd Francis, Lévy Patrick, Garrigue Stéphane
Pneumology Departments, University Hospital, Grenoble, France.
J Cardiovasc Electrophysiol. 2004 Sep;15(9):1034-40. doi: 10.1046/j.1540-8167.2004.04030.x.
A number of pacemakers use transthoracic impedance to derive minute ventilation as a sensor for rate adaptation. Transthoracic impedance is also able to track fluctuations in tidal volume occurring in sleep apnea/hypopnea syndromes (SAS). We evaluated the feasibility of a transthoracic impedance-derived pacemaker algorithm for monitoring sleep respiratory disturbances.
Forty-two patients who presented with a conventional indication for DDD pacing or cardiac resynchronization underwent conventional polysomnography 1 month after implantation of a Talent trade mark 3 pacemaker (ELA Medical). The respiratory disturbance index (RDI) stored in the pacemaker memory was compared to the apnea/hypopnea index (AHI) derived from polysomnography. The ability of the pacemaker to identify severe SAS patients (AHI > or = 30) was assessed. A minimal systematic error was observed from a Bland and Altman plot (bias = 0.9 events/hour). The ability of the pacemaker RDI to identify severe SAS patients was determined by analysis of the receiver operator characteristic. A cutoff RDI value of 30.6/hour of recording was found to yield 75% sensitivity, 94% specificity, 75% positive predictive value, and 94% negative predictive value.
The RDI monitoring function appears to be of value in screening pacemaker patients for SAS. Its performance is comparable to existing simple screening techniques. The ability to permanently monitor respiration, in combination with other diagnostic capabilities (such as Holter functions), presents a unique opportunity to monitor the association between arrhythmias and disturbances of breathing during sleep.
许多起搏器利用经胸阻抗来推导每分通气量,以此作为频率适应性的传感器。经胸阻抗还能够追踪睡眠呼吸暂停/低通气综合征(SAS)中潮气量的波动情况。我们评估了一种基于经胸阻抗的起搏器算法用于监测睡眠呼吸紊乱的可行性。
42例有DDD起搏或心脏再同步治疗常规适应证的患者,在植入Talent商标3起搏器(ELA Medical公司)1个月后接受了常规多导睡眠图检查。将起搏器内存中存储的呼吸紊乱指数(RDI)与多导睡眠图得出的呼吸暂停/低通气指数(AHI)进行比较。评估起搏器识别重度SAS患者(AHI≥30)的能力。从布兰德-奥特曼图中观察到最小系统误差(偏倚=0.9次/小时)。通过分析受试者工作特征曲线来确定起搏器RDI识别重度SAS患者的能力。发现记录的RDI临界值为30.6次/小时时,灵敏度为75%,特异性为94%,阳性预测值为75%,阴性预测值为94%。
RDI监测功能在筛查起搏器患者有无SAS方面似乎有价值。其性能与现有的简单筛查技术相当。能够持续监测呼吸,再结合其他诊断功能(如动态心电图功能),为监测心律失常与睡眠期间呼吸紊乱之间的关联提供了独特的机会。