Dias Margarida, Gonçalves Inês, Amann Bruno, Marques Pedro, Martinho Cristina, Leitão Catarina, Basto Rita Pinto, de Sousa João, Pinto Paula, Bárbara Cristina
Pulmonology Department, Centro Hospitalar de Vila Nova de Gaia, Vila Nova de Gaia, Portugal.
Cardiology Department, Centro Hospitalar Lisboa Norte, Lisboa, Portugal.
Sleep Med. 2017 Sep;37:27-31. doi: 10.1016/j.sleep.2017.06.006. Epub 2017 Jun 24.
Patients with cardiac pacemakers present a high prevalence of undiagnosed sleep apnea syndrome (SAS). New-generation pacemakers have algorithms that identify sleep respiratory events. Our aim was to evaluate their accuracy in the diagnosis of SAS.
We performed a prospective study that included patients with new-generation pacemakers (Reply 200 pacemakers). All patients underwent a polysomnography (PSG). On the same night, the respiratory disturbance index of the PSG (RDI-PSG) and of the pacemaker (RDI-PM) were recorded. The agreement between methods was assessed using the kappa coefficient, Bland and Altman statistics and receiver operating characteristic (ROC) curves.
Sixty patients were recruited but the RDI-PM for the PSG night was not available in six patients. PSG diagnosed SAS in 74% of patients (20% severe, 19% moderate, 35% mild). Besides snoring (63%), most patients had no SAS symptoms. There was a strong positive correlation between RDI-PSG and RDI-PM (r = 0.522, p < 0.001), but the level of agreement between methods regarding SA diagnosis/severity was poor (k = 0.167). ROC curves identified a RDI-PM of 10 events/h as the optimal cut-off point for diagnosing SAS (area under the curve (AUC): 0.81, sensitivity: 80%, specificity: 79%, positive predictive value: 91%, negative predictive value: 58%). The best cut-off for identifying moderate/severe SAS was at 13 events/h (AUC: 0.86, sensitivity: 100%, specificity: 70%, positive predictive value: 68%, negative predictive value: 100%).
SAS prevalence in patients with pacemakers is high (74%). Most are asymptomatic, which could delay the diagnosis. Patients with clinical indication for a pacemaker may benefit from a device with sleep apnea monitoring.
心脏起搏器植入患者中，未诊断出的睡眠呼吸暂停综合征（SAS）患病率较高。新一代起搏器具备识别睡眠呼吸事件的算法。我们的目的是评估其在SAS诊断中的准确性。
我们开展了一项前瞻性研究，纳入了使用新一代起搏器（Reply 200起搏器）的患者。所有患者均接受了多导睡眠图（PSG）检查。在同一晚，记录PSG的呼吸紊乱指数（RDI-PSG）和起搏器的呼吸紊乱指数（RDI-PM）。使用kappa系数、布兰德-奥特曼统计方法和受试者工作特征（ROC）曲线评估两种方法之间的一致性。
招募了60名患者，但6名患者无法获取PSG当晚的RDI-PM数据。PSG诊断出74%的患者患有SAS（20%为重度，19%为中度，35%为轻度）。除打鼾（63%）外，大多数患者无SAS症状。RDI-PSG与RDI-PM之间存在强正相关（r = 0.522，p < 0.001），但两种方法在SA诊断/严重程度方面的一致性水平较差（k = 0.167）。ROC曲线确定RDI-PM为每小时10次事件是诊断SAS的最佳截断点（曲线下面积（AUC）：0.81，敏感性：80%，特异性：79%，阳性预测值：91%，阴性预测值：58%）。识别中度/重度SAS的最佳截断点为每小时13次事件（AUC：0.86，敏感性：100%，特异性：70%，阳性预测值：68%，阴性预测值：100%）。
起搏器植入患者中SAS患病率较高（74%）。大多数患者无症状，这可能会延迟诊断。有起搏器临床适应证的患者可能会受益于具备睡眠呼吸暂停监测功能的设备。
