Margarida Dias1, Inês Gonçalves2, Bruno Amann3, Pedro Marques2, Cristina Martinho3, Catarina Leitão3, Rita Pinto Basto3, João de Sousa2, Paula Pinto4, Cristina Bárbara4. 1. Pulmonology Department, Centro Hospitalar de Vila Nova de Gaia, Vila Nova de Gaia, Portugal. Electronic address: margarida.pinho.dias@chvng.min-saude.pt. 2. Cardiology Department, Centro Hospitalar Lisboa Norte, Lisboa, Portugal. 3. Pulmonology Department, Centro Hospitalar Lisboa Norte, Lisboa, Portugal. 4. Pulmonology Department, Centro Hospitalar Lisboa Norte, Lisboa, Portugal; Faculdade de Medicina da Universidade de Lisboa, Lisboa, Portugal; Instituto de Saúde Ambiental (ISAMB), Lisboa, Portugal.
Abstract
OBJECTIVE: 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. METHODS: 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. RESULTS: 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%). CONCLUSIONS: 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.
OBJECTIVE: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. METHODS: 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. RESULTS: 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%). CONCLUSIONS: 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.