ABSTRACT
BACKGROUND: Sleep apnea (SA) is associated with cardiovascular diseases and is highly prevalent in patients with pacemakers (PMs). OBJECTIVE: To validate a transthoracic impedance sensor with an advanced algorithm (sleep apnea monitoring) for identifying severe SA. METHODS: Patients with indications for PM (VVI/DDD) were enrolled regardless of symptoms suggesting SA. Severe SA diagnosis was acknowledged when the full polysomnography gave an apnea-hypopnea index (PSG-AHI) of ≥30 events/h. The PSG-AHI was compared with the respiratory disturbance index evaluated by the SAM algorithm (SAM-RDI) compiled from the device during the same diagnosis night, and the performance of the device and the SAM algorithm was calculated to identify patients with severe SA. The agreement between methods was assessed by using Bland and Altman statistics. RESULTS: Forty patients (mean age 73.8 ± 19.1 years; 67.5% men; body mass index 27.7 ± 4.4 kg/m(2)) were included. Severe SA was diagnosed by PSG in 56% of the patients. We did not retrieve SAM-RDI data in 14% of the patients. An optimal cutoff value for the SAM-RDI at 20 events/h was obtained by a receiver operator characteristic curve analysis, which yielded a sensitivity of 88.9% (95% confidence interval [CI] 65.3%-98.6%), a positive predictive value of 88.9% (95% CI 65.3%-98.6%), and a specificity of 84.6% (95% CI 54.6%-98.1%) (n = 31). The Bland-Altman limits of agreement for PSG-AHI (in events per hour) were [-14.1 to 32.4]. CONCLUSION: The results suggest that an advanced algorithm using PM transthoracic impedance could be used to identify SA in patients with PMs outside the clinic or at home.