Utility of cardiac implantable electronic device algorithm for detecting severe sleep-disordered breathing in cardiomyopathy

Background: Half of patients with heart failure are estimated to have sleep-disordered breathing (SDB). However, many are undiagnosed as they do not report typical symptoms. This study aims to evaluate the implantable cardiac defibrillator (ICD) sleep-disordered breathing algorithm in a cohort of multi-racial Asian patients for detection of SDB against polysomnography (PSG).

Methods: In this prospective pilot study, participants who fulfill the American College of Cardiology (ACC) indication for ICD were recruited. The ICD algorithm uses transthoracic impedance sensing to calculate respiratory disturbance index (RDI).

Results: Twenty-four patients were enrolled between August 2020 and December 2021. All patients underwent PSG exams and were followed up for up to 12 months. Eighteen participants completed the PSG study as of August 23, 2022. Severe SDB (defined as PSG-AHI ≥30 episodes/h) was diagnosed in 66.7% of the patients. No significant direct linear correlation was found between the PSG-AHI measurements and the RDI measurements (adjusted r ² = .224, r = .473, p = .027). Applying a binary threshold cut-off RDI value of 32 episodes/h for the detection of severe SDB yielded a sensitivity of 91.7% and specificity of 16.7%.

Conclusions: Transthoracic impedance sensing with an advanced inbuilt algorithm may be helpful as a screening test in detecting severe SDB in patients with heart failure and cardiomyopathy, potentially by applying a binary threshold cut-off value. This is the first study known to validate the algorithm in an exclusively multi-ethnic Asian population with heart failure.