학술논문

Early identification of heart failure deterioration through respiratory monitoring with adaptive servo‐ventilation.
Document Type
Article
Source
Journal of Sleep Research. Feb2023, Vol. 32 Issue 1, p1-11. 11p.
Subject
*VENTILATION
*VENTILATION monitoring
*HEART failure
*HEART failure patients
*BODY mass index
*VENTRICULAR ejection fraction
Language
ISSN
0962-1105
Abstract
Summary: Cardiac decompensation is associated with worse prognosis in patients with heart failure. Reliable methods to predict cardiac decompensation events are not yet available. Sleep‐disordered breathing (SDB) is a frequent comorbidity in heart failure, and it has been shown to correlate with heart failure severity. This prospective observational trial investigated SDB characteristics in patients with heart failure with the aim to identify patterns that may predict early cardiac decompensation. Patients with heart failure with diagnosed SDB and hospitalised for cardiac decompensation were prospectively enrolled and treated with adaptive servo‐ventilation (ASV). SDB characteristics, daily body weight and clinical cardiac decompensation events were collected over a 1‐year follow‐up. Clinical events were categorised by an independent clinical event committee. A total of 43 patients were enrolled (81% male, mean [SD] age 71 [11] years, body mass index 30 kg/m2, 95% New York Heart Association function class III or IV, mean [SD] left ventricular ejection fraction 37% [11%], median apnea–hypopnoea index [AHI] of 37 events/h). A total of 48 cardiac decompensation events were recorded during the 1‐year study period. Respiratory rate was found to be significantly lower in patients with cardiac decompensation. The AHI and applied inspiratory pressure ASV‐device support were significantly increased 10 days before a clinical cardiac decompensation event. Device usage was also found to be significantly decreased 2 nights before cardiac decompensation. Device‐derived respiratory data in ASV therapy devices for SDB may therefore serve as a monitoring tool to predict early clinical cardiac decompensation events. Prediction and avoidance of cardiac decompensation, in turn, may attenuate serious health consequences in patients with heart failure. [ABSTRACT FROM AUTHOR]