Diagnosis And Treatment of Sleep Apnea in Patient With Heart Failure (DASAP-HF)

Heart Failure (HF) is a leading cause of morbidity and mortality in developed countries and a major national and global health problem involving about 2% of the overall population and 10% of the elderly.

A remarkably high proportion (around 50%) of stable optimally treated patients with HF and systolic dysfunction experience persistent, moderate-to-severe breathing disorders both during nighttime e during short-term laboratory recording.Sleep Disordered Breathing (SDB) is associated with transient hypoxia and increased sympathetic activity. Both factors could worsen Left Ventricular Ejection Function (LVEF) or increase serious arrhythmia.

Diagnosing and treating apnea may become a relevant issue in the management of HF patients . Prognostic stratification of congestive HF is an important objective in patient management. Many prognostic stratification scores have been suggested, however none has gained extensive acceptance. Variables used to generate stratification scores must be simple, clinically relevant, and readily obtainable. Furthermore, they must correlate to clinical events, such as hospitalization, Implant Cardioverter Defibrillator (ICD) intervention and mortality. ICD interventions are known to correlate with prognosis, and should thus be included among the end-points.

Cardiac resynchronization therapy (CRT) has been demonstrated to positively affect SA by reducing the apnea-hypopnea index (AHI). The recently developed implantable ventilation sensor which allows automated detection of advanced breathing disorders may provide not only the possibility to closely track the benefit of treatment but also provide further insights into the pathophysiological mechanisms linking Central Sleep Apnea (CSA) to HF. Given that the automated detection of sleep disordered breathing has been only performed in a limited cohort of patients with preserved LVEF requiring pacemaker (PM) implantation for standard bradycardia indications, one aspect requiring clarification is the assessment/validation of the performance of the automated detection in patients with HF.

The RDI is used to assess the severity of sleep apnea based on the total number of complete cessations (apnea) and partial obstructions (hypopnea) of breathing occurring per hour of sleep. These pauses in breathing must last for 10 seconds and are associated with a decrease in oxygenation of the blood. In general, the RDI can be used to classify the severity of disease (mild 5-15, moderate 15-30, and severe greater than 30). An implanted pacing device with a respiratory sensing function may provide clinically useful diagnostics and treatment for sleep-related breathing disorders.

The purpose of this study is to evaluate the performance of the APNEA Scan algorithm in patients implanted with an ICD or CRT-D device endowed with the APNEA Scan algorithm. Primary objective of this study is to evaluate the performance of RDI value calculated by APNEA Scan algorithm, as a binary discriminator of severe Sleep Apnea (SA) as detected by the gold-standard sleep study. Secondary objective of the study is to assess the incidence of clinical events after 24 months of enrollment and investigate its association with the RDI values calculated by APNEA Scan algorithm.