Diagnosis And Treatment of Sleep Apnea in Patient With Heart Failure
NCT ID: NCT02620930
Last Updated: 2017-02-23
Study Results
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Basic Information
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UNKNOWN
265 participants
OBSERVATIONAL
2014-03-31
2018-07-31
Brief Summary
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Detailed Description
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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.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Interventions
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All market approved CRT-D or ICD systems endowed with the APNEA Scan algorithm
Eligibility Criteria
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Inclusion Criteria
* Patient implanted with CRT-D or ICD endowed with continuous respiratory sensor designed for sleep apnea monitoring.
* Age 18 or above, or legal age to provide informed consent according to national law.
Exclusion Criteria
* Woman pregnant or planning to become pregnant.
* Patient is unwilling or unable to sign an authorization to use and disclose health information or an Informed Consent.
* Patient unavailable to attend scheduled follow-up visits at the center.
* Patient life expectancy is less than 12 months.
* Patient is participating in another clinical study that may have an impact on the study endpoints.
18 Years
ALL
No
Sponsors
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Luigi Padeletti
OTHER
Responsible Party
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Luigi Padeletti
Head of Electrophysiology and Cardiac Pacing
Locations
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Department of Heart and Vessels, University of Florence
Florence, , Italy
Countries
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References
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Boriani G, Pisano ECL, Pieragnoli P, Locatelli A, Capucci A, Talarico A, Zecchin M, Rapacciuolo A, Piacenti M, Indolfi C, Arias MA, Diemberger I, Checchinato C, La Rovere MT, Sinagra G, Emdin M, Ricci RP, D'Onofrio A. Prognostic value of implantable defibrillator-computed respiratory disturbance index: The DASAP-HF study. Heart Rhythm. 2021 Mar;18(3):374-381. doi: 10.1016/j.hrthm.2020.10.019. Epub 2020 Oct 24.
Other Identifiers
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Prot. n. 2013/00 21553
Identifier Type: -
Identifier Source: org_study_id
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