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

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT02620930
Recruitment Status : Unknown
Verified February 2017 by Luigi Padeletti, University of Florence.
Recruitment status was:  Active, not recruiting
First Posted : December 3, 2015
Last Update Posted : February 23, 2017
Sponsor:
Information provided by (Responsible Party):
Luigi Padeletti, University of Florence

Brief Summary:
DASAP-HF is an observational prospective single arm study. All patients will be treated according to the standard care followed by each center. The protocol requires enrollment of consecutive patients from each center, according to eligibility criteria. All patients must sign the Patient Informed Consent (PIC) before the enrollment in the study. All patients, after the enrollment phase, will be followed for 24 months. Approximately every 12 months a clinical follow-up procedure should be performed in each patient. A sleep study will be done in all patients at 1 month (or at 3 months) from the enrollment, in order to evaluate the performance of the algorithm as a diagnostic tool in this population (primary objective). During the 24 months follow-up period, all Adverse Events occurred in the study population will be collected (HF hospitalizations, all-cause deaths, ventricular arrhythmias, etc.). At the end of the 24 months follow-up, the incidence of clinical events will be evaluated as well as its association with the Respiratory Disturbance Index (RDI) values calculated by APNEA Scan algorithm (secondary objective).

Condition or disease Intervention/treatment
Sleep Apnea Heart Failure Device: All market approved CRT-D or ICD systems endowed with the APNEA Scan algorithm

Detailed Description:

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.

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Study Type : Observational
Actual Enrollment : 265 participants
Observational Model: Cohort
Time Perspective: Prospective
Official Title: Diagnosis And Treatment of Sleep Apnea in Patient With Heart Failure DASAP-HF Study
Actual Study Start Date : March 2014
Actual Primary Completion Date : September 2016
Estimated Study Completion Date : July 2018

Resource links provided by the National Library of Medicine





Primary Outcome Measures :
  1. Severe Sleep Apnea diagnosed with polysomnography [ Time Frame: 27 months ]
    Primary objective of this study is to evaluate the accuracy of RDI value calculated by APNEA Scan algorithm, as a binary discriminator of severe SA as detected by the gold-standard sleep study.


Secondary Outcome Measures :
  1. Incidence of clinical events [ Time Frame: 4 years ]
    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.



Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Probability Sample
Study Population
Patients implanted with an ICD or CRT-D endowed with the APNEA Scan algorithm that meet all inclusion/exclusion criteria.will be enrolled after signing of an informed consent form and an authorization to use and disclose health information.
Criteria

Inclusion Criteria:

  • Patient with left ventricular systolic dysfunction, left ventricular ejection fraction ≤35%, as documented at the moment of device implant, and conventional indication to CRT-D or ICD.
  • 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:

  • Patient on cardiac resynchronization therapy for a period longer than 7 days.
  • 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.

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT02620930


Locations
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Italy
Department of Heart and Vessels, University of Florence
Florence, Italy, 50134
Sponsors and Collaborators
Luigi Padeletti
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Responsible Party: Luigi Padeletti, Head of Electrophysiology and Cardiac Pacing, University of Florence
ClinicalTrials.gov Identifier: NCT02620930    
Other Study ID Numbers: Prot. n. 2013/00 21553
First Posted: December 3, 2015    Key Record Dates
Last Update Posted: February 23, 2017
Last Verified: February 2017
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No
Keywords provided by Luigi Padeletti, University of Florence:
Sleep Disorders
Sleep Apnea
Apnea-Hypopnea Index (AHI)
Respiratory Disturbance Index (RDI)
Additional relevant MeSH terms:
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Apnea
Sleep Apnea Syndromes
Heart Failure
Heart Diseases
Cardiovascular Diseases
Respiration Disorders
Respiratory Tract Diseases
Signs and Symptoms, Respiratory
Sleep Disorders, Intrinsic
Dyssomnias
Sleep Wake Disorders
Nervous System Diseases