Sunrise® a New Medical Device to Diagnose Sleep Apnea Syndrome
NCT ID: NCT04262557
Last Updated: 2020-10-19
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
NA
40 participants
INTERVENTIONAL
2020-05-18
2020-09-28
Brief Summary
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The aim of this study is to evaluate the Sunrise®, a new medical integrated solution for SAS diagnosis, in comparison with PSG. This solution consists in a chin sensor recording mandibular movements and measuring the respiratory event index (ERI) through an artificial intelligence algorithm analysis.
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Detailed Description
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The objective of this study is to evaluate the efficiency of the device in comparison with PSG for sleep apnea diagnosis.
40 subjects, suspected to be apneic, will be equipped at home by the chin sensor, the Sunrise® device, recording their mandibular movements while sleeping. The Sunrise® solution will provide the respiratory event index (REI) as well as the respiratory micro-arousals.
Inclusion visit will be executed at the University Hospital Grenoble Alpes. However, PSG and Sunrise® will be set at the patient's home by IC@dom. The first night, the patient will be equipped by both PSG and Sunrise® and only by the Sunrise® for the two following nights.
Conditions
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Study Design
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NA
SINGLE_GROUP
DIAGNOSTIC
NONE
Study Groups
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Sunrise+PSG
PSG and Sunrise® will be set at the patient's home by IC@dom. The first night, the patient will be equipped by both PSG and Sunrise® and only by the Sunrise® for the two following nights.
Sunrise® solution
Type II medical device with the CE label. It is a chin sensor associated to an integrated and connected platform.
Polysomnography
Gold standard method to diagnose SAS used as comparator
Interventions
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Sunrise® solution
Type II medical device with the CE label. It is a chin sensor associated to an integrated and connected platform.
Polysomnography
Gold standard method to diagnose SAS used as comparator
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
* Able to use a smartphone application
* Be legally able to give consent
* Person affiliated to social security
Exclusion Criteria
* Patients suffering from a chronic obstructive or restrictive pulmonary disease with or without oxygen.
* Patients suffering from a unstable cardiovascular disease or a severe heart failure requiring an hospitalzation in the previous three months or conform with the New York Heart Association criteria for class II or III diseases
* Patients treated with myorelaxant medicines
* Patients with a long beard disabling the setting of the mandibular sensor
* Subjects listed in articles L1121-5 à L1121-8: Pregnant women, feeding and parturient; subject under administrative or judicial control, persons who are protected under the act.
* Person in exclusion period for another study or participating in a medical study testing drugs.
* Subjects not being cooperative or respecting the study instructions, according the investigator.
18 Years
80 Years
ALL
No
Sponsors
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Sunrise
INDUSTRY
Icadom
INDUSTRY
DOCAPOST
UNKNOWN
University Hospital, Grenoble
OTHER
Responsible Party
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Principal Investigators
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Jean Louis Pépin, MD, PhD
Role: PRINCIPAL_INVESTIGATOR
University Hospital Grenoble Alpes
Locations
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University Hospital Grenoble Alpes
Grenoble, , France
Countries
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References
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Kelly JL, Ben Messaoud R, Joyeux-Faure M, Terrail R, Tamisier R, Martinot JB, Le-Dong NN, Morrell MJ, Pepin JL. Diagnosis of Sleep Apnoea Using a Mandibular Monitor and Machine Learning Analysis: One-Night Agreement Compared to in-Home Polysomnography. Front Neurosci. 2022 Mar 15;16:726880. doi: 10.3389/fnins.2022.726880. eCollection 2022.
Other Identifiers
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38RC19.358
Identifier Type: -
Identifier Source: org_study_id
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