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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RECRUITING
90 participants
OBSERVATIONAL
2026-01-10
2026-01-15
Brief Summary
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The BodySleep automatic algorithm of the polysomnograph used in our lab (A1-Nox, ResMed) associated only with respiratory signals could be used to identify respiratory events. Thus the child would have fewer sensors installed on him.
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Detailed Description
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The BodySleep automatic algorithm of the polysomnograph used in our service (A1-Nox, ResMed) combines actigraphy data (body position during sleep) and induction plethysmography signal resulting from the thoracoabdominal belts to identify sleep-wake stages could be used instead of EEG, EOG and EMG electrodes. The BodySleep algorithm associated only with respiratory signals (nasal cannula, thoracoabdominal straps, pulse oximetry, actimetry) could be used to identify respiratory events. Thus the child would have fewer sensors installed on him.
The hypothesis of this study is that the BodySleep algorithm associated with respiratory signals can identify OSA in children.
Conditions
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Study Design
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COHORT
RETROSPECTIVE
Interventions
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Polysomnography
PSG performed prospectively in routine care in children suspected of OSA
Eligibility Criteria
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Inclusion Criteria
* Age between 2 and 18 years
Exclusion Criteria
2 Years
18 Years
ALL
No
Sponsors
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Central Hospital, Nancy, France
OTHER
Responsible Party
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Locations
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CHRU de Nancy
Nancy, Grand Est, France
Countries
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Central Contacts
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Facility Contacts
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References
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Dietz-Terjung S, Martin AR, Finnsson E, Agustsson JS, Helgason S, Helgadottir H, Welsner M, Taube C, Weinreich G, Schobel C. Proof of principle study: diagnostic accuracy of a novel algorithm for the estimation of sleep stages and disease severity in patients with sleep-disordered breathing based on actigraphy and respiratory inductance plethysmography. Sleep Breath. 2021 Dec;25(4):1945-1952. doi: 10.1007/s11325-021-02316-0. Epub 2021 Feb 16.
Other Identifiers
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2023PI030
Identifier Type: -
Identifier Source: org_study_id
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