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Recruiting NCT07345312

BodySleep Algorithm for OSA Diagnosis in Children

— Observational Obstructive Sleep Apnea of Child

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: Polysomnography.
Who it may be relevant to
Registry conditions: Obstructive Sleep Apnea of Child. Basic parameters: 2 years — 18 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
France
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →

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Official title

The Use of the BodySleep Algorithm (ResMed) for the Diagnosis of Obstructive Sleep Apnea Syndrome in Children

Overview

Diagnosing obstructive sleep apnea-hypopnea syndrome in children (OSA) requires the performance of polysomnography (PSG) in the hospital which is sometimes challenging to perform in children, and time-consuming for installation and analysis. Simplified recording and analysis methods are preferable in children but require validation in this population. 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.

Detailed description

The diagnosis of obstructive sleep apnea-hypopnea syndrome in children (OSA) requires the performance of polysomnography (PSG) in the hospital with video surveillance and monitoring by a nurse to put the sensors back on the child if necessary. During the night. The PSG gives the index of obstructive apnea-hypopnea (IAHO) necessary for the diagnosis of OSAS and to determine its severity. But the PSG is a rather cumbersome examination, sometimes challenging to perform in children, with several sensors and electrodes to install (electroencephalogram (EEG), electromyogram (EMG), electrooculogram (EOG), necessary to determine the periods of wakefulness -sleep and intra-sleep micro-arousals, nasal cannula, thoracoabdominal straps, pulse oximetry, actimetry to score respiratory events), time-consuming for installation and analysis. Simplified recording and analysis methods are preferable in children but require validation in this population.

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.

Interventions

  • Diagnostic test Polysomnography
    PSG performed prospectively in routine care in children suspected of OSA

Primary outcome measures

  • Obstructive apnea-hypopnea index by BodySleep in comparison with OAHI by PSG [Time frame: One night]

Eligibility criteria

Inclusion criteria

  • Children suspected of OSA who are addressed for a PSG by the ear nose throat physician, pediatric pulmonologist, neurologist, psychiatrist, sleep specialist, genetics, and nutritionist physician.
  • Age between 2 and 18 years

Exclusion criteria

  • Age under 2 years and over 18 years

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model
Cohort

Study locations

France · 1 center
  • CHRU de Nancy — Nancy

Publications

  • 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: PMID 33594617

Identifiers

NCT: NCT07345312 · 2023PI030

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗