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Completed

NCT Number: NCT03632382

Non-invasive Device for the Screening and Diagnosis of Sleep Apnea Syndrome

This prospective study aims to establish and evaluate a predictive model to diagnose OSA with maxillofacial characteristics 3D acquisition.

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Key information

Conditions

Obstructive Sleep Apnea Apnea Dyssomnias Nervous System Diseases Respiration Disorders Respiratory Tract Diseases Sleep Apnea Syndromes Sleep Apnea, Obstructive Sleep Disorders, Intrinsic Sleep Wake Disorders

Age range

40 year–75 year

Sex eligibility

Male

Study type

Interventional

Phase

Not applicable

Primary location

Grenoble Alpes University Hospital

Grenoble, France

About this study

Polysomnography is the gold-standard for obstructive sleep apnea (OSA) diagnosis. However, OSA is still undiagnosed. Maxillofacial profile can influence OSA severity. Morphological characteristics can be identified but are not enough measurable and analysable by physicians. 3D acquisition of maxillofacial characteristics with a user-friendly tool, quick and low-priced could be used to obtain a predictive model as an OSA risk indicator. Thus, the aim of this study is to establish and evaluate a predictive model to diagnose OSA with maxillofacial characteristics 3D acquisition.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • BMI < 35 kg/m²
  • caucasian men
  • patients from the sleep laboratory (CHU Grenoble Alpes) admitted for a polysomnography
  • Patient who has given free and informed consent in writing

Exclusion criteria

  • history of maxillofacial surgery
  • dental malocclusion
  • patient involved in another clinical research study
  • patient not affiliated with social security
  • patient deprived of liberty or hospitalized without consent

Treatment and study plan

3D acquisition of maxillofacial characteristics

Diagnostic Test

A 3D acquisition of maxillofacial characteristics will be performed for each patient in order to validate a predictive model comparable to data obtained by polysomnography

Primary outcomes

  1. Establish and evaluate a predictive model for OSA diagnosis by 3D acquisition of characteristics maxillofacial

    Time frame: 1 measure at inclusion

    apnea hypopnea index will be measured by polysomnography for each patient and compared to a predictive model establish from body mass index and 3D acquisition (cricomental distance...)

Secondary outcomes

  1. Sensitivity study from different stages of OSA severity

    Time frame: 1 measure at inclusion

    OSA severity stages will be apnea hypopnea index <5, <10, <15

  2. Compare diagnosis performances of predictive model and Berlin or NoSAS questionnaires

    Time frame: 1 measure at inclusion

    Correlation between the Berlin or NoSAS score and the predictive model results

  3. Evaluate performances of the combination (Berlin questionnaire + predictive model) to estimate the OSA risk

    Time frame: 1 measure at inclusion

    Calculate the sensitivity, specificity, predictive positive value and predictive negative value of the combination

Sponsors and collaborators

Lead sponsor

University Hospital, Grenoble

Other

Collaborators

  • ARCTIC
  • ARTEHIS
  • SATT Linksium GRENOBLE

Registry information

Acronym: Episas

Important dates

Study start
2018
Primary completion
2018
Study completion
2020
First posted
Aug 15, 2018
Registry last updated
Feb 10, 2021

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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