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

Not Applicable

Completed

• Conditions: Obstructive Sleep Apnea
• Interventions: Diagnostic Test: 3D acquisition of maxillofacial characteristics

• Registration Number: NCT03632382
• Lead Sponsor: University Hospital, Grenoble

Brief Summary

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

Detailed Description

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.

Study Timeline

• Study Start: 2018-07-27
• Primary Completion: 2018-07-27
• Study First Submitted: 2018-08-13
• Study First Submitted QC: 2018-08-13
• Study First Posted: 2018-08-15
• Study Completion: 2020-09-08
• Status Verified: 2021-02
• Last Update Submitted: 2021-02-09
• Last Update Posted: 2021-02-10

Recruitment & Eligibility

• Status: COMPLETED
• Sex: Male
• Target Recruitment: 280

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

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: SINGLE_GROUP

Arm && Interventions

Group	Intervention	Description
OSA diagnosis with 3D acquisition	3D acquisition of maxillofacial characteristics	OSA diagnosis with 3D acquisition

Primary Outcome Measures

Name	Time	Method
Establish and evaluate a predictive model for OSA diagnosis by 3D acquisition of characteristics maxillofacial	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 Outcome Measures

Name	Time	Method
Sensitivity study from different stages of OSA severity	1 measure at inclusion	OSA severity stages will be apnea hypopnea index \<5, \<10, \<15
Compare diagnosis performances of predictive model and Berlin or NoSAS questionnaires	1 measure at inclusion	Correlation between the Berlin or NoSAS score and the predictive model results
Evaluate performances of the combination (Berlin questionnaire + predictive model) to estimate the OSA risk	1 measure at inclusion	Calculate the sensitivity, specificity, predictive positive value and predictive negative value of the combination

Trial Locations

Locations (1)

Grenoble Alpes University Hospital; 🇫🇷 Grenoble, France