UZA
Edegem, Antwerp, 2650, Belgium
NCT Number: NCT04753684
OBJECTIVES
To train and test a mathematical model to predict complete concentric collapse at the level of the palate (CCCp, primary) and other sites of upper airway collapse (secondary) during drug-induced sleep endoscopy (DISE) using the data captured during a diagnostic polysomnography (PSG).
HYPOTHESIS
The site, pattern and degree of upper airway collapse is associated with distinct flow features as captured during a baseline PSG.
STUDY DESIGN
Retrospective trial.
STUDY POPULATION
200 patients with moderate to severe obstructive sleep apnea (OSA, AHI ≥ 15/h) who underwent both a DISE and a diagnostic PSG at the Antwerp University Hospital (UZA) between January 2018 and December 2020.
OUTCOME MEASURES:
Raw data as captured during a diagnostic PSG, including electroencephalography (EEG), flow, electrocardiography (ECG), electromyography (EMG), oxygen desaturation and breathing effort.
SAMPLE SIZE / DATA ANALYSIS
Data of 200 patients will be retrospectively included into this study protocol. Different machine learning techniques will be adopted to select features, train the model and test the model.
TIME SCHEDULE
January 30, 2021 - November 30, 2021
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Notify Me18 year and older
All sexes
Observational
Edegem, Antwerp, 2650, Belgium
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Time frame: Retrospective, measured during the baseline polysomnography study
The primary outcome of this study is the effect of DISE site, degree and pattern of collapse on the airflow [l/s] as measured during the baseline polysomnography
University Hospital, Antwerp
Other
Correlation Between Upper Airway Endoscopy and Physiological Traits of Obstructive Sleep Apnea: a Retrospective Study
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