Paper Info
Title
Linear Mixed Effects Modelling Of Oxygen Desaturation After Sleep Apneas And Hypopneas: A Pilot Study
Abstract
Obstructive Sleep Apnea severity is commonly determined after a sleep polysomnographic study by the Apnea-Hypopnea Index (AHI). This index does not contain information about the duration of events, and weights apneas and hypopneas alike. Significant differences in disease severity have been reported in patients with the same AH. The aim of this work was to study the effect of obstructive event type and duration on the subsequent oxygen desaturation (SaO(2)) by mixed-effects models. These models allow continuous and categorical independent variables and can model within-subject variability through random effects. The desaturation depth dSaO(2), desaturation duration dtSaO(2) and desaturation area SaO(2)A were analyzed in the 2022 apneas and hypopneas of eight severe patients. A mixed-effects model was defined to account for the influence of event duration (AD), event type, and their interaction on SaO(2) parameters. A two-step backward model reduction process was applied for random and fixed effects optimization. The optimum model obtained for dtSaO(2) suggests an almost subject-independent proportional increase with AD, which did not significantly change in apneas as compared to hypopneas. The optimum model for dSaO(2) reveals a significantly higher increase as a function of AD in apneas than hypopneas. Dependence of dSaO(2) on event type and duration was different in every subject, and a subject-specific model could be obtained. The optimum model for SaO(2)A combines the effects of the other two. In conclusion, the proposed mixed-effects models for SaO(2) parameters allow to study the effect of respiratory event duration and type, and to include repeated events within each subject. This simple model can be easily extended to include the contribution of other important factors such as patient severity, sleep stage, sleeping position, or the presence of arousals.
Year
DOI
Venue
2019
10.1109/EMBC.2019.8857551
2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Field
DocType
Volume
Obstructive sleep apnea,Computer vision,Random effects model,Sleep apnea,Event type,Computer science,Categorical variable,Internal medicine,Cardiology,Artificial intelligence
Conference
2019
ISSN
Citations 
PageRank 
1557-170X
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Jordi Solà-Soler100.34
Beatriz F. Giraldo200.34
R Jané313143.71