Frequency of flow limitation using airflow shape

Author:

Mann Dwayne L123ORCID,Georgeson Thomas14ORCID,Landry Shane A35ORCID,Edwards Bradley A35ORCID,Azarbarzin Ali6ORCID,Vena Daniel6ORCID,Hess Lauren B6,Wellman Andrew6,Redline Susan6,Sands Scott A6,Terrill Philip I1

Affiliation:

1. School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia

2. Institute for Social Science Research, University of Queensland, Brisbane, Australia

3. Department of Physiology, School of Biomedical Sciences and Biomedical Discovery Institute, Monash University, Melbourne, Australia

4. Faculty of Medicine, University of Queensland, Brisbane, Australia

5. School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia

6. Division of Sleep and Circadian Disorders, Department of Medicine, Brigham & Women’s Hospital & Harvard Medical School, Boston, MA, USA

Abstract

Abstract Study Objectives The presence of flow limitation during sleep is associated with adverse health consequences independent of obstructive sleep apnea (OSA) severity (apnea-hypopnea index, AHI), but remains extremely challenging to quantify. Here we present a unique library and an accompanying automated method that we apply to investigate flow limitation during sleep. Methods A library of 117,871 breaths (N = 40 participants) were visually classified (certain flow limitation, possible flow limitation, normal) using airflow shape and physiological signals (ventilatory drive per intra-esophageal diaphragm EMG). An ordinal regression model was developed to quantify flow limitation certainty using flow-shape features (e.g. flattening, scooping); breath-by-breath agreement (Cohen’s ƙ); and overnight flow limitation frequency (R2, %breaths in certain or possible categories during sleep) were compared against visual scoring. Subsequent application examined flow limitation frequency during arousals and stable breathing, and associations with ventilatory drive. Results The model (23 features) assessed flow limitation with good agreement (breath-by-breath ƙ = 0.572, p < 0.001) and minimal error (overnight flow limitation frequency R2 = 0.86, error = 7.2%). Flow limitation frequency was largely independent of AHI (R2 = 0.16) and varied widely within individuals with OSA (74[32–95]%breaths, mean[range], AHI > 15/h, N = 22). Flow limitation was unexpectedly frequent but variable during arousals (40[5–85]%breaths) and stable breathing (58[12–91]%breaths), and was associated with elevated ventilatory drive (R2 = 0.26–0.29; R2 < 0.01 AHI v. drive). Conclusions Our method enables quantification of flow limitation frequency, a key aspect of obstructive sleep-disordered breathing that is independent of the AHI and often unavailable. Flow limitation frequency varies widely between individuals, is prevalent during arousals and stable breathing, and reveals elevated ventilatory drive. Clinical trial registration: The current observational physiology study does not qualify as a clinical trial.

Funder

National Health and Medical Research Council

American Heart Association

National Heart Foundation of Australia

National Institutes of Health

American Academy of Sleep Medicine Foundation

AASM Foundation

Publisher

Oxford University Press (OUP)

Subject

Physiology (medical),Neurology (clinical)

Reference55 articles.

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