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Related Experiment Videos

Predicting epiglottic collapse in patients with obstructive sleep apnoea.

Ali Azarbarzin1, Melania Marques2,3, Scott A Sands2,4

  • 1Division of Sleep and Circadian Disorders, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA aazarbarzin@bwh.harvard.edu.

The European Respiratory Journal
|September 22, 2017
PubMed
Summary

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Detecting epiglottic collapse in obstructive sleep apnoea (OSA) is now possible using airflow patterns during sleep. This non-invasive method aids in better treatment decisions for OSA patients.

Area of Science:

  • Respiratory Medicine
  • Sleep Medicine
  • Biomedical Engineering

Background:

  • Obstructive sleep apnoea (OSA) involves pharyngeal obstruction at various sites.
  • Epiglottic collapse is a significant risk factor for treatment failure in OSA.
  • Current diagnosis of epiglottic collapse requires invasive endoscopic or imaging studies.

Purpose of the Study:

  • To investigate the potential of using airflow patterns during sleep to detect epiglottic collapse.
  • To develop a predictive model for identifying epiglottic collapse non-invasively.

Main Methods:

  • Natural sleep endoscopy was performed on 23 OSA patients.
  • Airflow signals were recorded simultaneously with endoscopy to analyze breath characteristics.
  • A predictive model was built using flow features to differentiate epiglottic from nonepiglottic collapse.

Related Experiment Videos

  • Nasal pressure signals were used to validate pneumotachograph flow features in 10 OSA patients.

    • Main Results:

    • Epiglottic collapse is characterized by rapid inspiratory flow falls, increased flow variability, and reduced tidal volume.
    • The developed predictive model achieved a cross-validated accuracy of 84% in identifying epiglottic collapse.
    • Pneumotachograph and nasal pressure flow features showed strong correlations.

    Conclusions:

    • Airflow signals measured during sleep studies can effectively identify epiglottic collapse.
    • This non-invasive approach offers a promising alternative for diagnosing epiglottic collapse.
    • The findings may improve clinical characterization of OSA physiology and guide treatment strategies.