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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
SUBMITTER: Mann DL
PROVIDER: S-EPMC8664601 | biostudies-literature | 2021 Dec
REPOSITORIES: biostudies-literature