Polysomnographic airflow shapes and site of collapse during drug-induced sleep endoscopy

Differences in the pharyngeal site-of-collapse influences efficacy of non-CPAP therapies for obstructive sleep apnoea (OSA). Notably, complete concentric collapse at the palate (CCCp) during drug-induced sleep endoscopy (DISE) is associated with reduced efficacy of hypoglossal nerve stimulation, but CCCp is currently not recognisable using polysomnography. Here we develop a means to estimate DISE-based site-of-collapse using overnight polysomnography.182 OSA patients provided DISE and polysomnography data. Six polysomnographic flow-shape characteristics (mean during hypopnoeas) were identified as candidate predictors of CCCp (primary outcome variable, N=44/182), including inspiratory skewness and inspiratory scoopiness. Multivariable logistic regression combined the six characteristics to predict clear presence (N=22) versus absence (N=128) of CCCp (partial collapse and concurrent tongue-base collapse excluded). Odds ratios for actual CCCp between predicted subgroups were quantified after cross-validation. Secondary analyses examined complete lateral wall, tongue-base, or epiglottis collapse. External validation was performed on a separate dataset (Ntotal=466).CCCp was characterised by greater scoopiness (β=1.5±0.6 per 2SD, multivariable estimate±se) and skewness (β=11.4±2.4) compared to non-CCCp. Odds ratio [95%CI] for CCCp in predicted positive versus negative subgroups was 5.0[1.9-13.1]. The same characteristics provided significant cross-validated prediction of lateral wall (OR=6.3[2.4-16.5]), tongue-base (3.2[1.4-7.3]), and epiglottis (4.4[1.5-12.4]) collapse. CCCp and lateral wall collapse shared similar characteristics (skewed, scoopy), diametrically opposed to tongue-base and epiglottis collapse characteristics. External validation confirmed model prediction.The current study provides a means to recognise patients with likely CCCp or other DISE-based site-of-collapse categories using routine polysomnography. Since site-of-collapse influences therapeutic responses, polysomnographic airflow shape analysis could facilitate precision site-specific OSA interventions.