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

Abstract

Background: Differences in the pharyngeal site of collapse influence efficacy of non-continuous positive airway pressure therapies for obstructive sleep apnoea (OSA). Notably, complete concentric collapse at the level of 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.

Methods: 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 (n_total=466).

Results: CCCp was characterised by greater scoopiness (β=1.5±0.6 per 2sd, multivariable estimate±se) and skewness (β=11.4±2.4) compared with non-CCCp. The odds ratio for CCCp in predicted positive versus negative subgroups was 5.0 (95% CI 1.9-13.1). The same characteristics provided significant cross-validated prediction of lateral wall (OR 6.3, 95% CI 2.4-16.5), tongue base (OR 3.2, 95% CI 1.4-7.3) and epiglottis (OR 4.4, 95% CI 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.

Conclusions: 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.

FIGURE 1

Visual inspection of characteristic event (ensemble average flow shape) for a) a representative patient with complete concentric collapse at the level of the palate (CCCp) and b) a patient with tongue base collapse. Patients with CCCp (a) exhibited increased scoopiness (higher negative effort dependence (NED)), increased inspiratory skewness (left-leaning inspiration) and greater early inspiratory peak flow, as shown. Other parameters included in the analyses were rise time, early inspiratory versus expiratory peak time and early inspiratory volume. Ensemble average flow shapes were constructed by ensemble averaging 15 breaths, centred around the scored end of the hypopnoea. Start and end points of each inspiration and expiration of each last hypopnoea breath were determined. Next, inspiration and expiration were averaged and joined back together. This process was repeated for all 15 positions of the ensemble average flow shape. A detailed overview on this technique is presented in “Visualisation of characteristic events” in the supplementary methods.

FIGURE 2

Raw individual breath data of a) patients with complete concentric collapse at the level of the palate (CCCp) and b) patients with tongue base collapse. Overall probabilities of CCCp or tongue base collapse per patient are depicted on the left-hand side of each panel. Probabilities of CCCp or tongue base collapse for individual breaths are depicted below each breath.

FIGURE 3

Simplified two-trait model “slices” for each of the five models: a) complete concentric collapse at the level of the palate (CCCp), b) lateral wall collapse (LW), c) tongue base collapse (TB), d) epiglottis collapse (EG) and e) CCCp/LW versus TB/EG. Each slice plot considers two of six features. The other four features in the model are at their mean value. Slices representing the most important model contributors (inspiratory skewness, rise time, early inspiratory volume and negative effort dependence (NED)) are depicted here. Full model representations are shown in the supplementary material. a–d) Patients with a certain collapse type are depicted in red, patients without this collapse type are depicted in green. Open circles denote patients for whom the model simplification does not apply as the other traits are too far from the mean value for this specific two-dimensional model “slice”. Background colours represent predicted presence of collapse. e) Green dots represent patients with TB or EG, red dots represent patients with CCCp or LW. Background colours depict the predicted site of collapse based on the model (green: TB or EG; red: CCCp or LW).

FIGURE 4

Repeatability analysis on a different cohort (n=18 subjects, n=36 total measurements), measured in a different centre. a) The six selected flow shape characteristics showed moderate to good reliability. b) Site of collapse prediction showed good reliability. CCCp: complete concentric collapse at the level of the palate; LW: lateral wall collapse; TB: tongue base collapse; EG: epiglottis collapse.