Predicting complete concentric collapse at the palatal level during drug-induced sleep endoscopy: an analysis of 1761 cases

Abstract

Purpose: Drug-induced sleep endoscopy (DISE) helps select patients with obstructive sleep apnea (OSA) for surgery by identifying upper airway collapse patterns. This study aimed to predict the probability of complete concentric collapse at the palatal level (CCCp) during DISE based on patient characteristics, specifically body mass index (BMI).

Methods: We retrospectively reviewed records of OSA patients who underwent DISE from January 2018 to July 2023. Logistic regression with receiver operating characteristic (ROC) analysis and classification and regression tree (CART) analysis were used to assess the diagnostic efficiency of BMI and other predictors for CCCp.

Results: A consecutive series of 1761 eligible patients was included for analysis. CCCp was observed in 22.3% of cases. The CCCp group had significantly higher BMI, neck circumference, apnea-hypopnea index (AHI) and height as well as increase in partial and complete collapse at oropharyngeal level. The ROC analysis for predicting CCCp for a BMI cut-off was similar for males and females 29.4 kg/m² and 29.5 kg/m², with an area under the curve (AUC) of 0.65 and 0.73, respectively. Adding predictors like tonsils, AHI, height and neck circumference improved the model's performance.

Conclusion: Although confirming an association between increasing BMI and presence of CCCp, we were unable to define an accurate BMI cut-off value for predicting CCCp. The multifactorial nature of this collapse pattern challenges BMI's efficacy as a sole predictor. Our findings underscore the continued importance of DISE in evaluating CCCp and other collapse patterns for clinical decision-making in patients considered for hypoglossal nerve stimulation therapy.

Keywords: Complete concentric collapse (CCCp); Drug-induced sleep endoscopy (DISE); Hypoglossal nerve stimulation (HGNS); Obstructive sleep apnea (OSA); Prediction; Sleep surgery.