• Ahmad A Bamagoos, Peter A Cistulli, Kate Sutherland, Melanie Madronio, Danny J Eckert, Lauren Hess, Bradley A Edwards, Andrew Wellman, and Scott A Sands.
• Sleep Research Group, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia.
• Ann Am Thorac Soc. 2019 Nov 1; 16 (11): 1422-1431.

AbstractRationale: Oral appliance therapy is efficacious in many patients with obstructive sleep apnea (OSA), but prediction of treatment outcome is challenging. Small, detailed physiological studies have identified key OSA endotypic traits (pharyngeal collapsibility and loop gain) as determinants of greater oral appliance efficacy.Objectives: We used a clinically applicable method to estimate OSA traits from routine polysomnography and identify an endotype-based subgroup of patients expected to show superior efficacy.Methods: In 93 patients (baseline apnea-hypopnea index [AHI], ≥20 events/h), we examined whether polysomnography-estimated OSA traits (pharyngeal: collapsibility and muscle compensation; nonpharyngeal: loop gain, arousal threshold, and ventilatory response to arousal) were associated with oral appliance efficacy (percentage reduction in AHI from baseline) and could predict responses to treatment. Multivariable regression (with interactions) defined endotype-based subgroups of "predicted" responders and nonresponders (based on 50% reduction in AHI). Treatment efficacy was compared between the predicted subgroups (with cross-validation).Results: Greater oral appliance efficacy was associated with favorable nonpharyngeal traits (lower loop gain, higher arousal threshold, and lower response to arousal), moderate (nonmild, nonsevere) pharyngeal collapsibility, and weaker muscle compensation (overall R2 = 0.30; adjusted R2 = 0.19; P = 0.003). Predicted responders (n = 54), compared with predicted nonresponders (n = 39), exhibited a greater reduction in AHI from baseline (mean [95% confidence interval], 73% [66-79] vs. 51% [38-61]; P < 0.0001) and a lower treatment AHI (8 [6-11] vs. 16 [12-20] events/h; P = 0.002). Differences persisted after adjusting for clinical covariates (including baseline AHI, body mass index, and neck circumference).Conclusions: Quantifying OSA traits using clinical polysomnography can identify an endotype-based subgroup of patients that is highly responsive to oral appliance therapy. Prospective validation is warranted.

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