Abstract

Abstract Introduction Apnea-hypopnea index (AHI), a frequency-based index commonly used to define the severity of obstructive sleep apnea (OSA), fails to capture the risk related to OSA. Sleep apnea-specific hypoxic burden (SASHB) appears to be more predictive of OSA-related risk than AHI but has only been studied in cohorts of untreated individuals. This is the first assessment of the ability of precision oral appliance therapy (OAT) to reduce SASHB and the use of SASHB, rather than AHI, to define therapeutic efficacy. Methods Data previously obtained from a clinical study investigating prediction of response to precision OAT in OSA were analyzed. Study participants with OSA (n = 11 mild, n = 19 moderate, and n = 18 severe) completed two-night level 3 home sleep tests before and after receiving a precision oral appliance (ProSomnus Sleep Technologies, Pleasanton, CA). Apnea-hypopnea index and SASHB were calculated. For SASHB, a cut-off of 53 %min/h was selected based on data suggesting that values above this limit are associated with OSA-related risk; for AHI, cut-offs of < 10 h-1 and < 15 h-1 were selected due to their widespread use in clinical practice. Results Precision oral appliance therapy reduced AHI from 31.6 ± 19.2 h-1 to 11.7 ± 15.8 h-1 (p < 0.001) and SASHB from 83.2 ± 63.6 %min/h to 25.2 ± 42.3 %min/h (p < 0.001). Using an AHI-based definition of therapeutic efficacy, 83% (for AHI < 15 h-1) and 71% (for AHI < 10 h-1) of participants achieved efficacy with precision OAT. However, when the risk-based SASHB definition of therapeutic efficacy (SASHB < 53 %min/h) was used, precision OAT efficacy increased to 90%. Conclusion In the population studied, precision OAT significantly improved SASHB. The use of AHI, a frequency-based index of OSA, appears to misclassify some individuals as therapeutic non-responders to precision OAT despite their having an SASHB in the low-risk range. Sleep apnea-specific hypoxic burden likely provides a more meaningful assessment of OSA treatment efficacy as it accounts for the risk associated with the disease. Support (if any) This work was supported by ProSomnus Sleep Technologies.

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