Single-channel oximetry monitor versus in-lab polysomnography oximetry analysis: does it make a difference?

Abstract

Objective: Portable oximetry has been shown to be a promising candidate for large-scale obstructive sleep apnea screening. In polysomnography (PSG), the gold standard OSA diagnosis test, the oxygen desaturation index (ODI) is usually computed from desaturation events occurring during sleep periods only, i.e. overnight desaturations occurring during or overlapping with a wake state are excluded. However, for unattended home oximetry, all desaturations are taken into account since no reference electroencephalogram is available for sleep staging. We aim to evaluate the hypothesis that the predictive power of oximetry for OSA screening is not impaired when reference sleep stages are not available. Approach: We used a PSG clinical database of 887 individuals from a representative São Paulo (Brazil) population sample. Using features derived from the oxygen saturation time series and demographic information, OxyDOSA, a published machine learning model, was trained to distinguish between non-OSA and OSA individuals using the ODI computed while including versus excluding overnight desaturations overlapping with a wake period, thus mimicking portable and PSG oximetry analyses, respectively. Main results: When excluding wake desaturations, the OxyDOSA model had an AUROC = 94.9 ± 1.6, Se = 85.9 ± 2.8, Sp = 90.1 ± 2.6 and F1 = 86.4 ± 2.7. When considering wake desaturations, the OxyDOSA model had an AUROC = 94.4 ± 1.6, Se = 88.0 ± 2.0, Sp = 87.7 ± 2.9 and F1 = 86.2 ± 2.4. Non-inferiority was demonstrated (p = 0.049) at a tolerance level of 3%. In addition, analysis of the desaturations excluded by PSG oximetry analysis suggests that up to 21% of the total number of desaturations might actually be related to apneas or hypopneas. Significance: This analysis of a large representative population sample provided strong evidence that the predictive power of oximetry for OSA screening using the OxyDOSA model is not impaired when reference sleep stages are not available. This finding motivates the usage of portable oximetry for OSA screening.

Nocturnal oximetry in bariatric surgery patients referred to overnight in‐lab polysomnography

“…Our findings are comparable to those of other studies showing that the ODI is a useful tool in the screening and management of adult individuals with suspected OSA (17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(33)(34)(35)(36). Obesity is undoubtedly an important risk factor for OSA.…”

“…Among the various parameters derived from pulse oximetry recordings, the oxygen desaturation index (ODI), which is a measure of the number of times that a drop in SpO 2 (usually 3% or 4%) is observed per hour of sleep, is the most frequently used (17)(18)(19)(20)(21)(22)(23)(24)(25)(26). Indeed, as part of PSG, oximetry contributes to the scoring of respiratory events and consequently it is a major driver of the apnea-hypopnea index (AHI), which summarizes the OSA severity (17).…”

Digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use

“…There exist many implementations of the ODI with variable definitions. In the present work, the implementation of the ODI x detection algorithm was developed and validated by Behar et al 50 , building on the parent model and desaturation definition of Jung et al 51 . Specifically, the model of Jung et al 51 defines three fiducial points A, B, and C, to determine the occurrence of a desaturation.…”

“…List of digital oximetry biomarkers for the categories: desaturation measures and hypoxic burden. The oxygen desaturation index as defined in Jung et al and Behar et al50,51 , by default x = 3 event/h26 DL μMean of desaturations length (e.g., related work in Kulkas et al47 ) s…”

Alternative algorithms and devices in sleep apnoea diagnosis: what we know and what we expect

“…A vasoconstriction during an apnoea event will reduce blood flow to the periphery and will show artificially low oxygen saturation values when compared with other sensor positions. Independent of this complex nature of the signal, the signal itself is very intuitive and therefore much liked as a measure for sleep apnoea [ 19 ]. According to the AASM manual [ 7 ] the drop of oxygen saturation is a diagnostic criterion for defining hypopnoea events.…”