Breathing Disturbances Without Hypoxia Are Associated With Objective Sleepiness in Sleep Apnea

Abstract

Study objectives: To determine whether defining two subtypes of sleep-disordered breathing (SDB) events-with or without hypoxia-results in measures that are more strongly associated with hypertension and sleepiness.

Methods: A total of 1022 participants with 2112 nocturnal polysomnograms from the Wisconsin Sleep Cohort were analyzed with our automated algorithm, developed to detect breathing disturbances and desaturations. Breathing events were time-locked to desaturations, resulting in two indices-desaturating (hypoxia-breathing disturbance index [H-BDI]) and nondesaturating (nonhypoxia-breathing disturbance index [NH-BDI]) events-regardless of arousals. Measures of subjective (Epworth Sleepiness Scale) and objective (2981 multiple sleep latency tests from a subset of 865 participants) sleepiness were analyzed, in addition to clinically relevant clinicodemographic variables. Hypertension was defined as BP ≥ 140/90 or antihypertensive use.

Results: H-BDI, but not NH-BDI, correlated strongly with SDB severity indices that included hypoxia (r ≥ 0.89, p ≤ .001 with 3% oxygen-desaturation index [ODI] and apnea hypopnea index with 4% desaturations). A doubling of desaturation-associated events was associated with hypertension prevalence, which was significant for ODI but not H-BDI (3% ODI OR = 1.06, 95% CI = 1.00-1.12, p < .05; H-BDI OR 1.04, 95% CI = 0.98-1.10) and daytime sleepiness (β = 0.20 Epworth Sleepiness Scale [ESS] score, p < .0001; β = -0.20 minutes in MSL on multiple sleep latency test [MSLT], p < .01). Independently, nondesaturating event doubling was associated with more objective sleepiness (β = -0.52 minutes in MSL on MSLT, p < .001), but had less association with subjective sleepiness (β = 0.12 ESS score, p = .10). In longitudinal analyses, baseline nondesaturating events were associated with worsening of H-BDI over a 4-year follow-up, suggesting evolution in severity.

Conclusions: In SDB, nondesaturating events are independently associated with objective daytime sleepiness, beyond the effect of desaturating events.

Keywords: Outcome Assessment (Health Care); Pattern recognition; automated; sleep apnea syndromes.

Figure 1

Demonstration of algorithm-tagged events. Two 120-second epochs of sleep from the same individual, demonstrating (A) two desaturation-associated breathing disturbances (contributing to H-BDI) and (B) one nondesaturating breathing disturbance (contributing to NH-BDI).

Figure 2

Participants’ mean event duration, stratified by index. Boxplot of event durations with central line demonstrating mean of individual means, the box ends demonstrating 2 SD around the mean, and the whiskers demonstrating range of individual means. All pairwise comparisons between indices were significantly different, p < .05. Abbreviations: BDI = breathing disturbance index, H-BDI = desaturation-associated breathing disturbance index, NH-BDI = nondesaturation-associated breathing disturbance index.

Figure 3

Relationship of breathing variables with subjective and objective sleepiness. Visual demonstration of the impact of changes in (A) Epworth sleepiness scale (ESS) score and (B) mean sleep latency (MSL) on multiple sleep latency testing, based on back-transformation of the log₂-transformed predictor variables (the indices) used in the original linear modeling (Table 4). The log₂-transformation results in changes in the outcomes of interest (ESS score and MSL) for every doubling of event rate. A broken line was introduced in (A) because of overlap of the models for ODI3 and H-BDI. Abbreviations: ODI3 = 3% desaturation ODI criterion; BDI = total breathing disturbance index; H-BDI = breathing disturbance index with associated oxygen desaturations; NH-BDI = breathing disturbance index without associated oxygen desaturations.