Sleep structure in patients with COMISA compared to OSA and insomnia

Sleep Bruxism and Sleep Structure in Comorbid Insomnia and Obstructive Sleep Apnea (COMISA) Syndrome: A Polysomnographic Study

Introduction: Comorbid insomnia and obstructive sleep apnea (COMISA) is not a well-identified sleep disorder, despite having a significant impact on health. This study investigates the relationship between sleep bruxism (SB) and sleep architecture in patients with COMISA, obstructive sleep apnea (OSA), and in those without any sleep disorders. Methods: 119 patients were included in the study and divided into three groups: OSA, COMISA, and a control group. Polysomnographic (PSG) examination provided parameters related to sleep architecture, OSA, and characteristics of SB. Results: The bruxism episode index (BEI) and other SB parameters were not found to be statistically different between the three groups (p > 0.05). There was no statistical difference in measured sleep architecture between the COMISA and OSA groups (p > 0.05). In comparison to the control group, participants in the COMISA group were found to have an increased apnea-hypopnea index (AHI), oxygen desaturation index (ODI), respiratory disturbance index (RDI), all arousals (AA), and respiratory arousals (RA) (p < 0.05). Among COMISA patients, AA and RA were shown to have a positive linear correlation with the number of bradycardia events per hour (r = 0.49, r = 0.48, p < 0.05). Conclusions: SB does not occur in patients with COMISA more frequently than in patients with OSA or those without any sleep disorders. PSG parameters are not specific for COMISA; therefore, in order to differentiate this disorder from OSA alone, a comprehensive patient assessment has to be performed.

Multi-night home assessment of sleep structure in OSA with and without insomnia

OBJECTIVE

To explore sleep structure in participants with obstructive sleep apnea (OSA) and comorbid insomnia (COMISA) and participants with OSA without insomnia (OSA-only) using both single-night polysomnography and multi-night wrist-worn photoplethysmography/accelerometry.

METHODS

Multi-night 4-class sleep-staging was performed with a validated algorithm based on actigraphy and heart rate variability, in 67 COMISA (23 women, median age: 51 years) and 50 OSA-only (15 women, median age: 51) participants. Sleep statistics were compared using linear regression models and mixed-effects models. Multi-night variability was explored using a clustering approach and between- and within-participant analysis.

RESULTS

Polysomnographic parameters showed no significant group differences. Multi-night measurements, during 13.4 ± 5.2 nights per subject, demonstrated a longer sleep onset latency and lower sleep efficiency for the COMISA group. Detailed analysis of wake parameters revealed longer mean durations of awakenings in COMISA, as well as higher numbers of awakenings lasting 5 min and longer (WKN≥5min) and longer wake after sleep onset containing only awakenings of 5 min or longer. Within-participant variance was significantly larger in COMISA for sleep onset latency, sleep efficiency, mean duration of awakenings and WKN≥5min. Unsupervised clustering uncovered three clusters; participants with consistently high values for at least one of the wake parameters, participants with consistently low values, and participants displaying higher variability.

CONCLUSION

Patients with COMISA more often showed extended, and more variable periods of wakefulness. These observations were not discernible using single night polysomnography, highlighting the relevance of multi-night measurements to assess characteristics indicative for insomnia.

Heart rate response to cortical arousals in patients with isolated obstructive sleep apnea and with comorbid insomnia (COMISA)

PURPOSE

Comorbid insomnia often occurs in patients with obstructive sleep apnea (OSA), referred to as COMISA. Cortical arousals manifest as a common feature in both OSA and insomnia, often accompanied by elevated heart rate (HR). Our objective was to evaluate the heart rate response to nocturnal cortical arousals in patients with COMISA and patients with OSA alone.

METHODS

We analyzed data from patients with COMISA and from patients with OSA matched for apnea-hypopnea index. Sleep staging and analysis of respiratory events and cortical arousals were performed using the Philips Somnolyzer automatic scoring system. Beat-by-beat HR was analyzed from the onset of the cortical arousal to 30 heartbeats afterwards. HR responses were divided into peak and recovery phases. Cortical arousals were separately evaluated according to subtype (related to respiratory events and spontaneous) and duration (3-6 s, 6-10 s, 10-15 s).

RESULTS

A total of 72 patients with COMISA and 72 patients with OSA were included in this study. There were no overall group differences in the number of cortical arousals with and without autonomic activation. No significant differences were found for spontaneous cortical arousals. The OSA group had more cortical arousals related to respiratory events (21.0 [14.8-30.0] vs 16.0 [9.0-27.0], p = 0.016). However, the COMISA group had longer cortical arousals (7.2 [6.4-7.8] vs 6.7 [6.2-7.7] s, p = 0.024) and the HR recovery phase was prolonged (52.5 [30.8-82.5] vs 40.0 [21.8-55.5] beats/min, p = 0.017). Both the peak and the recovery phase for longer cortical arousals with a duration of 10-15 s were significantly higher in patients with COMISA compared to patients with OSA (47.0 [27.0-97.5] vs 34.0 [21.0-71.0] beats/min, p = 0.032 and 87.0 [47.0-132.0] vs 71.0 [43.0-103.5] beats/min, p = 0.049, respectively).

CONCLUSIONS

The HR recovery phase after cortical arousals related to respiratory events is prolonged in patients with COMISA compared to patients with OSA alone. This response could be indicative of the insomnia component in COMISA.

Evaluation of daytime sleepiness and insomnia symptoms in OSA patients with a characterization of symptom-defined phenotypes and their involvement in depression comorbidity-a cross-sectional clinical study

Introduction

Recent research highlights the significance of insomnia and sleepiness, shifting from obstructive sleep apnea (OSA) severity and sleep structure, in defining OSA phenotypes.

Objectives

This study aimed to characterize insomnia and sleepiness associated with OSA phenotypes and assess their involvement in depression symptoms (DS) in OSA.

Materials and methods

This cross-sectional, clinical study included 181 participants who underwent polysomnography (PSG) and filled out questionnaires, including the Epworth Sleepiness Scale (ESS), Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), and Beck Depression Index (BDI). They were categorized into phenotypes: insomnia-sleepiness (I + S; ESS ≥ 11; ISI ≥ 15; n = 20), sleepiness (S; ESS ≥ 11; ISI < 15; n = 22), insomnia (I; ESS < 11; ISI ≥ 15), and asymptomatic (A; ESS < 11; ISI<15; n=55).

Results

A linear regression model for the BDI score (R2 = 0.357, p < 0.001) included ISI score and subjective-to-objective sleep latency ratio. The ISI score was a predictive factor for mild and moderate DS [OR = 1.23 (95% CI: 1.09-1.38), p < 0.001 and OR = 1.39 (95% CI: 1.13-1.72), p = 0.002]. The I and I + S phenotypes are characterized by higher BDI scores (p < 0.001 and p = 0.02), longer subjective sleep latency (p = 0.008 and p = 0.04), and shorter subjective total sleep time (TST; p = 0.049 and p = 0.006) compared to A. Furthermore, the I and I + S groups had shorter subjective TST than S (p = 0.03 and p = 0.047). The I and I + S had higher BDI scores than A (p < 0.001 and p = 0.02, respectively) and S (p < 0.001 and p = 0.02, respectively). The I phenotype was associated with the risk of mild and moderate DS (OR = 5.61 (95% CI: 1.91-16.53), p < 0.001 and OR = 9.55 (95% CI: 1.81-50.48), p = 0.008 respectively). Moreover, the I + S phenotype presented an even greater risk for mild DS (OR = 10.29 (95% CI: 2.95-35.85), p < 0.001).

Conclusion

Using clinical features for OSA phenotyping holds promise for finding OSA individuals with increased risk for DS occurrence.

EEG Power Spectral Density in NREM Sleep is Associated with the Degree of Hypoxia in Patients with Obstructive Sleep Apnea

Purpose

Obstructive sleep apnea (OSA) is a prevalent sleep-related breathing disorder. Research conducted on patients with OSA using electroencephalography (EEG) has revealed a noticeable shift in the overnight polysomnography (PSG) power spectrum. To better quantify the effects of OSA on brain function and to identify the most reliable predictors of pathological cortical activation, this study quantified the PSG power and its association with the degree of hypoxia in OSA patients.

Patients and Methods

This retrospective study recruited 93 patients with OSA. OSA patients were divided into three groups based on their apnea-hypopnea index (AHI) scores. The clinical characteristics and sleep macrostructure of these patients were examined, followed by an analysis of PSG signals. Power spectral density (PSD) in five frequency bands was analyzed during nonrapid eye movement (NREM) sleep, rapid eye movement (REM) sleep, and wakefulness. Finally, correlation analysis was conducted to assess the relationships among PSD, PSG parameters, and serum levels of S100β and uric acid.

Results

Obstructive sleep apnea occurred during both the NREM and REM sleep phases. Except for a decrease in the duration of N2 sleep and an increase in the microarousal index, there were no significant differences in sleep architecture based on disease severity. Compared to the mild OSA group, the theta and alpha band PSD in the frontal and occipital regions during NREM sleep and wakefulness were significantly decreased in the moderate and severe OSA groups. Correlation analysis revealed that theta PSD in N1 and N3 stages were negatively correlated the AHI, oxygen desaturation index, SaO2<90% and microarousal index.

Conclusion

These findings imply that patients with more severe OSA exhibited considerable NREM hypoxia and abnormal brain activity in the frontal and occipital regions. Therefore, sleep EEG oscillation may be a useful neurophysiological indicator for assessing brain function and disease severity in patients with OSA.