Profile of subjective-objective sleep discrepancy in patients with insomnia and sleep apnea

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.

Effects of Temperature, Duration, and Heating Height of Foot Thermal Therapy on Sleep Quality of Older Adults: A Systematic Review and Meta-Analysis

Background: Sleep disturbances, which are common problems in older adults, often lead to cognitive decline and depression and may even increase mortality risk. Foot thermal therapy is a simple and safe approach for improving sleep and is associated with relatively few side effects. However, the effect of different operations of foot thermal therapy on sleep quality in older adults is inconclusive. This study aimed to access the effects of temperature, duration, and heating height of foot thermal therapy (administered through a footbath) on the subjective and objective sleep quality of older adults. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline, eight databases were searched for all relevant articles published up to July 2023, and a rigorous systematic review and meta-analysis was conducted. This study was registered in the PROSPERO database (CRD42022383460). Inclusion criteria were: (1) participants with a mean age ≥60 years; (2) interventions that included foot thermal therapy; (3) a control group that received routine care but no thermal therapy; (4) outcome measurements that assessed sleep quality; and (5) the studies that utilized randomized controlled trials or quasi-experimental studies. Methodological quality was assessed using the Joanna Briggs Institute critical appraisal tools. The meta-analysis was performed using RevMan version 5.4. Results: A total of 11 studies were included. Foot thermal therapy before bedtime improved subjective sleep quality in older adults, with optimal parameters of 40°C temperature (standardized mean difference [SMD] = 0.66, 95% confidence interval [CI]: 0.33 to 0.99), ≤20-min duration (SMD = 0.66, 95% CI: 0.39 to 0.93), and 10 cm heating height (SMD = 0.78, 95% CI: 0.45 to 1.11). Subgroup analyses revealed that a temperature of 41°C-42°C can improve objective sleep latency (SMD = 0.54, 95% CI: 0.09 to 0.99). Conclusions: It is recommended to administer foot thermal therapy (40°C; ≤20 min; 10 cm above the ankle) to older adults 1 h before their bedtime. If they have trouble falling asleep, the temperature can be increased to 41°C-42°C.

Reconsidering sleep perception in insomnia: from misperception to mismeasurement

So-called 'sleep misperception' refers to a phenomenon in which individuals have the impression of sleeping little or not at all despite normal objective measures of sleep. It is unknown whether this subjective-objective mismatch truly reflects an abnormal perception of sleep, or whether it results from the inability of standard sleep recording techniques to capture 'wake-like' brain activity patterns that could account for feeling awake during sleep. Here, we systematically reviewed studies reporting sleep macro- and microstructural, metabolic, and mental correlates of sleep (mis)perception. Our findings suggest that most individuals tend to accurately estimate their sleep duration measured with polysomnography (PSG). In good sleepers, feeling awake during sleep is the rule at sleep onset, remains frequent in the first non-rapid eye movement sleep cycle and almost never occurs in rapid eye movement (REM) sleep. In contrast, there are patients with insomnia who consistently underestimate their sleep duration, regardless of how long they sleep. Unlike good sleepers, they continue to feel awake after the first sleep cycle and importantly, during REM sleep. Their mental activity during sleep is also more thought-like. Initial studies based on standard PSG parameters largely failed to show consistent differences in sleep macrostructure between these patients and controls. However, recent studies assessing sleep with more refined techniques have revealed that these patients show metabolic and microstructural electroencephalography changes that likely reflect a shift towards greater cortical activation during sleep and correlate with feeling awake. We discuss the significance of these correlates and conclude with open questions and possible ways to address them.

Investigating sleep quality and sleep hygiene awareness among Chinese adults: an association and network analysis study

PURPOSE

The relationships between sleep quality and sleep hygiene awareness in the Chinese population were unclear. We aimed to investigate the associations and related factors between sleep quality and sleep hygiene awareness in adults and to identify the most central domain for sleep quality using network analysis.

METHODS

A cross-sectional survey was conducted from April 22 to May 5, 2020. Adults (18 years old or above) who had access to smartphones were invited to participate in this survey. The Pittsburg Sleep Quality Index (PSQI) and the Sleep Hygiene Awareness and Practice Scale (SHAPS) were used to evaluate the sleep quality and sleep hygiene awareness of the participants. Propensity score matching (PSM) was used as sensitivity analysis to reduce the confounding effects. Multiple logistic regression was performed to evaluate the associations. The R packages "bootnet" and "qgraph" were used to estimate the connection and calculate the network centrality indices between good and poor sleepers.

RESULTS

In total, 939 respondents were included in the analysis. Of them, 48.8% (95% CI: 45.6-52.0%) were identified as poor sleepers. Participants with nervous system diseases, psychiatric diseases, and psychological problems were more likely to have poor sleep quality. The notion that using sleep medication regularly was beneficial to sleep was associated with poor sleep quality. Similarly, the notion that waking up at the same time each day disrupted sleep was also associated with poor sleep quality. The findings were consistent before and after PSM. Subjective sleep quality was the most central domain for sleep quality in good and poor sleepers.

CONCLUSION

Poor sleep quality was positively associated with certain sleep hygiene notions in Chinese adults. Effective measures such as self-relief, sleep hygiene education, and cognitive behavioral treatment may have been needed to improve sleep quality, especially during the COVID-19 outbreak.

Clinical phenotypes of obstructive sleep apnea: a cluster analysis based on sleep perception and sleep quality

PURPOSE

To determine obstructive sleep apnea (OSA) phenotypes using cluster analysis including variables of sleep perception and sleep quality and to further explore factors correlated with poor sleep quality in different clusters.

METHODS

This retrospective study included patients with OSA undergoing polysomnography (PSG) between December 2020 and April 2022. Two-step cluster analysis was performed to detect distinct clusters using sleep perception variables including discrepancy in total sleep time (TST), sleep onset latency (SOL), and wakefulness after sleep onset (WASO); objective TST, SOL, and WASO; and sleep quality. One-way analysis of variance or chi-squared tests were used to compare clinical and PSG characteristics between clusters. Binary logistic regression analyses were used to explore factors correlated with poor sleep quality.

RESULTS

A total of 1118 patients were included (81.6% men) with mean age ± SD 43.3 ± 13.1 years, Epworth sleepiness score, 5.7 ± 4.4, and insomnia severity index 3.0 ± 2.4. Five distinct OSA clusters were identified: cluster 1 (n = 254), underestimated TST; cluster 2 (n = 158), overestimated TST; cluster 3 (n = 169), overestimated SOL; cluster 4 (n = 155), normal sleep discrepancy and poor sleep quality; and cluster 5 (n = 382), normal sleep discrepancy and good sleep quality. Patients in cluster 2 were older, more commonly had hypertension, and had the lowest apnea-hypopnea index and oxygen desaturation index. Age and sleep efficiency were correlated with poor sleep quality in clusters 1, 2, and 5, and also AHI in cluster 2.

CONCLUSION

Subgroups of patients with OSA have different patterns of sleep perception and quality that may help us to further understand the characteristics of sleep perception in OSA and provide clues for personalized treatment.

Relationship between Symptom Profiles and Endotypes among Patients with Obstructive Sleep Apnea: A Latent Class Analysis

Rationale: Obstructive sleep apnea (OSA) is a heterogeneous syndrome with various endotypic traits and symptoms. A link among symptoms, endotypes, and disease prognosis has been proposed but remains unsupported by empirical data. Objectives: To link symptom profiles and endotypes by clustering endotypic traits estimated using polysomnographic signals. Methods: We recruited 509 patients with moderate to severe OSA from a single sleep center. Polysomnographic data were collected between May 2020 and January 2022. Endotypic traits, namely arousal threshold, upper airway collapsibility, loop gain, and upper airway muscle compensation, were retrieved using polysomnographic signals during non-rapid eye movement periods. We used latent class analysis to group participants into endotype clusters. Demographic and polysomnographic parameter differences were compared between clusters, and associations between endotype clusters and symptom profiles were examined using logistic regression analyses. Results: Three endotype clusters were identified, characterized by high collapsibility/loop gain, low arousal threshold, and low compensation, respectively. Patients in each cluster exhibited similar demographic characteristics, but those in the high collapsibility/loop gain cluster had the highest proportion of obesity and severe oxygen desaturation observed in polysomnographic studies. The low compensation cluster was characterized by fewer sleepy symptoms and exhibited a lower rate of diabetes mellitus. Compared with the excessively sleepy group, disturbed sleep symptoms were associated with the low arousal threshold cluster (odds ratio, 1.89; 95% confidence interval, 1.16-3.10). Excessively sleepy symptoms were associated with the high collapsibility/loop gain cluster (odds ratio, 2.16; 95% confidence interval, 1.39-3.37) compared with the minimally symptomatic group. Conclusions: Three pathological endotype clusters were identified among patients with moderate to severe OSA, each exhibiting distinct polysomnographic characteristics and clinical symptom profiles.

Sleep structure in patients with COMISA compared to OSA and insomnia

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) and insomnia frequently co-occur, making diagnosis and treatment challenging. We investigated differences in sleep structure between patients with OSA, insomnia, and comorbid insomnia and sleep apnea (COMISA) to identify characteristics that can be used to improve the diagnosis of COMISA.

METHODS

We obtained polysomnography data of 326 patients from the Sleep and OSA Monitoring with Non-Invasive Applications database. The group included patients with OSA (n = 199), insomnia (n = 47), and COMISA (n = 80). We compared statistics related to sleep structure between the 3 patient groups.

RESULTS

Wake after sleep onset was significantly shorter for the OSA group (median: 60.0 minutes) compared to the COMISA (median: 83.3 minutes, P < .01) and the insomnia (median: 83.5 minutes, P = .01) groups. No significant differences were found in the total number of awakenings and the number of short (up to and including 2 minutes) and medium-length awakenings (2.5 up to and including 4.5 minutes). However, the number of long awakenings (5 minutes or longer) and wake after sleep onset containing only long awakenings was significantly lower for patients with OSA (median: 2 awakenings and 25.5 minutes) compared to patients with COMISA (median: 3 awakenings, P < .01 and 43.3 minutes, P < .001) or with insomnia (median: 3 awakenings, P < .01 and 56.0 minutes, P < .001). Total sleep time was significantly longer and sleep efficiency was significantly higher for the OSA group (median: 418.5 minutes and 84.4%) compared to both the COMISA (median: 391.5 minutes, P < .001 and 77.3%, P < .001) and the insomnia (median: 381.5 minutes, P < .001 and 78.2%, P < .001) groups. The number of sleep-stage transitions during the night for patients with COMISA (median: 194.0) was lower compared to that for patients with OSA (median: 218.0, P < .01) and higher compared to that for patients with insomnia (median: 156.0, P < .001). Other sleep architectural parameters were not discriminative between the groups.

CONCLUSIONS

Patients with COMISA show specific characteristics of insomnia, including prolonged awakenings. This variable is distinctive in comparison to patients with OSA. The combination of prolonged awakenings and the presence of sleep-disordered breathing leads to increased sleep disturbance compared to patients having only 1 of the sleep disorders.

CITATION

Wulterkens BM, Hermans LWA, Fonseca P, et al. Sleep structure in patients with COMISA compared to OSA and insomnia. J Clin Sleep Med. 2023;19(6):1051-1059.

More than sleepiness: prevalence and relevance of nonclassical symptoms of obstructive sleep apnea

PURPOSE OF REVIEW

The purpose of this review is to describe the nonclassical symptoms and manifestations occurring in patients with obstructive sleep apnea (OSA), both from a standpoint of prevalence and in terms of clinical relevance. Particular emphasis will be given to nightmares, comorbid insomnia, restless legs syndrome and periodic limb movement disorder, bruxism, morning headache, nocturia, acid reflux, chronic cough and dysphagia.

RECENT FINDINGS

A review of the recent literature suggests that nonclassical symptoms have a high prevalence, are underestimated, and can interact with quality of life. Although these disturbances may occur together by mere coincidence, they may interact reciprocally. However, the degree of symptoms is not always correlated with OSA severity.

SUMMARY

OSA is a heterogeneous disease with variable clinical manifestations. This review highlights the need for detailed evaluation of patients with OSA to diagnose other important sleep disorders and clinical manifestations, given their frequent association.

Discrepancy between subjective and objective sleep duration among dementia caregivers and non-caregivers

STUDY OBJECTIVES

Poor sleep, including short sleep duration, is common among caregivers of persons with dementia. However, it is unclear whether poor sleep is consistent across both self-reported and objective measures of sleep in caregivers. This study aimed to test the role of caregiving status (caregivers vs. non-caregivers) on the discrepancy between self-reported and objective sleep duration.

METHODS

This was a cross-sectional study. Study participants were community-dwelling caregivers of spouses with dementia (n=122) and non-caregivers (n=53). A sleep duration discrepancy index was created by subtracting objective sleep duration measured with three consecutive 24-hour periods of actigraphy from self-reported sleep duration measured with the Pittsburgh Sleep Quality Index. Covariates included participants' demographic characteristics, depressive symptoms, positive and negative affect, personal mastery, and caregiving-role overload.

RESULTS

Caregivers showed a greater discrepancy in sleep duration than did non-caregivers (-0.46 hour vs. 0.22 hour, respectively; p=0.003). In a regression model, however, caregiving status was no longer associated with this sleep duration discrepancy, when accounting for covariates. Higher positive affect was significantly associated with less sleep duration discrepancy (R²=11.3%, p=0.014). Sobel's test of mediation showed that 26% of the effect of caregiving on this sleep discrepancy was attributable to caregivers with low positive affect.

CONCLUSIONS

The findings suggest a potential mediating role of positive affect on the relationship between caregiving status and sleep duration discrepancy. As an aid for understanding the role of lower positive affect, use of actigraphy may be useful to address sleep discrepancy in caregivers.

Chronic Lumbar Pain and Insomnia in College-Aged Students

Insomnia in college students has a significant impact on academic performance and mental health (e.g., depression). Although the mechanisms underlying insomnia and chronic pain are becoming clearer, only a few studies on college students have examined these factors by their location in the body. The purpose of the present study was to identify the location of chronic pain in the body most associated with insomnia in college students. A web-based survey was used to collect information pertaining to nine questions from 494 university students: sex, age, presence of chronic pain, intensity of chronic pain, location of chronic pain, and duration of chronic pain, as well as scores from the Athens Insomnia Scale (AIS), Pain Catastrophizing Scale, and Hospital Anxiety and Depression Scale. To examine the association between insomnia and the site of chronic pain, stepwise logistic regression analysis was conducted with AIS as the target variable. The results showed a significant positive correlation between chronic pain in the lumbar region and AIS scores. Future longitudinal studies including multiple factors are necessary to clarify the causal relationship between insomnia and chronic lower back pain.

Prolonged Sleep Latency and Reduced REM Latency Are Associated with Depressive Symptoms in a Japanese Working Population

Background: Examining the relationship between sleep and depression may be important for understanding the aetiology of affective disorders. Most studies that use electroencephalography (EEG) to objectively assess sleep have been conducted using polysomnography in the laboratory. Impaired sleep continuity, including prolonged sleep latency and changes in rapid eye movement (REM) sleep, have been reported to be associated with depression in clinical settings. Here, we aimed to use home EEG to analyse the association between sleep and depressive symptoms. Methods: We performed a cross-sectional epidemiological study in a large Japanese working population to identify the EEG parameters associated with depressive symptoms based on the results of a questionnaire survey and home EEG measurements using 1-channel (1-Ch) EEG. Results: The study included 650 Japanese patients (41.2% male, 44.7 ± 11.5 years) who underwent home EEG monitoring along with the Patient Health Questionnaire-9 (PHQ-9) to assess depressive symptoms. Logistic regression analysis revealed that depressive symptoms (PHQ-9 ≥ 10) were associated with sleep latency (odds ratio (OR) 1.02; 95% confidence interval (CI): 1.00–1.04) and REM latency (OR, 0.99; 95% CI: 0.99–1.00). Conclusions: Our results suggest that depressive symptoms are associated with prolonged sleep latency and reduced REM latency in a Japanese working population. The 1-Ch EEG may be a useful tool to monitor sleep and screen depression/depressive symptoms in non-clinical settings.

The Effect of Cognitive Behavioural Therapy for Insomnia (CBT-I) on Subjective–Objective Sleep Discrepancy in Individuals with Co-Morbid Insomnia and Sleep Apnoea: A Randomised Controlled Trial

People with insomnia frequently underestimate the duration of their sleep compared to objective polysomnography-measured sleep duration. Cognitive behavioural therapy for insomnia (CBT-I) is the most effective treatment for insomnia and also reduces the degree of sleep underestimation. Obstructive sleep apnoea (OSA) is a highly prevalent sleep disorder characterised by frequent narrowing (hypopnoea) and closure (apnoea) of the upper airway during sleep. Comorbid insomnia and sleep apnoea (COMISA) is a prevalent and debilitating disorder. No study has investigated subjectively (sleep diary) versus objectively (polysomnography) measured sleep discrepancies (SOSD) in individuals with COMISA before or following CBT-I. This randomised waitlist-controlled trial investigated SOSD in 145 participants with COMISA before and 6-weeks after CBT-I (n = 72) versus control (n = 73). All participants were studied prior to continuous positive airway pressure treatment for sleep apnoea. At baseline, participants underestimated their total sleep time (mean ± SD −51.9 ± 94.1 min) and sleep efficiency (−9.6 ± 18.3%), and overestimated sleep onset latency (34.5 ± 86.1 min; all p = < 0.001). Mixed models indicated a main effect of time on reduction of SOSD in both groups, but no between-group difference in the reduction of any SOSD parameters. These findings may indicate that untreated OSA contributes to a discrepancy between perceived and objective sleep parameters in people with COMISA that is not amenable to CBT-I alone (ACTRN12613001178730).

Multi-Scale Permutation Entropy: A Potential Measure for the Impact of Sleep Medication on Brain Dynamics of Patients with Insomnia

Insomnia is a common sleep disorder that is closely associated with the occurrence and deterioration of cardiovascular disease, depression and other diseases. The evaluation of pharmacological treatments for insomnia brings significant clinical implications. In this study, a total of 20 patients with mild insomnia and 75 healthy subjects as controls (HC) were included to explore alterations of electroencephalogram (EEG) complexity associated with insomnia and its pharmacological treatment by using multi-scale permutation entropy (MPE). All participants were recorded for two nights of polysomnography (PSG). The patients with mild insomnia received a placebo on the first night (Placebo) and temazepam on the second night (Temazepam), while the HCs had no sleep-related medication intake for either night. EEG recordings from each night were extracted and analyzed using MPE. The results showed that MPE decreased significantly from pre-lights-off to the period during sleep transition and then to the period after sleep onset, and also during the deepening of sleep stage in the HC group. Furthermore, results from the insomnia subjects showed that MPE values were significantly lower for the Temazepam night compared to MPE values for the Placebo night. Moreover, MPE values for the Temazepam night showed no correlation with age or gender. Our results indicated that EEG complexity, measured by MPE, may be utilized as an alternative approach to measure the impact of sleep medication on brain dynamics.