Analysis of Clinical Characteristics and Polysomnography Indicators of Obstructive Sleep Apnea-Hypopnea Syndrome Patients Based on Sleep Perception Types

A scoping review of sleep discrepancy methodology: What are we measuring and what does it mean?

STUDY OBJECTIVES

To examine how past studies have conceptualised sleep discrepancy and identify and evaluate the methods used for its measurement and analysis.

METHOD

We searched MEDLINE, Embase, PsycINFO, CINAHL Plus, PubMed, Scopus, and Web of Science in April 2022 for studies comparing self-report and objective measures of sleep. Methodological information was extracted from relevant studies and included measures of self-report and objective sleep, sleep variables (e.g., total sleep time), derived discrepancy indices (e.g., difference scores), handling of repeated measurements, and methods of measure comparison (e.g., Bland-Altman analyses).

RESULTS

Two hundred and forty-four relevant records were identified. Studies varied according to objective sleep measure; actigraphy algorithm, software, and rest interval; polysomnography setting and scoring criteria; sleep variables; self-report sleep measure; number of nights of objective recording; time frame of self-report measure; self-report sleep variable definition; sleep discrepancy derived index; presence and handling of repeated measurements; and statistical method for measure comparison.

CONCLUSIONS

Sleep discrepancy was predominantly conceived as discordance in sleep states or sleep time variables, and various forms of this discordance differed in their conceptual distance to sleep misperception. Furthermore, studies varied considerably in methodology with critical conceptual and practical implications that have received little attention to date. Substantive methodological issues were also identified relating to the use of derived indices for operationalising sleep discrepancy, defining objective sleep onset latency, calculating actigraphy rest intervals, measuring correlation and concordance, averaging sleep variables across nights, and defining sleep quality discrepancy. Solutions and recommendations for these issues are discussed.

Association between mean platelet volume and obstructive sleep apnea-hypopnea syndrome: A systemic review and meta-analysis

BACKGROUND

Despite polysomnography (PSG) being acknowledged being considered the gold standard for diagnosing obstructive sleep apnea-hypopnea syndrome (OSAHS), researchers have been seeking a biomarker that is less invasive, more practical in detection, and cost-effective for diagnosing and assessing the severity of the disease. To address this concern, the values of mean platelet volume (MPV) between patients with OSAHS and healthy controls were compared, and the relationship between MPV and multiple sleep monitoring parameters was analyzed in this study.

METHODS

A comprehensive search was conducted across medical databases, including PubMed, Web of Science, EMBASE, CNKI, and Wanfang, up until August 2, 2023, to identify published articles related to OSAHS. This study reviewed the literature regarding the values of MPV in individuals with OSAHS and control groups, the Pearson/Spearman correlation coefficients between MPV and sleep monitoring parameters, and the odds ratios (OR) of MPV concerning the occurrence of cardiovascular diseases (CVDs) in patients with OSAHS. Meta-analyses were performed using standardized mean difference (SMD), Fisher's z values correlation coefficients (ZCOR) and odds ratio (OR) as effect variables. A fixed-effect model was used if the heterogeneity was not significant (I2<50%); otherwise, a random-effect model was applied. We will also combine the treatment effect estimates of individual trials using fixed-effect and random-effects models. Statistical analysis was carried out by employing STATA 11.0 and R 4.1.3.

RESULTS

In total, 31 articles were selected for the final analysis. The study involved 3604 patients and 1165 control individuals. The MPV in the OSAHS group was considerably elevated in comparison to the healthy controls (SMD = 0.37, 95%CI = 0.21-0.53, P < 0.001), particularly among individuals with severe OSAHS (SMD = 0.57, 95%CI = 0.23-0.90, P = 0.001). Subgroup analysis based on ethnicity, mean body mass index (BMI), and study design type also revealed a considerably higher MPV in the OSAHS category in comparison to the healthy controls. Furthermore, MPV showed correlations with various sleep monitoring parameters. The elevation of MPV may be one of the risk factors for CVDs in individuals with OSAHS (adjusted OR = 1.72, 95%CI = 1.08-2.73, P = 0.022).

CONCLUSION

MPV is a relatively simple, cost-effective, and practical indicator of the severity of OSAHS, with its values being linked to the risk of CVDs in individuals with OSAHS.

Interleukin-10 is not associated with obstructive sleep apnea hypopnea syndrome: A meta-analysis and meta-regression

BACKGROUND

This study was conducted to explore the potential relationship between interleukin-10 (IL-10) and obstructive sleep apnea hypopnea syndrome (OSAHS).

METHODS

All the related research articles published before October 2022 were retrieved through the online database (EMBASE, VIP, Wan Fang, Web of Science, PubMed, and CNKI). Stata 11.0 software was used to calculate the standard mean difference (SMD) of the continuous variable and 95% confidence interval (CI). Expression profiles GSE38792 and GSE135917 were acquired from Gene Expression Omnibus (GEO) database, respectively. The expression of IL-10 mRNA in subcutaneous adipose tissue and visceral adipose tissue of OSAHS patients and healthy subjects was extracted by R software to verify the difference in IL-10 between the 2 groups.

RESULTS

The IL-10 level in the plasma of people with and without OSAHS (STD Mean Difference (SMD) = -0.68, 95% CI = -1.58 to 0.21, I2 = 94.3%, P = .136) was the same. There was also no difference in IL-10 levels in serum between people with and without OSAHS (SMD = -0.12, 95% CI = -0.55 to 0.32, I2 = 94.4%, P = .591). In addition, the subjects were divided into different subgroups for meta-analysis according to race, body mass index, age, study type, and disease severity. Based on the outcomes, no notable difference was observed in the plasma/serum IL-10 level between the OSAHS subgroups and the control group. The results of bioinformatics analysis indicated that there was no significant difference in the expression of IL-10 mRNA in subcutaneous adipose tissue and visceral adipose tissue between patients with OSAHS and those in the control group.

CONCLUSION

The current meta-analysis highlighted that IL-10 levels between patients with OSAHS and healthy people had no difference.

The REM microarousal and REM duration as the potential indicator in paradoxical insomnia

OBJECTIVE

Although paradoxical insomnia is a prevalent subtype of chronic insomnia, the etiology of it is unclear. Contrary to complaints of little or no sleep, polysomnography (PSG) findings show that paradoxical insomnia patients have near normal sleep macrostructure. The purpose of this study is to determine the changes of microstructure and explore the etiology of paradoxical insomnia.

METHODS

The PSG findings of 89 paradoxical insomnia patients were compared with those of 41 gender balanced healthy controls without sleep complaints. All subjects underwent nocturnal PSG recordings. Conventional PSG measures and microarousals were quantified and statistically analyzed. Receiver operating characteristic curve and correlation analysis were used to evaluate the potential of REM sleep microarousals and REM duration as indicators of paradoxical insomnia.

RESULTS

Compared with the controls, paradoxical insomnia patients had no significant differences in sleep macrostructures. Statistical analysis showed that non-rapid eye movement (NREM) microarousals revealed no significant differences between paradoxical insomnia patients and controls. Noticeably, more spontaneous microarousals appeared in rapid eye movement (REM) stage for paradoxical insomnia patients. Based on receiver operating characteristic curve (ROC), the optimal cutoff value of REM sleep microarousals could predict paradoxical insomnia. Furthermore, a positive correlation between microarousals in REM sleep and the duration of REM sleep was presented in paradoxical insomnia patients.

CONCLUSIONS

The frequency of REM microarousals and the duration of REM sleep could reflect the real sleep state of paradoxical insomnia patients. That suggested PSG investigation extended to microarousal could be helpful to understand the etiology in paradoxical insomnia.

Association between mean platelet volume and obstructive sleep apnea-hypopnea syndrome in children

To evaluate the correlation between mean platelet volume (MPV) and obstructive sleep apnea-hypopnea syndrome (OSAHS) in children, and to explore the diagnostic value of MPV for OSAHS. Children with OSAHS diagnosed by polysomnography (PSG) at Fuyong People's Hospital of Bao'an District/Shenzhen Children's Hospital from January 2020 to January 2021 were enrolled in this study. MPV in peripheral venous blood of the enrolled children was detected. Based on the PSG results (apnea-hypopnea index [AHI] and lowest oxygen saturation [LSaO2]), illness severity was classified, and correlations between the 2 parameters were statistically analyzed. A total of 190 children (males = 135, females = 55) with OSAHS were enrolled in the study. There were no significant correlations between AHI, LSaO2, white blood cell count, red blood cell count, blood platelets, hemoglobin, and packed cell volume (P > .05), but there was a significant positive correlation between AHI and MPV (R > 0, P < .05). There was a significant negative correlation between the LSaO2 index and MPV (R > 0, P < .05). In addition, the receiver operating characteristic (ROC) curve indicated that the best cutoff value for MPV to diagnose mild and moderate-to-severe disease conditions was 9.35 fl, and the coincidence rates for these 2 disease conditions were 93% and 80%, respectively. The ROC curve was also optimal for the diagnosis of mild and moderate-to-severe hypoxia. The critical value was 8.85 fl, and the coincidence rates for these 2 conditions were 96.4% and 76.3%, respectively. In children with OSAHS, MPV is positively correlated with AHI and negatively correlated with the LSaO2 index of PSG. Based on the results of ROC curve analysis, MPV can be used as an auxiliary diagnostic index to judge the severity of OSAHS and the degree of hypoxia in children.

Sleep Misperception and Associated Factors in Patients With Anxiety-Related Disorders and Complaint of Insomnia: A Retrospective Study

Purpose

Data on sleep parameters by polysomnography (PSG) in patients with anxiety-related disorders are limited. Although the disturbance and risk factors of sleep misperception have been implicated in psychopathology, its role in anxiety-related disorders remains unclear. This retrospective study aimed to explore the characteristics and sleep parameters in patients with anxiety-related disorders and different sleep perception types, and to explore the associated factors for sleep misperception.

Methods

Patients with anxiety-related disorders who had complaint of insomnia for more than 3 months were collected at Wuhan Mental Health Center between December 2019 and July 2021. Patients underwent a two-night PSG monitoring and completed a self-reported sleep questionnaire. Behaviors were assessed using 30-item Nurses' Observation Scale for Inpatient Evaluation (NOSIE-30). Patients were divided into normal sleep perception (NSP), positive sleep perception abnormality [PSPA; overestimation of total sleep time (TST) >60 min], and negative sleep perception abnormality (NSPA; underestimation of TST >60 min) groups. PSG indicators and NOSIE-30 scores were compared among groups using the one-way analysis of variance and the Kruskal-Wallis test. Multiple linear regression analysis was performed to determine the associated factors for misperception index.

Results

The subjective and objective TST were 5.5 ± 1.9 h and 6.4 ± 1.7 h in 305 patients, respectively. Sixty-nine (22.6%) had PSPA, 80 (26.2%) had NSP, and 156 (51.1%) had NSPA. Subjective TST and objective sleep parameters were significantly different among groups. No statistical differences in NOSIE-30 subscale and total scores were observed among groups. Sex, rapid eye movement (REM)/TST (%), sleep efficiency, number of awakenings, Non-rapid eye movement of stage 2 sleep (NREM)/TST (%), REM spontaneous arousal times, sleep latency, diagnosis, social competence, and manifest psychosis were associated with sleep misperception.

Conclusion

Sleep misperception is common in patients with anxiety-related disorders. Various sleep perception types have different PSG profiles, but similar personal and social behaviors. These data may be helpful to conduct personalized treatment.

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).