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ObjectivesTo observe the efficacy and side effects of liraglutide in the treatment of type 2 diabetes mellitus (T2DM) patients with severe obstructive sleep apnea (OSA).MethodsThe study conducted in an outpatient setting was a two-center, prospective randomized controlled study. T2DM patients with severe OSA were randomized to the control group (continuous positive airway pressure [CPAP] and drug treatment without liraglutide) or the liraglutide group (CPAP and drug treatment including liraglutide). Demographic and clinical characteristics, sleep-disordered breathing indices, cardiac function indices, and side effects were evaluated and compared between the two groups before and after 3 months.ResultsOf 90 patients, 45 were randomized to the intervention arm (with liraglutide) and 45 to the control arm (without liraglutide). One patient in the liraglutide group dropped out of the study on day 8 after enrollment due to obvious gastrointestinal symptoms. No significant differences were found between the two groups in baseline demographics, clinical characteristics, cardiac function indicators, or sleep disorder respiratory indices (P > 0.05). After 3 months, the body mass index (BMI), apnea hypopnea index (AHI), and mean systolic blood pressure in the liraglutide treatment group were significantly lower than those in the control group (P < 0.05). The minimum oxygen saturation was significantly higher in the liraglutide group compared with that in the control group after 3 months of follow-up (P < 0.05). No difference was found between the two groups in the summary of side effects (P > 0.05).ConclusionsLiraglutide combined with CPAP can effectively reduce BMI, lower mean systolic blood pressure, and improve AHI scores and hypoxia in T2DM patients with severe OSA. Liraglutide did not increase side effects.

BackgroundThe effects of sleep duration on the development of mental illness remain controversial. Therefore, it is necessary to identify the effects of long or short sleep duration on psychological disorders, which could reveal new ways for preventing and treating mental health conditions cheaply.MethodsIdentifying published papers was accomplished by using the following five English databases on March 16, 2022: PubMed, MEDLINE, Embase, Web of Science databases, and Scopus. Cross-sectional and cohort studies were considered if they evaluated the association of sleep duration with all kinds of mental illness in adults. We excluded case reports, editorials, narrative reviews, and studies without detailed information on sleep duration. Summary effect-size estimates were expressed as risk ratios (RRs) or odds ratios (ORs) with 95% confidence intervals and were evaluated using random-effect models. Mantel-Haenszel’s random-effects model was used to estimate the inconsistency index (I2) and Tau2 index (measurement of heterogeneity).ResultsA total of 52 studies were included in this analysis, consisting of 14 cohort studies and 38 cross-sectional studies. These studies involved a combined sample size of 1,407,891 participants who met the inclusion criteria. Cohort (adjusted RR = 1.42, 95% CI: 1.26–1.60, P < .001, I2 = 37.6%, Tau2 = 0.014) and cross-sectional studies (adjusted OR = 1.67, 95% CI: 1.57–1.77, P < .001, I2 = 79.7%, Tau2 = 0.060) concluded that short sleep duration increased mental disorder risks. The same conclusions were acquired in the subgroup analysis, especially for depression (adjusted RR = 1.43, 95% CI: 1.24–1.65, P < .001, I2 = 80.4%, Tau2 = 0.082), anxiety (adjusted RR = 1.30, 95% CI: 1.04–1.63, P = .002, I2 = 0.0%, Tau2 = 0.000), and PTSD (adjusted RR = 1.35, 95% CI: 1.04–1.76, P = .022, I2 = 24.1%, Tau2 = 0.013) in cohort studies. The results of subgroup analysis indicated that long sleep duration was not a risk factor for depression (adjusted RR = 1.15, 95% CI: 0.98–1.34, P = .088, I2 = 63.4%, Tau2 = 0.045) and anxiety (adjusted RR = 1.37, 95% CI: 0.93–2.03, P = .114, I2 = 0.0%, Tau2 = 0.000).ConclusionsShort sleep duration, not long sleep duration, is an independent predictor of developing mental disorders, particularly anxiety and depression.

BackgroundSleep disorders are conditions that have long-term effects on health, quality of sexual function, productivity at work, and overall quality of life. Considering that reports on menopausal sleep disorders are heterogeneous, the aim of this research was to determine the global prevalence of sleep disorders during menopause by meta-analysis.MethodsPubMed, Google Scholar, Scopus, WoS, ScienceDirect, and Embase databases were checked with suitable keywords. All screening stages of articles were reviewed based on PRISMA and their quality was determined based on STROBE. Data analysis, examination of heterogeneity, and publication bias of factors affecting heterogeneity were performed in CMA software.ResultsThe overall prevalence of sleep disorders among postmenopausal women was 51.6% (95% CI: 44.6–58.5%). The upper prevalence of sleep disorders was among postmenopausal women at 54.7% (95% CI: 47.2–62.1%). The upper prevalence of sleep disorders in the same population category was related to restless legs syndrome with a prevalence of 63.8% (95% CI: 10.6–96.3%).ConclusionIn this meta-analysis, sleep disorders during menopause were found to be common and significant. Therefore, it is recommended that health policymakers offer pertinent interventions in relation to the health and hygiene of sleep for women in menopause.

PurposeThe majority of individuals with clinically significant obstructive sleep apnoea (OSA) are undiagnosed and untreated. A simple screening tool may support risk stratification, identification, and appropriate management of at-risk patients. Therefore, this systematic review and meta-analysis evaluated and compared the accuracy and clinical utility of existing screening questionnaires for identifying OSA in different clinical cohorts.MethodsWe conducted a systematic review and meta-analysis of observational studies assessing the diagnostic value of OSA screening questionnaires. We identified prospective studies, validated against polysomnography, and published to December 2020 from online databases. To pool the results, we used random effects bivariate binomial meta-analysis.ResultsWe included 38 studies across three clinical cohorts in the meta-analysis. In the sleep clinic cohort, the Berlin questionnaire’s pooled sensitivity for apnoea-hypopnoea index (AHI) ≥ 5, ≥ 15, and ≥ 30 was 85%, 84%, and 89%, and pooled specificity was 43%, 30%, and 33%, respectively. The STOP questionnaire’s pooled sensitivity for AHI ≥ 5, ≥ 15, and ≥ 30 was 90%, 90%, and 95%, and pooled specificity was 31%, 29%, and 21%. The pooled sensitivity of the STOP-Bang questionnaire for AHI ≥ 5, ≥ 15, and ≥ 30 was 92%, 95%, and 96%, and pooled specificity was 35%, 27%, and 28%. In the surgical cohort (AHI ≥ 15), the Berlin and STOP-Bang questionnaires’ pooled sensitivity were 76% and 90% and pooled specificity 47% and 27%.ConclusionAmong the identified questionnaires, the STOP-Bang questionnaire had the highest sensitivity to detect OSA but lacked specificity. Subgroup analysis considering other at-risk populations was not possible. Our observations are limited by the low certainty level in available data.

BackgroundSeveral studies evaluated the effect of bariatric surgery on obstructive sleep apnea (OSA) but findings have been inconsistent. The aim of this study was to conduct an updated systematic review and meta-analysis to investigate the effect of bariatric surgery on OSA.MethodsThe databases for PubMed, CENTRAL, and Scopus were searched up to the 1st of December, 2021. Studies were included if they were cohort or case–control in design, included patients with diagnosis of OSA, the patients underwent any bariatric surgery, and the study performed postoperative polysomnography.ResultsThe total number of the included patients was 2310 patients with OSA from 32 studies. Our analysis showed that bariatric surgery was associated with significant reduction in BMI (WMD =  − 11.9, 95%CI: − 13.4, − 10.4), apnea–hypopnea index (AHI) (WMD =  − 19.3, 95%CI: − 23.9, − 14.6), and respiratory disturbance index (RDI) (WMD =  − 33.9, 95%CI: − 42.1, − 25.7). The rate of OSA remission after the surgery was 65% (95%CI: 0.54, 0.76).ConclusionOur results suggest that bariatric surgeries are effective in reducing obesity among patients with OSA in addition to OSA severity measures. However, the low rate of OSA remission suggests that the main etiology of OSA is not only obesity but also includes other important variables such as the anatomy of the jaw.

PurposeDue to the lack of an objective population-based screening tool for obstructive sleep apnea (OSA), a large number of patients with potential OSA have not been identified in the general population. Our study compared an objective wearable sleep monitoring device with polysomnography (PSG) to provide a reference for OSA screening in a large population.MethodsUsing a self-control method, patients admitted to our sleep center from July 2020 to March 2021 were selected for overnight PSG and wearable intelligent sleep monitor (WISM) at the same time. The sensitivity and specificity of the device for the diagnosis of OSA were evaluated.ResultsA total of 196 participants (mean age: 45.1 ± 12.3 years [18–80 years]; 168 men [86%]) completed both PSG and WISM monitoring. Using an apnea–hypopnea index (AHI) ≥ 5 events/h as the diagnostic criterion, the sensitivity, specificity, kappa value, and area under the receiver operating characteristic curve of the WISM for OSA diagnosis were 93%, 77%, 0.6, and 0.95, respectively. Using an AHI ≥ 15 events/h as the diagnostic criterion for moderate-to-severe OSA, these values were 92%, 89%, 0.8, and 0.95, respectively. The mean difference in the AHI between PSG and the artificial intelligence oxygen desaturation index from the WISM was 6.8 events/h (95% confidence interval: − 13.1 to 26.7).ConclusionCompared with the PSG, WISM exhibits good sensitivity and specificity for the diagnosis of OSA. This small, simple, and easy-to-use device is more suitable for OSA screening in a large population because of its single-step application procedure.

PurposeOSAS is a syndrome that often presents clinically differently between men and women. The aim of this study was to assess the clinical presentation, nocturnal home sleep cardiorespiratory monitoring and therapeutic adherence to CPAP in both sexes to identify the most frequent patterns.MethodsData from the first visit, the nocturnal home sleep cardiorespiratory monitoring and follow-up visit of 74 OSA patients were collected. Exclusion criteria included other respiratory and/or neuromuscular diseases (including Obesity hypoventilation syndrome) and other non-respiratory sleep disorders.ResultsMen were older and had a higher supine AHI and ODI compared to women. In addition, BMI and age correlated positively with AHI in males. Women had a higher hypopneas frequency and better therapeutic adherence to CPAP.ConclusionsMen were associated with a higher AHI when sleeping in the supine position and this may be useful to look for new therapeutic options in combination with or as an alternative to CPAP. BMI correlated positively with AHI in men and this should be considered to stimulate weight loss as the main treatment to reduce the number of apneas/hypopneas, as men also had less therapeutic adherence to CPAP in our study. Females presented a significantly higher frequency of hypopneas than men, as well as a lower number of desaturation events per hour (ODI): these differences in the nocturnal home sleep cardiorespiratory monitoring could reflect different pathophysiological mechanisms of OSAS onset between the two sexes, which should be investigated in future scientific studies.

PurposePreliminary studies have shown a significant decrease in severity of obstructive sleep apnea (OSA) with the use of a combination of atomoxetine and oxybutynin, with patients having moderate pharyngeal collapsibility during sleep more likely to respond. This study evaluated the efficacy and safety of AD036 (atomoxetine 80 mg and oxybutynin 5 mg) in the treatment of OSA.MethodsThis trial was a phase 2, randomized, placebo-controlled crossover study comparing AD036, atomoxetine 80 mg alone, and placebo during three home sleep studies, each separated by about 1 week. The trial included patients with OSA and moderate pharyngeal collapsibility as defined by a higher proportion of hypopneas to apneas and mild oxygen desaturation.ResultsOf 62 patients who were randomized, 60 were included in efficacy analyses. The apnea–hypopnea index (AHI) from a median (interquartile range) of 14.2 (5.4 to 22.3) events/h on placebo to 6.2 (2.8 to 13.6) with AD036 and 4.8 (1.4 to 11.6) with atomoxetine alone (p < .0001). Both drugs also decreased the oxygen desaturation index (ODI) and the hypoxic burden (p < .0001). AD036, but not atomoxetine alone, reduced the respiratory arousal index and improved ventilation at the respiratory arousal threshold (greater Vactive). There was a trend for total sleep time to be decreased more with atomoxetine alone than with AD036. The most common adverse event was insomnia (12% with AD036, 18% with atomoxetine).ConclusionAD036 significantly improved OSA severity in patients with moderate pharyngeal collapsibility. Atomoxetine may account for the majority of improvement in OSA severity, while the addition of oxybutynin may mitigate the disruptive effect of atomoxetine on sleep and further improve ventilation.Trial registrationClinical trial registered with www.clinicaltrials.gov (NCT04445688).

IntroductionObstructive sleep apnea syndrome (OSAS) and asthma are two diseases with a high epidemiological impact that may often coexist. Both diseases have underlying pathogenic mechanisms (chronic inflammation, genetic predisposition, etc.); it is still unclear whether or not their coexistence is due to a specific pathophysiological factor. In the literature, the pathogenesis of OSAS has four pathophysiological traits: one or more anatomical predisposing factors, a low arousal threshold (low AT), high loop gain, and poor muscle responsiveness. In this study, we hypothesized that a low AT is a common pathophysiological factor in OSAS and asthma.MethodsA retrospective study of patients attending the Pulmonology Unit of the University Hospital of Trieste was carried out. Low AT was predicted on the bases of the following polysomnography features, as previously shown by Edwards et al.: an AHI of < 30 events/h, a nadir SpO2 of > 82.5%, and a hypopnea fraction of total respiratory events of > 58.3%.ResultsThirty-five patients with asthma and OSAS and 36 with OSAS alone were included in the study. Low AT was present in 71% of patients affected by asthma and OSAS (25 patients out of 35) versus 31% (11 patients out of 36) of patients affected by OSAS alone with a statistically significant difference (p = 0.002) between the two groups. Stratifying for BMI and OSAS severity, the difference between groups remained statistically significant.ConclusionsThis is the first study to describe specific polysomnographic characteristics of patients affected by asthma and OSAS. A low AT may well be the pathophysiological factor common to the two diseases. If confirmed by other studies, this finding could lead to the presence of asthma and OSAS in the same individual being considered a syndrome with a common pathophysiological factor.

PurposeTo develop an automated framework for sleep stage scoring from PSG via a deep neural network.MethodsAn automated deep neural network was proposed by using a multi-model integration strategy with multiple signal channels as input. All of the data were collected from one single medical center from July 2017 to April 2019. Model performance was evaluated by overall classification accuracy, precision, recall, weighted F1 score, and Cohen’s Kappa.ResultsTwo hundred ninety-four sleep studies were included in this study; 122 composed the training dataset, 20 composed the validation dataset, and 152 were used in the testing dataset. The network achieved human-level annotation performance with an average accuracy of 0.8181, weighted F1 score of 0.8150, and Cohen’s Kappa of 0.7276. Top-2 accuracy (the proportion of test samples for which the true label is among the two most probable labels given by the model) was significantly improved compared to the overall classification accuracy, with the average being 0.9602. The number of arousals affected the model’s performance.ConclusionThis research provides a robust and reliable model with the inter-rater agreement nearing that of human experts. Determining the most appropriate evaluation parameters for sleep staging is a direction for future research.