REM and NREM Sleep Parasomnia in Anti-NMDA Receptor Encephalitis.

OBJECTIVES: Encephalitis with anti-N-methyl-d-aspartate receptor antibodies (anti-NMDARe) is a rare disorder characterized by cognitive impairment, psychosis, seizures, and abnormal movements. Abnormal behaviors during REM sleep have not been described in anti-NMDARe. METHODS: Patients were monitored by video-polysomnography on a first night followed by multiple sleep latency tests and 18 hours of bed rest. RESULTS: Two patients with anti-NMDARe developed during the acute and postacute phase parasomnias including REM sleep behavior disorder and continuous finalistic quiet gesturing during a mixed N2/R sleep. The parasomnia disorder was improved by gabapentin and clonazepam. DISCUSSION: Video-polysomnography avoids misdiagnosing these parasomnia behaviors for seizure or movement disorders and allows adequate treatment.

Paediatric sleep diagnostics in the 21st century: the era of "sleep-omics"?

Paediatric sleep diagnostics is performed using complex multichannel tests in specialised centres, limiting access and availability and resulting in delayed diagnosis and management. Such investigations are often challenging due to patient size (prematurity), tolerability, and compliance with "gold standard" equipment. Children with sensory/behavioural issues, at increased risk of sleep disordered breathing (SDB), often find standard diagnostic equipment difficult.SDB can have implications for a child both in terms of physical health and neurocognitive development. Potential sequelae of untreated SDB includes failure to thrive, cardiopulmonary disease, impaired learning and behavioural issues. Prompt and accurate diagnosis of SDB is important to facilitate early intervention and improve outcomes.The current gold-standard diagnostic test for SDB is polysomnography (PSG), which is expensive, requiring the interpretation of a highly specialised physiologist. PSG is not feasible in low-income countries or outwith specialist sleep centres. During the coronavirus disease 2019 pandemic, efforts were made to improve remote monitoring and diagnostics in paediatric sleep medicine, resulting in a paradigm shift in SDB technology with a focus on automated diagnosis harnessing artificial intelligence (AI). AI enables interrogation of large datasets, setting the scene for an era of "sleep-omics", characterising the endotypic and phenotypic bedrock of SDB by drawing on genetic, lifestyle and demographic information. The National Institute for Health and Care Excellence recently announced a programme for the development of automated home-testing devices for SDB. Scorer-independent scalable diagnostic approaches for paediatric SDB have potential to improve diagnostic accuracy, accessibility and patient tolerability; reduce health inequalities; and yield downstream economic and environmental benefits.

Cognitive training and promoting a healthy lifestyle for individuals with isolated REM sleep behavior disorder: study protocol of the delayed-start randomized controlled trial CogTrAiL-RBD.

BACKGROUND: Isolated REM sleep behavior disorder (iRBD) is an early α-synucleinopathy often accompanied by incipient cognitive impairment. As executive dysfunctions predict earlier phenotypic conversion from iRBD to Parkinson's disease and Lewy body dementia, cognitive training focusing on executive functions could have disease-modifying effects for individuals with iRBD. METHODS: The study CogTrAiL-RBD investigates the short- and long-term effectiveness and the feasibility and underlying neural mechanisms of a cognitive training intervention for individuals with iRBD. The intervention consists of a 5-week digital cognitive training accompanied by a module promoting a healthy, active lifestyle. In this monocentric, single-blinded, delayed-start randomized controlled trial, the intervention's effectiveness will be evaluated compared to an initially passive control group that receives the intervention in the second, open-label phase of the study. Eighty individuals with iRBD confirmed by polysomnography will be consecutively recruited from the continuously expanding iRBD cohort at the University Hospital Cologne. The evaluation will focus on cognition and additional neuropsychological and motor variables. Furthermore, the study will examine the feasibility of the intervention, effects on physical activity assessed by accelerometry, and interrogate the intervention's neural effects using magnetic resonance imaging and polysomnography. Besides, a healthy, age-matched control group (HC) will be examined at the first assessment time point, enabling a cross-sectional comparison between individuals with iRBD and HC. DISCUSSION: This study will provide insights into whether cognitive training and psychoeducation on a healthy, active lifestyle have short- and long-term (neuro-)protective effects for individuals with iRBD. TRIAL REGISTRATION: The study was prospectively registered in the German Clinical Trial Register (DRKS00024898) on 2022-03-11, https://drks.de/search/de/trial/DRKS00024898 . PROTOCOL VERSION: V5 2023-04-24.

Change-point detection using diffusion maps for sleep apnea monitoring with contact-free sensors.

Monitoring and improving the quality of sleep are crucial from a public health perspective. In this study, we propose a change-point detection method using diffusion maps for a more accurate detection of respiratory arrest points. Conventional change-point detection methods are limited when dealing with complex nonlinear data structures, and the proposed method overcomes these limitations. The proposed method embeds subsequence data in a low-dimensional space while considering the global and local structures of the data and uses the distance between the data as the score of the change point. Experiments using synthetic and real-world contact-free sensor data confirmed the superiority of the proposed method when dealing with noise, and it detected apnea events with greater accuracy than conventional methods. In addition to improving sleep monitoring, the proposed method can be applied in other fields, such as healthcare, manufacturing, and finance. This study will contribute to the development of advanced monitoring systems that adapt to diverse conditions while protecting privacy.

Using standardized ultrasound imaging to correlate OSA severity with tongue morphology.

BACKGROUND: Ultrasound imaging has been explored as a potential diagnostic tool for obstructive sleep apnea (OSA); we reported backscatter ultrasound imaging (BUI) of the tongue correlates with OSA severity in adults. We focus on anatomical features of the tongue using standardized ultrasonography and hypothesize that differences in morphology correlate with OSA severity. METHODS: This prospective study was IRB approved (53,172) and conducted at Stanford University Sleep Surgery Clinic. Patients ≥18 years with polysomnography (PSG) underwent a standardized submental ultrasound scan using a laser alignment tool to observe the upper airway in supine position during tidal respiration. Images acquired from this scan were divided into 4 equiangular regions (A-D). RESULTS: A total of 144 patients (30 women) July 2020-December 2022 were included with mean age 41.6 years (±12.9 SD), BMI 27.2 kg/m2(±4.7 SD), and AHI 19.7 (±20.0 SD). Moderate-to-severe OSA patients had significantly narrower airspace at regions A, B and C with p-values ranging from <0.0001 to 0.0003. These patients had a significantly wider (p = 0.0021-0.0045 for regions A, B and C) tongue and thicker (p = 0.0403 for region B) deep tissue. The predictive model to assess the risk of moderate-to-severe OSA achieved an area under the receiver operating characteristic curve of 0.839 (95 % CI: 0.769 to 0.895). CONCLUSIONS: With standardized, computerized ultrasound imaging of the shape and configuration of the tongue, we identified regions that correlated well with OSA severity. Further research is needed to determine the clinical implications of such pathophysiological findings.

Validity, reliability, and responsiveness of the Brazilian version of the instrument World Health Organization Disability Assessment Schedule (WHODAS 2.0) for individuals with obstructive sleep apnoea.

BACKGROUND: Obstructive sleep apnoea (OSA) is a disabling health condition, and there is no disease-specific patient-reported outcome instrument to assess individuals with OSA. OBJECTIVES: To evaluate the psychometric properties of the Brazilian version of the World Health Organization Disability Assessment Schedule (WHODAS 2.0) in individuals with OSA. METHODS: One hundred individuals with OSA responded to the WHODAS 2.0 version of 36 items, the Epworth Sleepiness Scale (ESS), the Pittsburgh Sleep Quality Index (PSQI), and the 12-item health survey (SF-12). Internal consistency, convergent and discriminative validity, and responsiveness to continuous positive airway pressure (CPAP) were the psychometric properties tested. RESULTS: Cronbach's α values indicate good internal consistency (0.91 - 0.73), except for the self-care domain (α = 0.52). Convergent validity indicated an excellent correlation (r = -0.80) between the domains of functioning and quality of life. Discriminative validity showed no association between OSA severity and functioning (p = 0.90). The responsiveness to CPAP treatment showed a large effect size (r = 0.82; p < 0.05) CONCLUSIONS: The WHODAS 2.0 instrument is valid, reliable, and responsive for assessing individuals with OSA.

Diagnosis of obstructive sleep apnoea in primary care.

BACKGROUND: Obstructive sleep apnoea (OSA) is a highly prevalent condition associated with significant adverse health consequences affecting multiple organ systems. As the first point of contact for most patients with OSA, general practitioners (GPs) have an important role in the diagnosis of this common sleep disorder. OBJECTIVE: The aim of this paper is to improve awareness of common risk factors for and clinical presentation of OSA in primary care to improve patient health outcomes. We seek to understand how screening tools, such as the OSA50 questionnaire and the Epworth Sleepiness Scale, can help GPs identify patients who are at high risk for OSA with significant daytime sleepiness. DISCUSSION: Patients at high risk of symptomatic moderate-severe OSA should proceed to further investigation with sleep study testing. Referral to a sleep physician should be considered for patients with complex presentations or other suspected sleep disorders, commercial drivers, and those who fail to comply with or respond to initial OSA treatments.

[Analysis of the Current Application Status for Clinical and Home Monitoring of Obstructive Sleep Apnea-Hypopnea Syndrome].

The study provides an overview of the development status of sleep disorder monitoring devices. Currently, polysomnography (PSG) is the gold standard for diagnosing sleep disorders, necessitating multiple leads and requiring overnight monitoring in a sleep laboratory, which can be cumbersome for patients. Nevertheless, the performance of PSG has been enhanced through research on sleep disorder monitoring and sleep staging optimization. An alternative device is the home sleep apnea testing (HSAT), which enables patients to monitor their sleep at home. However, HSAT does not attain the same level of accuracy in sleep staging as PSG, rendering it inappropriate for screening individuals with asymptomatic or mild obstructive sleep apnea-hypopnea syndrome (OSAHS). The study suggests that establishing a Chinese sleep staging database and developing home sleep disorder monitoring devices that can serve as alternatives to PSG will represent a future development direction.

[Study on the application value of portable pulse oximeter in adult patients with obstructive sleep apnea].

Objective: To evaluate the application value of portable pulse oximeter in adult obstructive sleep apnea (OSA). Methods: This study prospectively enrolled adult patients who underwent polysomnography (PSG) due to snoring at the Respiratory and Sleep Medicine Department of Peking University People's Hospital from July 2022 to July 2023. During PSG monitoring, CS-WOxi was continuously used to monitor blood oxygen levels. The consistency between 3% oxygen desaturation index (ODI3) measured by portable pulse oximeter and ODI3 of polysomnography was evaluated using difference test, Pearson's correlation coefficient, and Bland-altman method. Receiver operating characteristic curve was used to determine the optimal threshold for diagnosing OSA. Results: A total of 184 subjects were included, including 121 males (65.8%) and 63 females (34.2%). The mean age was 46.0 (34.3, 59.0) years, body mass index was 26.0 (23.3, 29.6) kg/m², and the apnea-hypopnea index was 18.2 (5.8, 40.8) events/h. There was a significant difference between CS-ODI3 and PSG-ODI3 [17.1(6.2, 42.7) vs. 14.0(2.9, 32.6), P<0.001], and the Pearson correlation coefficient was 0.93 (P<0.001). There was a good correlation between CS-ODI3 and PSG-AHI (r=0.92, P<0.001). Bland-Altman consistency test showed that the average difference between the two was 0.7 events/h, and the 95% consistency limit was (-17.9, 19.3 events/h). When the CS-ODI3≥5 events/h was used to identify OSA, the sensitivity was 94.4%, the specificity was 80.0%, and the accuracy was 91.3%. When PSG-AHI≥5 events/h was used as the diagnostic criteria, the area under the receiver operating characteristic curve was 0.933. Conclusion: Portable pulse oximeter can monitor pulse oxygen saturation accurately and has good sensitivity and specificity for OSA high-risk patients, and is a reliable tool for OSA screening.

[Advances in the detection of arousal in obstructive sleep apnea].

Obstructive sleep apnea (OSA) is primarily characterized by intermittent nocturnal hypoxia and sleep fragmentation. Arousals interrupt sleep continuity and lead to sleep fragmentation, which can lead to cognitive dysfunction, excessive daytime sleepiness, and adverse cardiovascular outcome events, making arousals important for diagnosing OSA and reducing the risk of complications, including heart disease and cognitive impairment. Traditional arousal interpretation requires sleep specialists to manually score PSG recordings throughout the night, which is time consuming and has low inter-specialist agreement, so the search for simple, efficient, and reliable arousal detection methods can be a powerful tool to clinicians. In this paper, we systematically reviewed different methods for recognizing arousal in OSA patients, including autonomic markers (pulse conduction time, pulse wave amplitude, peripheral arterial tone, heart rate, etc.) and machine learning-based automated arousal detection systems, and found that autonomic markers may be more beneficial in certain subgroups, and that deep artificial networks will remain the main research method for automated arousal detection in the future.

Multi-Modal Sleep Stage Classification With Two-Stream Encoder-Decoder.

Sleep staging serves as a fundamental assessment for sleep quality measurement and sleep disorder diagnosis. Although current deep learning approaches have successfully integrated multimodal sleep signals, enhancing the accuracy of automatic sleep staging, certain challenges remain, as follows: 1) optimizing the utilization of multi-modal information complementarity, 2) effectively extracting both long- and short-range temporal features of sleep information, and 3) addressing the class imbalance problem in sleep data. To address these challenges, this paper proposes a two-stream encode-decoder network, named TSEDSleepNet, which is inspired by the depth sensitive attention and automatic multi-modal fusion (DSA2F) framework. In TSEDSleepNet, a two-stream encoder is used to extract the multiscale features of electrooculogram (EOG) and electroencephalogram (EEG) signals. And a self-attention mechanism is utilized to fuse the multiscale features, generating multi-modal saliency features. Subsequently, the coarser-scale construction module (CSCM) is adopted to extract and construct multi-resolution features from the multiscale features and the salient features. Thereafter, a Transformer module is applied to capture both long- and short-range temporal features from the multi-resolution features. Finally, the long- and short-range temporal features are restored with low-layer details and mapped to the predicted classification results. Additionally, the Lovász loss function is applied to alleviate the class imbalance problem in sleep datasets. Our proposed method was tested on the Sleep-EDF-39 and Sleep-EDF-153 datasets, and it achieved classification accuracies of 88.9% and 85.2% and Macro-F1 scores of 84.8% and 79.7%, respectively, thus outperforming conventional traditional baseline models. These results highlight the efficacy of the proposed method in fusing multi-modal information. This method has potential for application as an adjunct tool for diagnosing sleep disorders.

Rapid eye movement dependency is associated with increased inflammatory activity in obstructive sleep apnea syndrome.

OBJECTIVE: Rapid eye movement (REM)-dependent obstructive sleep apnea syndrome (OSAS) is a specific subtype of OSAS having some phenotypic characteristics like a preference for a younger age, female gender, and milder severity. Such favorable features could make it possible to consider an overall benign course for this phenotype. However, accumulating data introduced its association with several cardiometabolic and vascular disorders recently. The primary objective of this study was to address the disease from the inflammation perspective and evaluate the potential inflammatory status in this variant via two accessible blood parameters: platelet distribution width (PDW) and systemic immune-inflammation index (SII). The secondary aim was to investigate whether this status, together with other disease characteristics, demonstrates consistency under different definitions of REM-dependent OSAS published previously. PATIENTS AND METHODS: The medical records of 35 patients with mild-to-moderate REM-dependent OSAS, 35 age- and sex-matched patients with REM-independent OSAS, and 25 non-OSA controls were retrospectively analyzed. Baseline features, polysomnographic characteristics, PDW, and SII were compared between the groups. Secondly, the analyses were repeated using different definitions of REM-dependent OSAS. Bivariate analyses were performed, and a multiple stepwise regression model was applied to adjust for body mass index (BMI) and cardiovascular risk (CVR) factors.  RESULTS: Mean PDW and SII were increased in patients with REM-dependent OSAS as compared to non-OSA controls (p = .022 and .029). The significance remained stable after adjustment for BMI and CVRs and was consistent according to different definitions. The Comparison of patients with REM-independent OSAS and non-OSA controls, as well as the two different subtypes of OSAS, did not yield significance. CONCLUSION: Based on the current findings, patients with REM-dependent OSAS appear to be susceptible to inflammation and should be carefully monitored for the negative consequences of that issue. To our knowledge, this study is the first to evaluate SII and PDW in REM-dependent OSAS.

Functional changes in sleep-related arousal after ketamine administration in individuals with treatment-resistant depression.

The glutamatergic modulator ketamine is associated with changes in sleep, depression, and suicidal ideation (SI). This study sought to evaluate differences in arousal-related sleep metrics between 36 individuals with treatment-resistant major depression (TRD) and 25 healthy volunteers (HVs). It also sought to determine whether ketamine normalizes arousal in individuals with TRD and whether ketamine's effects on arousal mediate its antidepressant and anti-SI effects. This was a secondary analysis of a biomarker-focused, randomized, double-blind, crossover trial of ketamine (0.5 mg/kg) compared to saline placebo. Polysomnography (PSG) studies were conducted one day before and one day after ketamine/placebo infusions. Sleep arousal was measured using spectral power functions over time including alpha (quiet wakefulness), beta (alert wakefulness), and delta (deep sleep) power, as well as macroarchitecture variables, including wakefulness after sleep onset (WASO), total sleep time (TST), rapid eye movement (REM) latency, and Post-Sleep Onset Sleep Efficiency (PSOSE). At baseline, diagnostic differences in sleep macroarchitecture included lower TST (p = 0.006) and shorter REM latency (p = 0.04) in the TRD versus HV group. Ketamine's temporal dynamic effects (relative to placebo) in TRD included increased delta power earlier in the night and increased alpha and delta power later in the night. However, there were no significant diagnostic differences in temporal patterns of alpha, beta, or delta power, no ketamine effects on sleep macroarchitecture arousal metrics, and no mediation effects of sleep variables on ketamine's antidepressant or anti-SI effects. These results highlight the role of sleep-related variables as part of the systemic neurobiological changes initiated after ketamine administration. Clinical Trials Identifier: NCT00088699.

Machine learning methods for adult OSAHS risk prediction.

BACKGROUND: Obstructive sleep apnea hypopnea syndrome (OSAHS) is a common disease that can cause multiple organ damage in the whole body. Our aim was to use machine learning (ML) to build an independent polysomnography (PSG) model to analyze risk factors and predict OSAHS. MATERIALS AND METHODS: Clinical data of 2064 snoring patients who underwent physical examination in the Health Management Center of the First Affiliated Hospital of Shanxi Medical University from July 2018 to July 2023 were retrospectively collected, involving 24 characteristic variables. Then they were randomly divided into training group and verification group according to the ratio of 7:3. By analyzing the importance of these features, it was concluded that LDL-C, Cr, common carotid artery plaque, A1c and BMI made major contributions to OSAHS. Moreover, five kinds of machine learning algorithm models such as logistic regression, support vector machine, Boosting, Random Forest and MLP were further established, and cross validation was used to adjust the model hyperparameters to determine the final prediction model. We compared the accuracy, Precision, Recall rate, F1-score and AUC indexes of the model, and finally obtained that MLP was the optimal model with an accuracy of 85.80%, Precision of 0.89, Recall of 0.75, F1-score of 0.82, and AUC of 0.938. CONCLUSION: We established the risk prediction model of OSAHS using ML method, and proved that the MLP model performed best among the five ML models. This predictive model helps to identify patients with OSAHS and provide early, personalized diagnosis and treatment options.

Treating sleep-disordered breathing of idiopathic pulmonary fibrosis patients with CPAP and nocturnal oxygen treatment. A pilot study : Sleep-disordered breathing treatment in IPF.

INTRODUCTION: Sleep-disordered breathing (SDB) is a major comorbidity in idiopathic pulmonary fibrosis (IPF) and is associated with a poor outcome. There is a lack of knowledge regarding the impact of SDB treatment on IPF. We assessed at one year: (1) the effect of CPAP and/or nocturnal oxygen therapy on IPF regarding lung function, blood mediators, and quality of life; (2) adherence to SDB treatment and SDB changes. METHODOLOGY: This is a prospective study of consecutive newly diagnosed IPF patients initiating anti-fibrotic treatment. Lung function, polysomnography, blood tests and quality of life questionnaires were performed at inclusion and after one year. Patients were classified as obstructive sleep apnoea (OSA), central sleep apnoea (CSA), and sleep-sustained hypoxemia (SSH). SDB therapy (CPAP and/or nocturnal oxygen therapy) was initiated if needed. RESULTS: Fifty patients were enrolled (36% had OSA, 22% CSA, and 12% SSH). CPAP was started in 54% of patients and nocturnal oxygen therapy in 16%. At one-year, polysomnography found improved parameters, though 17% of patients had to add nocturnal oxygen therapy or CPAP, while 33% presented SDB onset at this second polysomnography. CPAP compliance at one year was 6.74 h/night (SD 0.74). After one year, matrix metalloproteinase-1 decreased in OSA and CSA (p = 0.029; p = 0.027), C-reactive protein in OSA (p = 0.045), and surfactant protein D in CSA group (p = 0.074). There was no significant change in lung function. CONCLUSIONS: Treatment of SBD with CPAP and NOT can be well tolerated with a high compliance. IPF patients may exhibit SDB progression and require periodic re-assessment. Further studies to evaluate the impact of SDB treatment on lung function and serological mediators are needed.

Interdisciplinary Role of Orthodontist in Screening and Managing Obstructive Sleep Apnea in Children and Adults.

Obstructive sleep apnea (OSA) can affect children and adults, and, if left untreated, could have a major impact on the general and overall well-being of the patient. Dental health care providers and orthodontists have an interdisciplinary role in screening patients at risk for OSA and make a referral to establish a definitive diagnosis by a sleep physician. The gold standard of diagnostic testing is polysomnography. The adeno-tonsillar hypertrophy is the primary cause of sleep apnea in children; therefore, adeno-tonsillectomy must be the first line of treatment. Post adeno-tonsillectomy, if there is residual OSA due to underlying skeletal discrepancy, the patient may be referred to an orthodontist for appropriate management. Currently the evidence in the literature for prophylactic growth modification in children to prevent OSA is weak. In adults, the gold standard for managing OSA is Positive Airway Pressure (PAP) therapy; however, adherence to this treatment is rather low. The oral appliance (OA) therapy is an alternate for PAP intolerant patients and for mild to moderate OSA patients. The OA therapy has to be administered by a qualified dentist or orthodontist after careful examination of dental and periodontal health as well as any pre-existing joint conditions. The OA therapy could cause OA-associated malocclusion and patients have to be made aware of prior to initiating treatment. In patients with severe OSA, surgical maxilla-mandibular advancement (MMA) is highly effective.

Association between sleep state misperception and bedtime behavior in patients with chronic insomnia.

Previous studies on sleep state misperception have objectively evaluated sleep status in special environments using polysomnography. There is a paucity of data from studies that evaluated habitual sleep status in home environments. The present study aimed to investigate sleep state misperception in the home environment of patients with chronic insomnia using a lumbar-worn actigraphy to identify sleep habits associated with sleep state misperception severity. Thirty-one patients and 42 healthy volunteers were included in the insomnia and non-insomnia group, respectively. Participants recorded subjective assessments in sleep diaries, objective assessments with an actigraphy worn for 14 days, and self-assessments using questionnaires. Both groups had similar objective sleep ratings; however, insomnia group had significantly worse subjective ratings (total sleep time, wake after sleep onset, and sleep onset latency). A significant correlation was found between subjective and objective total sleep time scores in non-insomnia group but not in insomnia group. Insomnia group had earlier bedtimes, significantly longer bedtimes, and impaired daytime functioning (Sheehan Disability Scale score); additionally, they underestimated their total sleep time, particularly with earlier bedtimes and longer laying durations. Monitoring the sleep status and habits of individuals in home environments could be instrumental in identifying key points for targeted interventions on sleep hygiene and cognitive behavioral therapy for insomnia.

Exploring the interplay of depression, sleep quality, and hearing in tinnitus-related handicap: insights from polysomnography and pure-tone audiometry.

BACKGROUND: Tinnitus affects approximately 740 million adults globally, involving hearing, emotion, and sleep systems. However, studies using polysomnography and pure-tone audiometry (PTA) are limited. We aimed to assess the correlation between tinnitus and hearing, sleep quality, characteristics, and depression using polysomnography and PTA. METHODS: In this cross-sectional study, we divided participants into tinnitus and non-tinnitus groups. We included 100 outpatients (65 with tinnitus, 35 without) from a medical center in Taiwan, who underwent polysomnography and completed rating scales including the Patient Health Questionnaire-9 (PHQ-9), Chinese version of the Pittsburgh Sleep Quality Index (PSQI), and Chinese-Mandarin version of the Tinnitus Handicap Inventory (THI-CM). We analyzed correlations, conducted group comparisons, assessed factors related to THI-CM scores, constructed ROC curves to predict depression in the tinnitus group, and performed multinomial and logistic regression to explore associations. RESULTS: Descriptive statistics identified a cohort with mean age 53.9 ± 12.80 years, 63% exhibited PHQ-9 scores ≥ 10, and 66% had Apnea-Hypopnea Index (AHI) > 5. The ratio of rapid eye movement and deep sleep to stage 1 + 2 sleep was relatively low and non-significant. Likewise, leg movements was higher in the tinnitus group but not statistically significant. In the tinnitus group, 63.08% had depression, and 81.54% had AHI > 5. Univariate logistic regression linked tinnitus to AHI > 5 (Odds ratio (OR) 2.67, p = 0.026) and male sex (OR 2.49, p = 0.034). A moderate positive correlation was found between the THI-CM score and PHQ-9 score (rs = 0.50, p < 0.001). Further adjustment for obstructive sleep apnea showed associations between PHQ-9 (total score) or depression and THI-CM Grade 3-5 (OR = 1.28; OR = 8.68). Single- and multifactor regression analyses highlighted significant associations of PSQI scores > 13 (OR 7.06, p = 0.018) and THI-CM scores > 47 (OR 7.43, p = 0.002) with depression. CONCLUSIONS: Our study recruited tinnitus participants with slight or mild hearing loss and mild tinnitus handicap. Depression was identified as a predominant factor in tinnitus-related handicap. The mild tinnitus handicap in tinnitus participants may explain the lack of significant differences in depression, sleep quality, and polysomnographic sleep characteristics between tinnitus and non-tinnitus groups. Further extensive and prospective studies are needed to elucidate the complex links among depression, sleep, and tinnitus.

Recognition of apnea and hypopnea by non-contact optical fiber mattress and its application in the diagnosis of obstructive sleep apnea hypopnea syndrome: a retrospective study.

Objectives: This study sought to evaluate the diagnostic value of a non-contact optical fiber mattress for apnea and hypopnea and compare it with traditional polysomnography (PSG) in adult obstructive sleep apnea hypopnea syndrome (OSAHS). Methods: To determine the value of a non-contact optical fiber mattress for apnea and hypopnea, six healthy people and six OSAHS patients were selected from Tongji Hospital to design a program to identify apnea or hypopnea. A total of 108 patients who received polysomnography for drowsiness, snoring or other suspected OSAHS symptoms. All 108 patients were monitored with both the non-contact optical fiber mattress and PSG were collected. Results: Six healthy controls and six patients with OSAHS were included. The mean apnea of the six healthy controls was 1.22 times/h, and the mean hypopnea of the six healthy controls was 2 times/h. Of the six patients with OSAHS, the mean apnea was 12.63 times/h, and the mean hypopnea was 19.25 times/h. The non-contact optical fiber mattress results showed that the mean apnea of the control group was 3.17 times/h and the mean hypopnea of the control group was 3.83 times/h, while the mean apnea of the OSAHS group was 11.95 times/h and the mean hypopnea of the OSAHS group was 17.77 times/h. The apnea index of the non-contact optical fiber mattress was positively correlated with the apnea index of the PSG (P < 0.05, r = 0.835), and the hypopnea index of the non-contact optical fiber mattress was also positively correlated with the hypopnea index of the PSG (P < 0.05, r = 0.959). The non-contact optical fiber mattress had high accuracy (area under curve, AUC = 0.889), specificity (83.4%) and sensitivity (83.3%) for the diagnosis of apnea. The non-contact fiber-optic mattress also had high accuracy (AUC = 0.944), specificity (83.4%) and sensitivity (100%) for the diagnosis of hypopnea. Among the 108 patients enrolled, there was no significant difference between the non-contact optical fiber mattress and the polysomnography monitor in total recording time, apnea hypopnea index (AHI), average heart rate, tachycardia index, bradycardia index, longest time of apnea, average time of apnea, longest time of hypopnea, average time of hypopnea, percentage of total apnea time in total sleep time and percentage of total hypopnea time in total sleep time. The AHI value of the non-contact optical fiber mattress was positively correlated with the AHI value of the PSG (P < 0.05, r = 0.713). The specificity and sensitivity of the non-contact optical fiber mattress AHI in the diagnosis of OSAHS were 95% and 93%, with a high OSAHS diagnostic accuracy (AUC = 0.984). Conclusion: The efficacy of the non-contact optical fiber mattress for OSAHS monitoring was not significantly different than PSG monitoring. The specificity of the non-contact optical mattress for diagnosing OSAHS was 95% and its sensitivity was 93%, with a high OSAHS diagnostic accuracy.