Polysomnographic Parameters Research Articles

Low-Grade Inflammation Associated with Major Depression Subtypes: A Cross-Sectional Study.

Major depressive disorder (MDD) is associated with inflammation and a high level of comorbidities. Atypical depression (AD) is a MDD subtype based on DSM criteria, that could have specific underlying biological mechanisms. AD is associated with elevated cardiovascular (CVD) comorbidities, higher risk of suicide attempts, hypersomnia, and anxiety disorder. In this study, we aim to investigate if AD and polysomnographic parameters could be associated with low-grade inflammation (LGI). LGI is defined by a range from 3 to 10 mg/L of C-reactive protein levels. We carried out a retrospective cohort study in which 765 individuals with MDD were split into two groups: with and without LGI. Our results exhibit differences between the groups for the polysomnographic parameters, with the LGI group showing parameters already associated with inflammation such as reduced rapid eye movement sleep and elevated hypoxemia markers (identified as CVD risk factor). We found that AD is associated with LGI (OR 1.48; p = 0.047) after adjustment. Likewise, we found an LGI prevalence in AD higher (34.8%) than in MDD without atypical features (26.8%). Overall, these results confirm the low-grade inflammation feature of AD and highlight polysomnographic parameters associated with LGI that could also act as risk factors in this context.

Phenotyping patients treated for obstructive sleep apnea with persistent objective impaired alertness or subjective sleepiness

Background and objectivesSleepiness in patients with obstructive sleep apnea (OSA) is associated with accidental and economic burden, as well as cardiovascular risk. Despite OSA treatment, 10–28 % of patients report residual sleepiness. Its determinants, as well as those of objective impaired alertness remain poorly known. In this study, we investigated factors associated with residual subjective sleepiness and objective impaired alertness in patients treated for OSA. MethodsConsecutive OSA treated patients referred for maintenance of wakefulness tests (MWT) at a tertiary university center were recruited between 2017 and 2020. Clinical data and polysomnography parameters were compared between patients with vs without subjective sleepiness (Epworth Sleepiness Scale, ESS≥11) and those with vs without impaired alertness (at least one trial with sleep onset on MWT). A multivariate logistic model was used to assess explanatory variables of MWT and ESS results. ResultsWe included 141 patients, of whom 12.8 % had both subjective sleepiness and objective impaired alertness, 17.7 % objective impaired alertness only and 9.2 % subjective sleepiness only. Self-reported history of car accident/near miss, smoking history and ESS≥11 were significantly associated with objective impaired alertness whereas residual Apnea-hypopnea Index and CPAP use were not. The only significant variable associated with ESS at the time of MWT evaluation was initial ESS. Patients with objective impaired alertness only were more often smokers (52 % vs 19 %, p = 0.01), had a higher body mass index (BMI) (32 vs 29 kg/m2, p = 0.05), and showed lower initial ESS (11 vs 13, p < 0.01). ConclusionsMore than one third of OSA treated patients referred for MWT have objective impaired alertness and/or subjective sleepiness. Our findings highlight the need for a comprehensive medical assessment including accident history, subjective sleepiness and comorbidities. Particular attention should be paid to smoking patients with high BMI, who are at risk of impaired alertness with no report of subjective sleepiness.

Multidimensional prediction of continuous positive airway pressure adherence

ObjectiveContinuous positive airway pressure (CPAP) is the standard treatment for obstructive sleep apnea (OSA). Unsatisfactory adherence to CPAP is an important clinical issue to resolve. Cluster analysis is a powerful tool to distinguish subgroups in a multidimensional fashion. This study aimed to investigate the use of cluster analysis for predicting CPAP adherence using clinical polysomnographic (PSG) parameters and patient characteristics. Patients/methodsParticipants of this multicenter observational study were 1133 patients with OSA who were newly diagnosed and implemented CPAP. Ward's method of cluster analysis was applied to in-laboratory diagnostic PSG parameters and patient characteristics. CPAP adherence was assessed during 90- and 365-day periods after CPAP initiation in each cluster. We adopted the Centers for Medicare and Medicaid Services criterion for CPAP adherence, i.e., CPAP use ≥4 h per night for 70 % or more of the observation period. Logistic regression analysis was performed to stratify clusters according to CPAP adherence. ResultsFive clusters were identified through cluster analysis. Clustering was significantly associated with CPAP adherence at 90- and 365-day periods after CPAP initiation. Logistic regression revealed that the cluster with features including apnea predominant sleep-disordered breathing, high apnea-hypopnea index, and relatively older age demonstrated the highest CPAP adherence. ConclusionCluster analysis revealed hidden connections using patient characteristics and PSG parameters to successfully identify patients more likely to adhere to CPAP for 90 days and up to 365 days. When prescribing CPAP, it is possible to identify patients with OSA who are more likely to be non-adherent.

CSF-profile and hypocretin levels in children with narcolepsy type 1 and 2

BackgroundNarcolepsy is a rare neurological disease caused by dysfunction of hypocretin-producing neurons. Hypocretin concentrations in the cerebrospinal fluid (CSF) of less than 110 pg/ml are considered pathological in adults. ObjectivesTo compare hypocretin levels of children with narcolepsy type 1, type 2 and disease control groups, in addition to a detailed CSF analysis, clinical and polysomnographic parameters. MethodsIn a retrospective, cross-sectional study, children diagnosed with narcolepsy based on clinical and polysomnographic parameters, who received a CSF analysis and hypocretin measurement, in addition to controls, were included. CSF was analyzed for the presence of cells, total protein, lactate, intrathecal synthesis of antibodies against measles, rubella and/or varicella zoster, and oligoclonal bands. All children had a complete sleep study including a multiple sleep latency test (MSLT). Results49 children with narcolepsy type 1, 15 children with type 2 and 37 children with other (suspected) neurological diseases were included. CSF routine analysis did not reveal any differences between the three groups. All children with narcolepsy type 1 had hypocretin levels of less than 110 pg/ml (range: 10–101 pg/ml). Hypocretin levels in type 2 patients ranged from 43 to 436 pg/ml (median 157 pg/ml). The median hypocretin level in the control cohort was 365 pg/ml (range: 153–583 pg/ml). In 4 children with narcolepsy type 2 the diagnosis was changed to narcolepsy level 1 because of a CSF hypocretin level of less than 110 pg/ml according to the recently proposed criteria, which consider the measurement of hypocretin in CSF. ConclusionChildren with narcolepsy type 1 showed significantly lower CSF hypocretin levels than children with narcolepsy type 2 and controls. As suggested by the recently published narcolepsy criteria, hypocretin levels of less than 110 pg/ml should be used as an additional criterion for the presence of narcolepsy type 1 in children.

Weight Status, Autonomic Function, and Systemic Inflammation in Children with Obstructive Sleep Apnea.

Children with obstructive sleep apnea (OSA) frequently experience chronic low-grade systemic inflammation, with the inflammasome playing a central role in OSA. This cross-sectional study evaluated the relationship between weight status, autonomic function, and systemic inflammation in a cohort of 55 children with OSA, predominantly boys (78%) with an average age of 7.4 ± 2.2 years and an apnea-hypopnea index of 14.12 ± 17.05 events/hour. Measurements were taken of body mass index (BMI), sleep heart-rate variability, morning circulatory levels of interleukin-1β, interleukin-1 receptor antagonist, and interleukin-6, and tumor necrosis factor-α, anthropometry, and polysomnography. Multiple linear regression modeling showed that an apnea-hypopnea index was significantly associated with BMI, the standard deviation of successive differences between normal-to-normal intervals during N3 sleep, and the proportion of normal-to-normal interval pairs differing by more than 50 ms during rapid-eye-movement sleep. A moderated mediation model revealed that interleukin-1 receptor antagonist levels mediated the association between BMI and interleukin-6 levels, with sympathovagal balance during N3 sleep and minimum blood oxygen saturation further moderating these relationships. This study highlights the complex relationships between BMI, polysomnographic parameters, sleep heart-rate-variability metrics, and inflammatory markers in children with OSA, underlining the importance of weight management in this context.

Long-term mortality risk in obstructive sleep apnea: the critical role of oxygen desaturation index.

Mortality predictors in obstructive sleep apnea (OSA) patients yet to be comprehensively understood, especially within large cohorts undergoing long-term follow-up. We aimed to determine the independent predictors of mortality in OSA patients. In our retrospective cohort study, 3,541 patients were included and survival data was obtained from electronic medical records. Demographic characteristics, anthropometric measurements, comorbidities, laboratory tests, and polysomnography parameters were analyzed for the survived and deceased patient groups. Univariate and multivariate Cox regression analyses were performed to determine independent predictors of all-cause mortality in patients followed for at least 5 years. Among all patients, 2,551 (72%) patients were male, with a mean age of 49.7 years. 231 (6.5%) patients had died. Deceased patients were significantly older and had higher waist-to-hip ratio and Epworth Sleepiness Scale (p < 0.001, p < 0.001, p = 0.003). OSA (nonpositional and not-rapid eye movement-related), periodic limb movements in sleep and Comorbidities of Sleep Apnea Score ≥ 1 were found to be associated with increased mortality (p < 0.001). Systemic immune-inflammation index was also significantly higher in the deceased group (p < 0.001). Higher oxygen desaturation index (ODI) and apnea-hypopnea index (AHI) were associated with increased mortality (p < 0.001). Due to the high correlation between ODI and AHI, two separate multivariate Cox regression models were created. While AHI lost its significance in the multivariate analysis, ODI remained significantly higher in the deceased patient group (HR = 1.007, 1.001-1.013, p = 0.01). ODI, as the only polysomnography parameter, emerged as an independent predictor of mortality in OSA patients.

Automated remote sleep monitoring needs uncertainty quantification.

Wearable electroencephalography devices emerge as a cost-effective and ergonomic alternative to gold-standard polysomnography, paving the way for better health monitoring and sleep disorder screening. Machine learning allows to automate sleep stage classification, but trust and reliability issues have hampered its adoption in clinical applications. Estimating uncertainty is a crucial factor in enhancing reliability by identifying regions of heightened and diminished confidence. In this study, we used an uncertainty-centred machine learning pipeline, U-PASS, to automate sleep staging in a challenging real-world dataset of single-channel electroencephalography and accelerometry collected with a wearable device from an elderly population. We were able to effectively limit the uncertainty of our machine learning model and to reliably inform clinical experts of which predictions were uncertain to improve the machine learning model's reliability. This increased the five-stage sleep-scoring accuracy of a state-of-the-art machine learning model from 63.9% to 71.2% on our dataset. Remarkably, the machine learning approach outperformed the human expert in interpreting these wearable data. Manual review by sleep specialists, without specific training for sleep staging on wearable electroencephalography, proved ineffective. The clinical utility of this automated remote monitoring system was also demonstrated, establishing a strong correlation between the predicted sleep parameters and the reference polysomnography parameters, and reproducing known correlations with the apnea-hypopnea index. In essence, this work presents a promising avenue to revolutionize remote patient care through the power of machine learning by the use of an automated data-processing pipeline enhanced with uncertainty estimation.

Prognostic Factors Related to Sleep Quality in Patients With Obstructive Sleep Apnea After Positive Airway Pressure Therapy

Background and Objectives: This study aimed to evaluate the factors that influence deep sleep restoration in patients with obstructive sleep apnea (OSA) following positive airway pressure (PAP) therapy.Methods: In total, 363 patients diagnosed with OSA who received PAP therapy over at least 3 months were enrolled in the study. Polysomnographic parameters, anatomical characteristics, and subjective sleep-related parameters were evaluated according to the presence of daytime sleepiness and morning headache before and after 3 months of PAP treatment.Results: Age was significantly different according to whether excessive daytime sleepiness (EDS) was alleviated (average: 49.35 years) or persisted (average: 52.82 years) (p=0.001). Age was also significantly associated with morning headache (p=0.037). Body mass index (BMI) was higher in the alleviated EDS group (28.70 kg/m&lt;sup&gt;2&lt;/sup&gt;) than in the persistent EDS group (27.13 kg/m&lt;sup&gt;2&lt;/sup&gt;; p=0.002). The apnea-hypopnea index (AHI) was correlated with the EDS outcome (p=0.011). The group with alleviated EDS had a longer mandibular plane to hyoid distance (MPH) than the group with persistent EDS (17.95 mm vs. 15.38 mm; p&lt;0.001). However, BMI, AHI, and MPH showed no significant associations with morning headache. Epworth Sleepiness Scale scores were higher in the alleviated EDS and alleviated morning headache groups (EDS: p&lt;0.001, morning headache: p=0.001). Self-Efficacy Measure for Sleep Apnea (SEMSA) values differed significantly between the EDS groups (p&lt;0.001), but not between the morning headache groups (p=0.122). After 3 months of PAP therapy, the MPH was negatively correlated with EDS in univariate (odds ratio [OR]=0.921, p&lt;0.001) and multivariate analyses (OR=0.937, p=0.028). The SEMSA score was also negatively correlated with EDS in univariate (OR=0.961, p&lt;0.001) and multivariate (OR=0.973, p=0.019) analyses.Conclusion: Age, polysomnographic metrics, and anatomical considerations were important for sleep quality-associated daytime symptoms. In addition, anatomical characteristics and the patient’s self-efficacy were significantly associated with the effect of PAP treatment on sleep quality.

The effect of sleep and its restriction on selected inflammatory parameters

Insufficient sleep duration may lead to a series of immune dysfunctions. One of the factors influencing this effect could be physical activity (PA). The study aimed to assess the impact of deprivation of sleep (DS) on selected inflammatory parameters. Seventy-seven participants completed the protocol consisting of polysomnography (PSG) conducted in a sleep laboratory and DS, monitored with an actigraph. PA was assessed with actigraphy, which categorized participants as active or inactive. White blood cells (WBC) values negatively correlated with sleep efficiency based on sleep diaries and PSG parameters (total sleep time, sleep efficiency, and REM duration), but regression analysis showed that WBC depends only on the sleep diary parameter. Granulocytes (GRA) positively correlated with REM latency, and negatively with sleep efficiency. After DS, all participants exhibited an elevated GRA count. The number of WBC and GRA increased also in the active group; inactive participants showed no changes in inflammatory parameters. The overall number of WBC depends primarily on the quality of sleep over a period of several days. Under the influence of sleep deprivation, the number of GRA increases, but the number of leukocytes depends on the level of physical activity during DS.

Proportion of sleep-related breathing disorders and their association with echocardiographic parameters in stable patients with chronic obstructive pulmonary disease: a cross-sectional observational exploratory study

Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality throughout the world. The coexistence of COPD and obstructive sleep apnea (OSA) (i.e., overlap syndrome) has been reported in several studies. Both disorders independently increase the risk of cardiovascular complications. Hence, there is a theoretical possibility that cardiovascular parameters may be worse in patients with overlap syndrome compared to those with only COPD. However, this has been sparsely assessed in the literature. This study aimed to compare the clinical characteristics, echocardiography, and sleep parameters amongst COPD patients with and without sleep-related breathing disorders (SRBD). This observational, cross-sectional study included 30 patients with stable COPD. All participants underwent a detailed clinical evaluation, followed by level 1 polysomnography (PSG). Each participant underwent echocardiographic evaluation to estimate mean pulmonary artery pressure from right ventricular systolic pressure (RVSP). Based on their PSG findings, participants were classified into non-SRBD and SRBD groups. Both groups were further compared with respect to clinical characteristics, echocardiographic, and PSG parameters. We found that most of the participants (93.3%) were male, and the mean age of the study population was 56±8.2 years. The only SRBD identified in this study was OSA, which was observed in 80% of participants. In this group, OSA was not associated with obesity. Systemic hypertension (50%) was the most common comorbidity, followed by diabetes mellitus (26.67%), but both were not significantly different between the groups. The mean RVSP was significantly higher amongst OSA patients than non-OSA patients (41.25±14.98 versus 30.83±5.84, respectively; p=0.01). OSA was seen in 80% of participants with stable COPD, even in the absence of obesity. The presence of OSA was associated with a higher RVSP in this patient group.

Amyloid profile is associated with sleep quality in preclinical but not in prodromal Alzheimer’s disease older adults

BackgroundFew studies have assessed whether neuropathological markers of AD in the preclinical and prodromal stages are associated with polysomnographic changes and obstructive sleep apnea (OSA). MethodsThis was a cross-sectional, case-control study of older adults (≥60 years) without relevant clinical and psychiatric comorbidities selected randomly from a cohort of individuals without dementia in a tertiary university hospital in São Paulo, Brazil. They underwent neuropsychological evaluation for clinical diagnosis and were allocated into two samples: cognitively unimpaired (CU) and mild cognitive impairment (MCI). Also, they underwent PET-PiB to determine the amyloid profile and all-night in-lab polysomnography. For each sample, we compared polysomnographic parameters according to the amyloid profile (A+ vs A-). ResultsWe allocated 67 participants (mean age 73 years, SD 10,1), 70 % females, 14 ± 5 years of education, into two samples: CU (n = 28, 42.4 %) and MCI (n = 39, 57.6 %). In the CU sample, the group A+ (n = 9) showed worse sleep parameters than A- (n = 19) (lower total sleep time (p = 0.007), and sleep efficiency (p = 0.005); higher sleep onset latency (p = 0.025), wake time after sleep onset (p = 0.011), and arousal index (AI) (p = 0.007)), and changes in sleep structure: higher %N1 (p = 0.005), and lower %REM (p = 0.006). In the MCI sample, MCI A-had higher AI (p = 0.013), respiratory disturbance index (p = 0.025, controlled for age), and higher rates of severe OSA than A+. DiscussionThe amyloid profile was associated with polysomnographic markers of worse sleep quality in individuals with preclinical AD but not with prodromal AD, probably due to the higher frequencies of severe OSA.

Correlation between arousal threshold and occurrence of hypertension in patients with obstructive sleep apnea hypopnea syndrome

Objective: To investigate the relationship between arousal threshold (ArTH) and hypertension in patients with obstructive sleep apnea hypopnea syndrome (OSA). Methods: This study recruited 648 patients diagnosed with OSA at the Sleep Center of the Second Affiliated Hospital of Soochow University from January 2020 to August 2021, including 569 males and 79 females, aged 42(35,52) years. The basic demographic information and clinical data of all patients were collected, including blood pressure measurement, and relevant questionnaire scores, and nocturnal polysomnography (PSG) parameters. A clinical predictive model based on sleep apnea hypopnea index (AHI), lowest pulse oxygen saturation (LSpaO2) and hypopnea ratio (FHypopneas) was used to access the arousal threshold of OSA patients. Patients were divided into OSA group and OSA with hypertension group according to whether they were combined with hypertension. The differences in the above indexes between the two groups were analyzed to explore the relationship between arousal threshold and hypertension in OSA patients, using a binary logistic stepwise regression analysis. Results: A total of 648 OSA patients were enrolled, including 415 in the OSA with hypertension group and 233 in the OSA group. Compared with OSA group, OSA with hypertension group had older age, higher body mass index (BMI), higher blood pressure at bedtime and at awakening, higher AHI and lower proportion of hypopnea (all P<0.05). There were no significant differences between other general data and PSG parameters (all P>0.05). The proportion of patients with low arousal threshold (AHI<30 events per hour, LSpO2>82.5%, Fhypopneas>58.3%) in OSA with hypertension group was lower, and the proportion of phenotypic patients with low arousal threshold was significantly lower (30.1% vs. 52.4% P<0.001). Binary logistic stepwise regression analysis showed that the high arousal threshold (OR=1.930, 95%CI:1.326-2.808, P=0.001) was an independent risk factor for OSA complicated with hypertension. Conclusion: The arousal threshold is associated with the development of hypertension in OSA patients, and OSA patients with a high arousal threshold have a higher risk of developing hypertension.

Polysomnography parameters in a large cohort of people with multiple sclerosis

BackgroundDisordered and disturbed sleep is quite common among people with multiple sclerosis (PwMS). It is associated with fatigue one of most disabling symptoms in MS. This study aims at comparing polysomnographic (PSG) sleep parameters in a large single cohort of PwMS from a single center to that of the published norms. Hence establishing PSG parameters in PwMS. MethodsThis is a retrospective review of 299 consecutive adult PwMS who were seen and evaluated with an overnight PSG at a Comprehensive MS Care Center between 11/19/2001 to 9/17/2014. Data extracted from the PSG included Total Sleep Time (TST), sleep efficiency (SE), sleep onset latency (SOL), Relative REM latency, total apnea-hypopnea indices (AHI), spontaneous arousal indices (AI), total periodic leg movements indices (PLMI) and, sleep architecture metrics including percentage spent in stages N1/N2, N3, and REM. ResultsPwMS, compared to normative data, had, on average, 85.9 min shorter TST (p < 0.001), 27.3 min longer SOL (p < 0.0001), 62.1 min longer REM latency (p < 0.0001), 10.7 % lower SE (p < 0.0001), 16.4 % more N1/N2 (p < 0.0001) and 11.4 % less N3 (p < 0.0001). REM latency The prevalence of Obstructive Sleep Apnea (OSA) was high at 60.7 % and the mean AHI was higher by 11.1 events per hour (p < 0.0001). ConclusionsThis study establishes PSG parameters in the largest PwMS cohort reported to date. It is important to be vigilant of sleep complaints in PwMS. Future prospective large single cohort studies with standardized methods are needed to further understand sleep disturbances in PwMS as well as their causes and implications.

Changes in slow-wave sleep characteristics in Parkinson's disease patients with mild-moderate depression

IntroductionDepression and sleep disturbances are commonly seen non-motor symptoms in patients with Parkinson's disease (PD). This study used polysomnography to examine the relationship between mild-moderate depression in PD and sleep characteristics, particularly slow wave activities (SWA). Methods59 PD patients were split into two groups: nd-PD (n = 27) (patients with PD without depression) and d-PD (n = 32) (patients with PD with mild-moderate depression). Their clinical features, polysomnography parameters, and demographics were evaluated. Early and late sleep SWA spectrum densities and overnight SWA decline in different brain regions were particularly analyzed. ResultsNon-rapid eye movement 3 (N3) sleep duration and percentage were greater in the d-PD group. N3 percentage was linked to depression (p = 0.014). During late sleep, higher SWA (0.5–4Hz) in the frontal and central regions, higher low-SWA (0.5–2Hz) in the whole brain, central and occipital regions, and higher high-SWA (2–4Hz) in the frontal region was observed in the d-PD group. During early sleep, there was also higher low-SWA (0.5–2Hz) in the occipital region. Patients in d-PD group exhibited reduced overnight high-SWA (2–4Hz) decline (Δhigh-SWA) in the whole brain and occipital regions. Δhigh-SWA(2–4Hz) in the occipital region were associated with depression (p = 0.049). ConclusionPD patients with mild-moderate depression have impaired slow wave sleep, exhibiting as increased N3 sleep, SWA, and reduced overnight SWA decline. This implies that synaptic strength reduction during sleep and impaired synaptic homeostasis regulation may be associated with depression in PD. Reduced overnight high-SWA decline in the occipital region may serve as a novel electrophysiological biomarker for indicating depression in PD.

Predicting Alzheimer's disease CSF core biomarkers: a multimodal Machine Learning approach.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder. Current core cerebrospinal fluid (CSF) AD biomarkers, widely employed for diagnosis, require a lumbar puncture to be performed, making them impractical as screening tools. Considering the role of sleep disturbances in AD, recent research suggests quantitative sleep electroencephalography features as potential non-invasive biomarkers of AD pathology. However, quantitative analysis of comprehensive polysomnography (PSG) signals remains relatively understudied. PSG is a non-invasive test enabling qualitative and quantitative analysis of a wide range of parameters, offering additional insights alongside other biomarkers. Machine Learning (ML) gained interest for its ability to discern intricate patterns within complex datasets, offering promise in AD neuropathology detection. Therefore, this study aims to evaluate the effectiveness of a multimodal ML approach in predicting core AD CSF biomarkers. Mild-moderate AD patients were prospectively recruited for PSG, followed by testing of CSF and blood samples for biomarkers. PSG signals underwent preprocessing to extract non-linear, time domain and frequency domain statistics quantitative features. Multiple ML algorithms were trained using four subsets of input features: clinical variables (CLINVAR), conventional PSG parameters (SLEEPVAR), quantitative PSG signal features (PSGVAR) and a combination of all subsets (ALL). Cross-validation techniques were employed to evaluate model performance and ensure generalizability. Regression models were developed to determine the most effective variable combinations for explaining variance in the biomarkers. On 49 subjects, Gradient Boosting Regressors achieved the best results in estimating biomarkers levels, using different loss functions for each biomarker: least absolute deviation (LAD) for the Aβ42, least squares (LS) for p-tau and Huber for t-tau. The ALL subset demonstrated the lowest training errors for all three biomarkers, albeit with varying test performance. Specifically, the SLEEPVAR subset yielded the best test performance in predicting Aβ42, while the ALL subset most accurately predicted p-tau and t-tau due to the lowest test errors. Multimodal ML can help predict the outcome of CSF biomarkers in early AD by utilizing non-invasive and economically feasible variables. The integration of computational models into medical practice offers a promising tool for the screening of patients at risk of AD, potentially guiding clinical decisions.

Ethnic/racial and sex disparities in obstructive sleep apnea among adolescents in southern California.

Pediatric obstructive sleep apnea (OSA) is common; however, inclusion of adolescents and especially those of ethnic/racial minorities in research is scarce. We hypothesized that ethnic/racial minority adolescents undergoing polysomnography have higher prevalence and more severe OSA compared to those who are non-Hispanic (NH) White. Retrospective review of 1,745 adolescents undergoing diagnostic polysomnography. Demographic characteristics, age, body mass index percentile, and polysomnography parameters were obtained. Descriptive statistics comparing race/ethnicity were analyzed. Linear regression of log-transformed obstructive apnea-hypopnea index, and logistic regression of moderate-severe OSA (obstructive apnea-hypopnea index ≥ 5 events/h) adjusting for covariates were analyzed. A total of 58.2% adolescents were Hispanic, 24.1% NH-White, 4.3% NH-Asian/Pacific Islander, 4.2% NH-Black/African American, and 6.6% NH-other. Compared to the NH-White group, the Hispanic group had higher obstructive apnea-hypopnea index and any level of OSA severity, the Black/African American group had higher any level of OSA, and the NH-Asian group had higher moderate-severe OSA. Multiple linear regression of log-obstructive apnea-hypopnea index identified a positive association with Hispanic ethnicity (β: 0.25, P value < .05). Compared to the NH-White group, the Hispanic and the Asian/Pacific Islander groups were 1.45 (95% confidence interval: 1.10, 1.93) and 1.81 (95% confidence interval: 1.05, 3.10) times more likely to have moderate-severe OSA, respectively, after adjusting for relevant covariates. Stratified analysis by sex identified an association only among males between Hispanic ethnicity (odds ratio: 1.85, 95% confidence interval: 1.27, 2.70) and Asian/Pacific Islander ethnicity (odds ratio: 2.62, 95% confidence interval: 1.35, 5.11) and moderate-severe OSA, compared to the NH-White group. Among adolescents undergoing polysomnography evaluation, we identified OSA racial/ethnic and sex disparities in Hispanic and NH-Asian adolescents. Community level studies with adequate representation of these minority groups are needed to identify factors associated with the reported increased susceptibility. Landeo-Gutierrez J, Ryu J, Tantisira K, Bhattacharjee R. Ethnic/racial and sex disparities in obstructive sleep apnea among adolescents in southern California. J Clin Sleep Med. 2024;20(10):1637-1645.

SnoreLab Application in the Assessment of Obstructive Sleep Apnea Syndrome: A Pilot Study

Background: SnoreLab (Version 5.3, Reviva Softworks Ltd., London, UK) is featured as the number one mobile application (app) for measuring snoring intensity and duration. The aim of this study was to conduct a comparative analysis between the results derived from SnoreLab and polysomnography (PSG). Methods: Male and female patients between 18 and 75 years of age, seeking medical counseling for suspected obstructive sleep apnea syndrome (OSAS), were considered eligible to participate in this study. Exclusion criteria were psychological or neurological disorders, drug or alcohol abuse, and inability to follow instructions. All patients underwent one overnight in-hospital PSG with simultaneous snoring recording using the SnoreLab app. Results: Nineteen patients (15 men, 4 women) aged 50.9 ± 10.5 years were included. The overall cohort exhibited a Snore Score of 24.8 ± 22.2 alongside an AHI of 15.1 ± 17.0, indicating moderate OSAS. Interestingly, elevated Snore Scores were observed in both the simple snoring (30.7 ± 19.2) and severe OSAS group (35.2 ± 21.4) (Kruskal–Wallis p-value = 0.176). The analysis of the Spearman’s test did not reveal a statistically significant correlation between PSG parameters and the Snore Score. Conclusions: While SnoreLab records snoring, it is not designed for screening sleep apnea. Although SnoreLab may not replace PSG for use in diagnosis, it could serve as a complementary tool for monitoring snoring and to improve the interaction between patients and clinicians when integrated into a suitable clinical assessment.

Assessment of sleep quality in patients with orofacial pain and headache complaints: A polysomnographic study.

Sleep is a physiological function essential for survival, recovery, tissue repair, memory consolidation, and brain function. Pain is also an indispensable aspect of human life. The coexistence of sleep disorders and pain is often described in the literature, yet it is critical to define sleep not only subjectively but also using objective instrumental methods, such as polysomnography, that provide data on sleep quality. The aim of the study was to determine the relationship between orofacial pain (OFP), headache (HA) and sleep quality using subjective and objective sleep quality assessment methods. Additionally, we aimed to explore whether poor sleep quality was related to OFP and HA alone or was influenced by the coexistence of psycho-emotional factors such as depression, anxiety and stress. A single-night video-polysomnography was performed on patients from the Outpatient Clinic for Temporomandibular Disorders at Wroclaw Medical University, Poland, who had been diagnosed with OFP and HA. Additionally, questionnaires were employed to assess sleep quality, pain, HA, and the psycho-emotional state. There was no statistically significant relationship between the severity of OFP and HA and polysomnographic sleep quality parameters. On the other hand, the quality of sleep as determined by questionnaire studies correlated markedly with the severity of experienced pain. The severity of pain was found to be significantly correlated with depression, anxiety and perceived stress scores. The psycho-emotional aspects are of critical importance in the perception of OFP and HA. They can be associated with worsened subjective sleep quality, insomnia or daytime sleepiness. Therefore, the treatment of such patients must be preceded by a comprehensive assessment of their psychoemotional state, as anxiety, stress and depression can significantly influence the course of the disease and the response to treatment procedures.

Clinical characteristics, associated comorbidities and hospital outcomes of neonates with sleep disordered breathing: a retrospective cohort study

ObjectiveAwareness of the need for early identification and treatment of sleep disordered breathing (SDB) in neonates is increasing but is challenging. Unrecognised SDB can have negative neurodevelopmental consequences. Our study...

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.