Severity and phenotype of sleep-disordered breathing in Prader-Willi syndrome compared to obstructive sleep apnea syndrome in children.

The aim of this study was to obtain additional data in the definition of phenotypes of Obstructive Sleep Apnea Syndrome (OSAS) by comparing the body mass index (BMI) and neck and waist circumference( NC and WC) measurements with polysomnography (PSG) findings in patients with OSAS. This retrospective study included 150 patients diagnosed with OSAS. The sociodemoographic data, comorbidities, PSG data (apnea-hypopnea index [AHI], obstructive apnea, central apnea, mixed apnea, obstructive hypopnea, central hypopnea, mixed hypopnea index, rapid eye movement [REM] AHI, supine AHI, minimum oxygen saturation), Epworth Sleepiness Scale (ESS), and Mallampati types were analyzed. The PSG data were compared in males and females according to BMI and NC and WC measurements. In female patients with NC > 40cm, the highest obstructive apnea index and AHI values (p = 0.009; p < 0.01, p = 0.030; p < 0.05) and the lowest O2 saturation values (p = 0.049; p < 0.05) were seen to be statistically significant. In females with BMI of 25-30, Mallampati 3 was seen at the highest rate, and the highest rates of central apnea and mixed apnea index values were determined in this group (p = 0.018; p < 0.05, p = 0.038; p < 0.05). In males with NC > 43cm, the AHI, obstructive apnea-hypopnea index, and REM-supine AHI values were highest (p < 0.01 for all), and the lowest O2 saturation values were seen in this group (p = 0.009; p < 0.01). In males with WC > 102cm, the highest AHI, obstructive apnea-hypopnea, and supine AHI values were determined (p = 0.042; p < 0.05; p = 0.042; p < 0.05; p = 0.002; p < 0.01; p = 0.016; p < 0.05), and the lowest O2 saturation values (p = 0.001; p < 0.01) at levels of statistical significance. The NC, WC, and BMI values were determined to be correlated with AHI in males but not in females. In females with BMI of 25-30, elevated central apnea and mixed apnea index values were a noticeable finding. The airway in these patients was determined to be narrower, and NC in females was related to supine AHI. It is thought that these findings could be helpful in the identification of OSAS phenotypes according to anthropometric measurements.

PurposeObstructive sleep apnea (OSA) is highly prevalent in polio survivors, but longitudinal data on its progression remain limited. This study aimed to characterize OSA progression in community-dwelling polio survivors and compare it with an age-matched control group.MethodsA prospective 5-year longitudinal study recruited 148 polio survivors (48.76 ± 5.97 years, 75% male). At baseline (2014), all participants underwent overnight oximetry. Among them, 42 completed in-lab polysomnography (PSG) testing. Over the 5-year follow-up, 112 polio survivors (76.79% male, mean age 48.48 ± 6.05 years) were successfully tracked, with 33 undergoing follow-up PSG. Additionally, 59 age- and sex-matched OSA patients were enrolled as controls. Primary outcomes included changes in oxygen desaturation index ≥4% (ODI4) and apnea-hypopnea index (AHI). Correlates of OSA progression were analyzed using Pearson’s correlations.ResultsOver 5 years, ODI4 increased significantly in polio survivors from 8.11 ± 9.13 to 10.35 ± 11.63 events/h (p = 0.01), with a shift toward moderate–severe ODI4 (13 to 22%, p = 0.027). AHI also rose in both groups: polio survivors (26.57 ± 21.25 to 33.86 ± 22.43 events/h, p = 0.02) and controls (27.14 ± 21.91 to 37.24 ± 24.55 events/h, p = 0.004), with no significant group difference in AHI progression (p = 0.89). However, polio survivors showed increased mixed apnea index (p = 0.02) and prolonged REM sleep latency (p = 0.009). ODI4 changes correlated with scoliosis (r = 0.27, p = 0.005) and BMI fluctuations (r = 0.25, p = 0.008).ConclusionOSA-related parameters, particularly mixed apnea and REM alterations, progress in polio survivors. Changes in ODI4 were positively correlated with BMI fluctuations and scoliosis.

PurposeSleep apnea is a prevalent sleep disorder with serious health implications. This study introduces ApneaWhisper, a Transformer-based audio segmentation model designed for noninvasive detection of sleep apnea subtypes using PSG-Audio data.Patients and MethodsWe utilized a PSG-Audio dataset from 284 patients. ApneaWhisper leverages a pretrained Whisper encoder to extract 10 ms-resolution frame-level features from 20-second audio clips. A lightweight Transformer decoder with token-based segmentation and a classification head aggregates these features for both frame-level and clip-level predictions. The model was fine-tuned using class-balanced cross-entropy loss to address data imbalance across apnea subtypes.ResultsApneaWhisper achieved strong performance for sleep apnea detection, with a clip-level F1-score of 0.82 and a frame-level F1-score of 0.70, outperforming conventional baselines including MFCC+DNN, VGGish+bi-LSTM, and VAD-based models. It also showed promising ability in distinguishing between OSA, MSA, CSA, and hypopnea, though with varying success.ConclusionThe model’s fine-grained temporal resolution enables precise apnea event localization, duration estimation, and subtype classification. While ApneaWhisper performs robustly for OSA, challenges remain in distinguishing central (CSA) and mixed (MSA) sleep apnea, due to subtle or ambiguous acoustic patterns. The frame-level segmentation also facilitates accurate apnea–hypopnea index (AHI) estimation, which could reduce dependence on full PSG studies in certain clinical and home-monitoring scenarios. Future improvements may involve multimodal integration (eg, oxygen saturation) and noise-robust training techniques.

Background/Objectives: Congenital laryngomalacia (LM) is the most common cause of stridor in infants, presenting with a clinical spectrum that ranges from benign, self-limiting symptoms to severe airway obstruction. This study aimed to objectively characterize the type and severity of sleep-disordered breathing in infants with LM using polysomnography (PSG) and to correlate findings with LM subtypes, clinical presentation, and type of surgical intervention. Methods: A cohort of 42 infants diagnosed with LM (Type I: n = 14, Type II: n = 18, Type III: n = 10) underwent overnight PSG before surgical treatment. The Apnea-Hypopnea Index (AHI), Oxygen Desaturation Index (ODI), minimum and mean SpO2, and heart rate were recorded. Clinical features (stridor, feeding difficulties, respiratory effort) and type of surgery (supraglottoplasty [S] or supraglottoplasty with epiglottopexy [S + E]) were analyzed across LM subtypes. Results: Baseline AHI was significantly higher in LM Type III (25.41 ± 6.95 events/h) compared with Type II (12.50 ± 5.05) and Type I (2.84 ± 1.96; p < 0.001). After surgery, AHI decreased to 1.76 ± 1.56 in Type III and 0.97 ± 0.70 in Type II. ODI showed a similar trend (Type III: 9.87 ± 5.99 before vs. 0.78 ± 0.69 after surgery; p < 0.001). Minimum SpO2 increased from 69.50 ± 7.76% to 93.60 ± 1.82% in Type III (p < 0.001). Feeding difficulties were observed in 100% of Type III patients, compared with 83.3% of Type II and 42.9% of Type I patients. The distribution of apnea type differed significantly across groups (p < 0.001), with mixed obstructive-central apnea predominating in Type III. Conclusions: Polysomnography is an effective and objective tool for assessing LM severity and guiding surgical qualification. Increasing LM severity is associated with more pronounced PSG abnormalities, greater clinical burden, and a higher likelihood of requiring advanced surgical correction.

Sleep-disordered breathing is a key childhood complication in children with achondroplasia. This retrospective study aimed to document the prevalence of sleep-disordered breathing in children with achondroplasia assessed by polysomnography. The prevalence of sleep-disordered breathing assessed by polysomnography among children aged 0-18 years with achondroplasia from 2013 to 2024 at The Royal Children's Hospital, Australia, was retrospectively reviewed. The cohort included 80 children with achondroplasia (54% females, 95% confirmed molecular diagnosis) with an average number of 3.6 polysomnographies collected per child (n=288). A total of 85% (68/80) had sleep-disordered breathing and 21% reported no prior symptoms. Sleep-disordered breathing subtypes included obstructive sleep apnoea in 81% (55/68), central sleep apnoea in 3% (2/68), mixed sleep apnoea in 7% (5/68) and primary snoring in 9% (6/68). Among those with obstructive and mixed sleep apnoea, 58% (35/60) had moderate or severe obstructive sleep apnoea. In 44 children, a corresponding MRI was evaluated for foramen magnum stenosis using the Achondroplasia Foramen Magnum Score. No correlation was found with sleep-disordered breathing severity (Spearman's coefficient (ρ)=0.03). Among 27 children who received a precision therapy for achondroplasia (vosoritide, n=18, infigratinib, n=8 and recifercept, n=1), the median respiratory disturbance index/hour improved from 2.7 (25th-75th percentile, (0.9-4.8)) to 1.1 (0.3-2.6) after 1 year of treatment compared with baseline. Sleep-disordered breathing was present in 85% of 80 children with achondroplasia, with 21% being asymptomatic. Respiratory parameters did not correlate with foramen magnum stenosis severity and improved after 1 year of treatment in those treated with a precision therapy.

ABSTRACT The reliability of Thai certificate qualifications for Advanced Sleep Technicians (ASTs) and Sleep Disorders Specialists (SDSs) in manual polysomnography (PSG) scoring has not been previously evaluated. This study assessed the reliability of PSG scoring performed by ASTs, an SDS, and an automated scoring system (AUTO) at Thammasat University Hospital, Thailand. A retrospective analysis of 250 PSG recordings conducted between September 2022 and February 2023 classified patients into four groups based on the apnea-hypopnea index (AHI): No OSA (AHI <5), mild OSA (AHI 5–15), moderate OSA (AHI 15–30), and severe OSA (AHI >30), comprising 11, 77, 105, and 57 cases, respectively. Scoring reliability was compared among ASTs, SDSs, and AUTO. A single-blinded SDS independently scored the PSG data without knowing the AST’s scoring to ensure an unbiased assessment. Across more than 630,000 epochs, the Kappa (κ) statistic demonstrated stronger agreement between AST and SDS (κ = 0.980, 95% CI 0.976–0.984) than between AST and AUTO (κ = 0.599, 95% CI 0.543–0.655), indicating significant differences (p < .0001). For mixed apneas (MAs), intraclass correlation coefficients (ICCs) showed the highest consistency between AST and SDS (ICC = 0.998, 95% CI 0.997–0.998) compared to AST and AUTO (ICC = 0.869, 95% CI 0.836–0.897). Significant differences were observed between AST and SDS compared to AST and AUTO across most metrics (P < .0487). While ASTs and SDSs demonstrated excellent scoring consistency, AUTO scoring was notably less accurate, suggesting that the AUTO system requires further refinement to ensure reliable clinical use.

To develop and validate a Complete Artificial Intelligence Sleep Report system (CAISR), a system for comprehensive automated sleep analysis, including sleep staging, arousal detection, apnea identification, and limb movement analysis. We utilized a large diverse dataset from four cohorts (MGH, MESA, MrOS, SHHS) comprising 25,749 participants to develop CAISR. Following American Academy of Sleep Medicine (AASM) guidelines, CAISR performs four tasks: it stages sleep into five categories (Wake, NREM 1, NREM 2, NREM 3, REM), detects arousals, detects and classifies breathing events (Obstructive Apnea, Central Apnea, Mixed Apnea, Hypopnea, and RERA), and detects limb movements and categorizes them as periodic or isolated. We tested CAISR against multiple datasets independently annotated by multiple experts, including UPenn (69 subjects, 6 experts), BITS (98 subjects, 3 experts), and Stanford (100 subjects, three experts). Sleep staging and arousal detection were accomplished using customized deep neural networks, while breathing event detection and classification and limb movement analysis were accomplished using rule-based signal processing approaches. We quantified CAISR performance with three metrics: Cohen's Kappa, area under the receiver operating characteristic curve (AUROC), and area under the precision-recall curve (AUPRC). To determine whether CAISR performed on par with human experts, we compared expert inter-rater reliability (IRR) with algorithm-expert IRR. The CAISR model showed strong overall performance across the four tasks: sleep staging, arousal detection, apnea detection, and limb movement detection. In sleep staging, the model achieved AUROC values ranging from 0.82 to 0.97 and AUPRC values between 0.63 and 0.90 across the BITS, Stanford, and Penn datasets, indicating high classification accuracy. The Kappa agreement analysis showed that in the BITS and Stanford datasets, CAISR outperformed human experts, with non-overlapping confidence intervals indicating superiority (Kappa values around 0.7 to 0.8 for CAISR vs. experts). In the Penn dataset, the model's performance was comparable to experts, with overlapping confidence intervals suggesting non-inferiority. For arousal detection, the model maintained reliable performance, with AUROC values ranging from 0.83 to 0.94 and AUPRC values from 0.67 to 0.85, and Kappa analysis showing overlapping confidence intervals, indicating comparable performance to experts in both the BITS and Stanford datasets (Kappa values for CAISR around 0.6 to 0.75). In apnea detection, including the detection of obstructive, central, and mixed apnea, the CAISR model achieved competitive results in the BITS dataset with AUROC values between 0.81 and 0.95 and AUPRC values between 0.58 and 0.82, but in the Stanford dataset, it underperformed compared to human experts, as shown by non-overlapping confidence intervals and lower Kappa values (around 0.55 to 0.65). Finally, in limb movement detection, the model demonstrated superior performance in the BITS dataset, with AUROC values of 0.9 to 0.96 and AUPRC values between 0.75 and 0.85, and Kappa analysis indicating significantly higher reliability compared to experts (CAISR Kappa around 0.8, with non-overlapping confidence intervals). In the Stanford dataset, CAISR's performance was comparable to experts, with overlapping confidence intervals suggesting non-inferiority (Kappa values around 0.65 to 0.7). Overall, the CAISR model consistently exhibited high classification performance and reliability across tasks, often matching or surpassing expert-level performance, with particularly strong results in sleep staging and limb detection. The CAISR model demonstrated high classification accuracy and reliability across sleep staging, arousal, apnea, and limb movement detection tasks, matching or surpassing human expert performance. Human errors and systematic biases in the annotation of micro-events during sleep, such as arousal and apnea detection, likely contributed to variability in expert performance, while the CAISR model showed more consistent results, reducing the impact of these biases and increasing overall reliability across task.

Abstract Introduction The PAP-NAP, a daytime abbreviated sleep study, is a tool designed to improve positive airway pressure (PAP) therapy use in patients with sleep-disordered breathing. We present a case where a PAP-NAP study was utilized to determine appropriate therapy in a complex sleep patient with persistent high residual apnea hypopnea index (AHI). Report of case A 54-year-old obese male with history of chronic pain and depression was diagnosed with severe obstructive sleep apnea (OSA) (AHI 90/h) in 2010 via a polysomnogram and titrated to CPAP 9 cm H2O with improvement in symptoms. He became noncompliant in 2014 and reinitiated therapy in 2018 with persistent snoring and fatigue. Repeat sleep study resulted in a CPAP prescription of 18 cm H2O with excellent compliance, minimal leak and residual AHI of 9/hr. The patient was diagnosed with tonsillar cancer in March 2024 requiring opioids for pain. Despite significant weight loss (BMI fell from baseline of 40 to 28), he required 11+ hours of sleep with high residual AHI of 17.2/hr and HCO3 of 31.5 (previously normal). CPAP was transitioned to APAP 16-20 cm H2O with 90th centile pressure of 19 cm H20 and high AHI. The patient underwent a bilevel titration study notable for minimal sleep and severe central and mixed sleep apnea. Given need for continued opioids, and patient resistance to repeat sleep study, decision was made to conduct a PAP-NAP in conjunction with arterial blood gas (ABG) to determine ideal therapy for patient - adaptive servo-ventilation (ASV) versus bilevel. ABG showed a metabolic alkalosis with normal paCO2. PAP-NAP showed excellent response to ASV-Auto with resolution of obstructive and central sleep apnea. At one month the patient demonstrated excellent compliance, with a residual AHI of 8/hr and improvement in daytime sleepiness. Conclusion Our patient was complex due to a history of severe OSA with emergence of severe central sleep apnea after weight loss and opioid use in the setting of new malignancy. He underwent several PSG titration studies, and declined an additional overnight study. PAP-NAP was the key to optimizing PAP therapy and improving his daytime symptoms. Support (if any)

Abstract Introduction Sleep disordered breathing(SDB) is common in patients with heart failure(CHF) and is subtyped into obstructive (OSA) and central sleep apnea(CSA). Based on prior studies,CSA occurs in 25-40% of patients with CHF with reduced ejection fraction (HFrEF). With the implementation of quadruple therapy for management of HFrEF in the recent years, we aim to understand the current prevalence of CSA in our hospitalized patients both with stable and decompensated HFrEF as well as compare outcomes data. Methods Through a retrospective review of patients from 09/2019-12/2023 in a hospital-based sleep medicine program registry. patients admitted with a history of HFrEF, who underwent inpatient Apnea link followed by outpatient polysomnography (PSG) were reviewed. Patients were subdivided into those admitted with stable HFrEF and decompensated HFrEF. Data on in-hospital AHI, time spent&amp;lt; 88% (T88), PSG AHI, sleep apnea type, medications and outcomes data were compared. Results Of the 77 HFrEF pts on whom complete data on inpatient screening and post-discharge PSG was available, 50 had decompensated and 27 were stable HFrEF. Mean BMI was 35.3 ±11.8 vs 35.2 ± 9.2 while mean EF was 27 ± 11 vs 32.5 ± 9.7. Interestingly, apnea link AHI was lower in the decompensated group compared to the outpatient PSG AHI (27.6 ±18.4 vs 34.5 ±27.5) though it was the opposite for stable HFrEF (34.5 ±26.7 vs 23 ±21.65). T88 was 76.3 ± 91.8 vs 73.6 ±109.3 min in decompensated patients and 65.9 ± 78.5 vs 59.5 ± 97.5 min in stable patients, with the former group desaturating more. The prevalence of CSA was notably low (6%,11%) with predominance of OSA (68% and 55%), mixed sleep apnea(8% and 11%). Quadruple therapy was prescribed more in the decompensated group, which also had higher 180-day ED and hospital readmissions (21/30 and 26/31) and mortality (12/50 vs 3/27). Conclusion The incidence of CSA for HFrEF was significantly lower compared to prior studies in ambulatory settings. This could be due to availability of better therapy. The decompensated group was observed to have worse AHI on PSG than with in-hospital portable sleep study as well as high 180-day ED and hospital re-admission and mortality. Support (if any)

Down syndrome (DS) is a genetic disease caused by a third copy of chromosome 21, leading to various physical features, developmental and cognitive delays, and intellectual disability. Obstructive sleep apnea (OSA) is highly prevalent in children with DS, with severity reported to be inversely related to age and culminating in neonates. OSA causes intermittent hypoxia and hypercapnia, which may have detrimental effects on health and development. Consequently, there are concerns about the impact of OSA on neurodevelopmental disorders associated with DS, particularly in neonates. Dp(16)1Yey mice, a genetically engineered model of DS, exhibit cognitive impairments and characteristics typically associated with OSA, including craniofacial hypoplasia and reduced upper airway volume in adulthood. To investigate the contribution of respiratory-related disorders to DS pathophysiology, we examined the cardio-respiratory phenotype of Dp(16)1Yey mice at birth, with special attention to OSA, using a pneumotachograph and a facemask combined with a laser abdominal profilometer to distinguish obstructive, central, and mixed apneas. Dp(16)1Yey mouse pups exhibited lower weight and heart rates compared to their wild-type counterparts. Baseline breathing variables and responses to hypercapnia were similar between the two groups. Obstructive apneas were observed in both Dp(16)1Yey and wild-type mice, but the total time spent in obstructive apneas was longer in Dp(16)1Yey mice, due to their longer mean duration. These findings highlight the relevance of the Dp(16)1Yey model for studying OSA in DS during the neonatal period and for investigating the contribution of early respiratory disorders to DS pathology.NEW & NOTEWORTHY Severe obstructive sleep apnea is prevalent in neonates with Down syndrome, but neonatal breathing disorders remain unexplored in mouse models. Using the Dp(16)1Yey model, we observed prolonged obstructive apneas and lower heart rates at birth in mutant pups compared to wild-type littermates. This preclinical model provides a novel platform to study neonatal obstructive sleep apnea in Down syndrome and its contribution to neurodevelopmental disorders associated with Down syndrome.

PurposeOur aim in this study is to investigate the significance and implications of different clinical subtypes of patients with obstructive sleep apnea syndrome (OSAS) in three different sleep centers from varied provinces.MethodsBetween January 2023 and November 2024, 330 patients from three sleep centers (Adana, Gaziantep, and Istanbul) were retrospectively examined for age, gender, body mass index (BMI), polysomnography parameters, sleep stages, arousals, oxygen parameters, heart rates, apnea-hypopnea indexes (AHI) and snoring.ResultsOSAS patients of Gaziantep were fat and severe OSAS patients who slept lightly but efficiently at lower oxygen levels with longer durations. They fell into Rapid Eye Movement (REM) sleep quickly. The number of hypopneas is high. OSAS patients of Adana sleep deeply, frequently wake after sleep onset, and snore less. The number of obstructive apnea is high. OSAS patients of Istanbul sleep efficiently but snore a lot. REM oxygen saturation, oxygen desaturation index (ODI) levels, and the average heart rate were high in Istanbul. The number of central and mixed apneas is high.ConclusionsSleep patterns and oxygen measurements varied among clinical subtypes of patients with OSAS, as well as among provinces. Understanding regional or subtype-specific OSAS could alter practice because treatment can be planned according to the severity of OSAS.

Determine the appropriate duration for multichannel sleep studies in former preterm infants with cardio-respiratory events beyond term equivalent age. A sleep study of 10 h will provide equivalent information compared to a 20-h study to detect significant cardio-respiratory abnormalities in this population. Single-center retrospective study of 50 infants with 20-h sleep study. Studies were evaluated for periodic breathing, obstructive, central, mixed apnea, desaturations, and bradycardia. Each study was partitioned into two 10-h epochs, compared to one another and the 20-h study. Differences were detected at the level of individual sleep studies when each epoch was compared to each other and a total 20-h study. 10-h study missed 17-31% of breathing abnormalities detected over 20 h adjusted for study time. Group analysis showed no statistical difference in the number and duration of events between epochs. A 20-h sleep study improves the detection of breathing abnormalities missed with a 10-h study.

Tonsillectomy, performed with or without adenoidectomy, involves the complete removal of the tonsils and has long been a cornerstone in the management of obstructive sleep apnea (OSA) and related sleep-disordered breathing conditions. Sleep apnea is classified into obstructive, central, or mixed types, with mixed apnea combining obstructive and central features, often linked to severe OSA. Sleep apnea is associated with various risk factors and leads to significant consequences, including cardiovascular morbidity, neurobehavioral deficits, increased healthcare utilization, and reduced quality of life. A primary contributing factor, particularly in pediatric OSA, is the proliferation of the adenoids and tonsils, resulting in upper airway obstruction during sleep. Adenotonsillectomy is an established first-line treatment for pediatric OSA, effectively improving apnea indices and quality of life, though residual central sleep apnea may persist in some cases. In adults, tonsillectomy reduces apnea severity; however, its effectiveness is influenced by factors such as body mass index. The impact of tonsillectomy on the quality of life of adults with sleep apnea remains underexplored. This review aims to assess the impact of tonsillectomy on various types of sleep apnea in both children and adults, while identifying gaps in current research and future directions. Further studies are needed to investigate the long-term outcomes of surgical interventions and the role of obesity in determining surgical success, to optimize diagnostic, therapeutic, and management strategies for sleep apnea across diverse populations.

Abstract Introduction AASM recommends the use of nasal pressure (NP), oronasal thermal flow (Th), and respiratory inductance plethysmography (RIP) for detecting and characterising respiratory events (RE) in polysomnography. A previous comparative study assessed utility of Noxturnal RIP flow (cRIPflow) as an alternative to Th for identification of RE in polysomnography. This demonstrated that cRIPflow was comparable with AASM recommendation for Th and NP (TH-NP) and indicated higher accuracy than Th in RE identification. We further investigate utility of cRIPflow between varying groups of apnoea hypopnoea index (AHI) severity. Method Respiratory scoring was performed by an experienced scorer on 10 diagnostic studies under AASM standards. Scoring was repeated using three different measurements for each study: cRIPflow only, Th only and Th-NP. AHI, central apnoea index (CAI), obstructive apnoea index (OAI), mixed apnoea index (MAI) and hypopnoea index (HI) were calculated. Data was catagorised into Group1 (AHI &amp;lt;30/hr) and Group2 (AHI &amp;gt;30/hr). Wilcoxon matched pairs test was utilised for comparison between flow measurements. Results Statistical difference found in Group1 (n=6) HI comparing cRIPflow vsTh (cRIPflow 6.08/hr+/-5.87SD, Th 4.57/hr+/-4.27SD, p=0.0312). No other statistical differences in RE identified when comparing cRIPflow vsTh, cRIPflow vs Th-NP and Th vs Th-NP within Group1 (n=6) and Group2 (n=4). Discussion This data suggests cRIPflow may be more sensitive in HI identification in lower severity AHI populations. Analysis with larger sample size would provide more insight. cRIPflow is comparative with AASM recommended flow sensors across varying AHI severity populations, suggesting an alternative method for detecting and characterising RE in polysomnography.

Obstructive sleep apnea is a common sleep-related breathing disorder. Although maxillomandibular advancement is widely recognized for its proven effectiveness, there are still uncertainties surrounding this procedure. This research therefore focused on the indication, surgical techniques, and outcomes of maxillomandibular advancement in patients with obstructive sleep apnea. A systematic review and meta-analysis showed that maxillomandibular advancement is more effective than multilevel surgery for the treatment of obstructive sleep apnea. Both maxillomandibular advancement and hypoglossal nerve stimulation were identified as effective and safe treatment methods for obstructive sleep apnea. Various retrospective studies also indicated that patients with hypopnea-dominant obstructive sleep apnea are better candidates for maxillomandibular advancement, in contrast to patients with cardiovascular diseases or a higher central apnea index. Furthermore, it was demonstrated that maxillomandibular advancement is effective in patients with a high percentage of central and mixed apneas, despite the potential surgical inaccuracies of maxillomandibular advancement, highlighting the broad applicability of this treatment method.

To explore the association between the severity of sleep-disordered breathing, different types of respiratory events, peripheral oxygen saturation (SpO2), age and sleep stage on cerebral oxygen saturation (rSO2) in children. We enrolled children aged 4-14 years who were treated for snoring or mouth breathing at the Sleep Center of Beijing Children's Hospital, from February 2022 to July 2022. All children completed polysomnography, and SpO2, rSO2, and heart rate (HR) were recorded synchronously. A total of 70 children were included, including 16 (22.9%) with primary snoring, 38 (54.3%) with mild obstructive sleep apnea (OSA), and 16 (22.9%) with moderate-to-severe OSA. There were no significant differences in the mean rSO2 or minimum rSO2 among the primary snoring, mild OSA, and moderate-to-severe OSA groups (all p > 0.05). A total of 1119 respiratory events were included in the analysis. Regardless of the type of respiratory event, rSO2 and HR changes occur prior to fluctuations in SpO2. A mixed-effects model showed that ΔrSO2 was positively correlated with ΔSpO2, duration of respiratory event, mixed and obstructive apnea, central apnea, while negatively correlated with age and rapid eye movement (REM) sleep stage (all p < 0.05). Larger rSO2 fluctuations were impacted by a greater ΔSpO2, longer duration of respiratory events, younger age, apnea-related respiratory events and non-REM sleep stage. Thus, sleep disordered breathing in younger children warrants more attention. More research is needed to determine whether REM sleep has special protective effects on rSO2.

To explore the differences and associations of hypoxic parameters among distinct types of respiratory events in patients with obstructive sleep apnea (OSA) and to construct prediction models for the types of respiratory events based on hypoxic parameters. A retrospective analysis was conducted on a cohort of 67 patients with polysomnography (PSG). All overnight recorded respiratory events with pulse oxygen saturation (SpO2) desaturation were categorized into four categories: hypopnea (Hyp, 3409 events), obstructive apnea (OA, 5561 events), central apnea (CA, 1110 events) and mixed apnea (MA, 1372 events). All event recordings were exported separately from the PSG software as comma-separated variable (.csv) files, which were imported into custom-built MATLAB software for analysis. Based on 13 hypoxic parameters, artificial neural network (ANN) and binary logistic regression (BLR) were separately used for construction of Hyp, OA, CA and MA models. Receiver operating characteristic (ROC) curves were employed to compare the various predictive indicators of the two models for different respiratory event types, respectively. Both ANN and BLR models suggested that 13 hypoxic parameters significantly influenced the classification of respiratory event types; The area under the ROC curves of the ANN models surpassed those of traditional BLR models respiratory event types. The ANN models constructed based on the 13 hypoxic parameters exhibited superior predictive capabilities for distinct types of respiratory events, providing a feasible new tool for automatic identification of respiratory event types using sleep SpO2.

PurposePhrenic nerve stimulation (PNS) was approved by the Food and Drug Administration (FDA) to treat moderate to severe central sleep apnea. We report here, results of a retrospective study regarding our institutional outcomes at one year. In this study we evaluated the change in the apnea hypopnea index, epworth sleepiness score, and functional outcomes of sleep score at one year post implant.MethodsThis is a retrospective analysis of patients ≥ 18 years of age who had PNS implanted for moderate to severe CSA at the Ohio State University Wexner Medical Center apnea between Feb 1, 2018 to July 1, 2021. Sleep disordered breathing parameters and objective sleepiness as measured by the Epworth Sleepiness Scale (ESS) scores, and Functional Outcomes of Sleep Questionnaire (FOSQ) scores were assessed at baseline and one-year post-implant.ResultsTwenty-two patients were implanted with PNS at OSU between February 1, 2018 and May, 31, 2022. The AHI showed a statistically significant decrease from a median of 40 events/hour at baseline to 18 at follow-up (p-value = 0.003). The CAI decreased from 16 events/hour to 2 events/hour (p-value of 0.001). The obstructive apnea index, mixed apnea index, and hypopnea index did not significantly change. The ESS scores had a statistically significant improvement from a median score of 12 to 9 (p-value = 0.028). While the FOSQ showed a trend to improvement from 15.0 to 17.8, it was not statistically significant (p-value of 0.086).ConclusionOur study found that PNS therapy for moderate to severe CSA improves overall AHI and CAI. Objective sleepiness as measured by the ESS also improved at one-year post implant.

Abstract Introduction Accurate identification of apnea types is crucial for effective diagnosis and management of sleep-disordered breathing. The Belun Sleep System (BLS-100, a.k.a., Belun Ring) is an FDA-cleared home sleep apnea testing system (K222579) comprising an adjustable ring-shaped wearable, a cradle, and two deep learning-powered algorithms. The Belun Cor, a novel subxiphoid sensor equipped with accelerometry, can detect respiratory effort, respiratory rate, body position, and facilitates the detection of central events. This preliminary analysis aims to assess the performance of the integrated BLS-100 in detecting apnea events containing central components. Methods This interim analysis evaluated the performance of BLS-100 in a clinical cohort of hospitalized patients admitted for acute ischemic stroke. Eligible patients underwent in-lab polysomnography (PSG) alongside concurrent BLS-100 testing. PSG scoring adhered to the latest AASM scoring manual, with scoring technicians blinded to the BLS-100 results. The BLS-100 derived total sleep time (bTST), sleep stages (bSTAGE), apnea-hypopnea index (bAHI), and combined central and mixed apnea index (bCMAI). Results As of 12/17/2023, 25 consecutive Taiwanese patients were enrolled. Four patients were excluded due to short bTST&amp;lt; 120 mins. The analysis was conducted on 21 patients. M:F 19:2; age 59.7; PSG TST 270 ± 61.9 mins; PSG AHI 27.0 (1.4-81.9) with 3 normal, 3 mild, 7 moderate, and 8 severe OSA cases. The mean PSG central apnea index (PSG-CAI) was 4.8 (0.0-34.0), with 5 patients having PSG-CAI≥5. The mean PSG central and mixed apnea index (PSG-CMAI) was 8.4 (0.0-47.3). Pearson correlation coefficients between PSG-CAI and bCMAI, as well as PSG-CMAI and bCMAI, were 0.939 (P&amp;lt; 0.001) and 0.982 (P&amp;lt; 0.001), respectively. Using bCMAI≥5 to predict PSG-CAI≥5, the accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Cohen’s Kappa were 0.81, 1.00, 0.75, 0.56, 1.00, and 0.59, respectively. Similarly, using bCMAI≥5 to predict PSG-CMAI≥5, the corresponding values were 0.86, 0.88, 0.85, 0.78, 0.92, and 0.70, respectively. Conclusion Early findings indicate that the BLS-100 with Belun Cor shows promising performance in identifying apnea events that include central components. An elevated bCMAI serves as a valuable indicator for clinicians, signaling the presence of central or mixed apneas. Support (if any) Case Western Reserve University-Taipei Medical University Pilot Award