BACKGROUND: 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.
METHODS: 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.
RESULTS: 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).
CONCLUSIONS: ODI, as the only polysomnography parameter, emerged as an independent predictor of mortality in OSA patients.

BACKGROUND: In certain situations, masks are worn during sleep to prevent respiratory infections. However, the effects of mask wearing on cardiopulmonary function during sleep are unknown. This study aimed to determine whether wearing masks during sleep has an impact on cardiopulmonary function, including in patients with obstructive sleep apnea.
METHODS: This was a prospective, randomized crossover-controlled trial. The effects of wearing surgical masks or N95 respirators on cardiopulmonary function were measured in healthy subjects and patients with mild-moderate obstructive sleep apnea. Sleep breathing parameters were monitored during nocturnal sleep using a sleep monitor, and subjective feelings about mask wearing were assessed using a questionnaire.
RESULTS: Wearing masks during sleep at night did not significantly impact sleep breathing parameters. Furthermore, there were no significant differences in heart rate, blood oxygenation, and blood pressure before and after wearing masks. However, wearing masks wearing, especially the N95 mask, had an adverse impact on sleep quality, and masks were found to be subjectively uncomfortable.
CONCLUSIONS: Wearing masks during sleep at night does not adversely affect cardiopulmonary function but they can be uncomfortable, especially the N95 mask. Thus, in circumstances where wearing N95 masks during nocturnal sleep proves intolerable, we recommend the use of surgical masks as a more comfortable alternative.

Sleep apnea is a common sleep disorder. The availability of an easy-to-use sleep apnea predictor would provide a public health benefit by promoting early diagnosis and treatment. Our goal was to develop a prediction tool that used commonly available variables and was accessible to the public through a web site. Using data from polysomnography (PSG) studies that measured the apnea-hypopnea index (AHI), we built a machine learning tool to predict the presence of moderate to severe obstructive sleep apnea (OSA) (defined as AHI ≥15). Our tool employs only seven widely available predictor variables: age, sex, weight, height, pulse oxygen saturation, heart rate and respiratory rate. As a preliminary step, we used 16,958 PSG studies to examine eight machine learning algorithms via five-fold cross validation and determined that XGBoost exhibited superior predictive performance. We then refined the XGBoost predictor by randomly partitioning the data into a training and a test set (13,566 and 3392 PSGs, respectively) and repeatedly subsampling from the training set to construct 1000 training subsets. We evaluated each of the resulting 1000 XGBoost models on the single set-aside test set. The resulting classification tool correctly identified 72.5 % of those with moderate to severe OSA as having the condition (sensitivity) and 62.8 % of those without moderate to-severe OSA as not having it (specificity); overall accuracy was 66 %. We developed a user-friendly publicly available website (https://manticore.niehs.nih.gov/OSApredictor). We hope that our easy-to-use tool will serve as a screening vehicle that enables more patients to be clinically diagnosed and treated for OSA.

OSA is diagnosed and managed by a metric called the apnea-hypopnea index (AHI). The AHI quantifies the number of respiratory events (apnea or hypopnea), disregarding important information on the characteristics and physiological consequences of respiratory events, including degrees of ventilatory deficit and associated hypoxemia, cardiac autonomic response, and cortical activity. The oversimplification of the disorder by the AHI is considered one of the reasons for divergent findings on the associations of OSA and cardiovascular disease (CVD) in observational and randomized controlled trial studies. Prospective observational cohort studies have demonstrated strong associations of OSA with several cardiovascular diseases, and randomized controlled trials of CPAP intervention have not been able to detect a benefit of CPAP to reduce the risk of CVD. Over the last several years, novel methodologies have been proposed to better quantify the magnitude of OSA-related breathing disturbance and its physiological consequences. As a result, stronger associations with cardiovascular and neurocognitive outcomes have been observed. In this review, we focus on the methods that capture polysomnographic heterogeneity of OSA.

Obstructive sleep apnea (OSA) is a chronic disorder characterized by recurrent episodes of upper airway collapse during sleep, which can lead to serious health issues like cardiovascular disease and neurocognitive impairments. While positive airway pressure serves as the standard treatment, intolerance in some individuals necessitates exploration of alternative therapies. Hypoglossal nerve stimulation (HGNS) promises to mitigate OSA morbidity by stimulating the tongue muscles to maintain airway patency. However, its effectiveness varies, prompting research for optimization. This review summarizes the effects of HGNS on upper airway obstruction from human and animal studies. It examines physiological responses including critical closing pressure, maximal airflow, nasal and upper airway resistance, compliance, stiffness, and geometry. Interactions among these parameters and discrepant findings in animal and human studies are explored. Additionally, the review summarizes the impact of HGNS on established OSA metrics, such as the apnea-hypopnea index, oxygen desaturation index, and sleep arousals. Various therapeutic modalities, including selective unilateral or bilateral HGNS, targeted unilateral HGNS, and whole unilateral or bilateral HGNS, are discussed. This review consolidates our understanding of HGNS mechanisms, fostering exploration of under-investigated outcomes and approaches to drive advancements in HGNS therapy.

UNASSIGNED: The aim of this study was to evaluate the safety and efficacy of microdebrider adenoidectomy on sleep-disordered breathing among pediatric patients with OSA.
UNASSIGNED: In the microdebrider group (Group I), there were 30 Japanese OSA patients consisting of 26 boys and 4 girls. For comparison, we had 15 children (13 boys and 2 girls) who underwent classical adenoidectomy (Group II). Patients in Group I were selected from a pool of 95 pediatric Japanese OSA patients and were matched by age, preoperative AHI, and Kaup index with those in Group II.Parameters such as the amount of residual adenoid tissue, bleeding, duration of the procedure, and sleep-related metrics were compared between the two groups.
UNASSIGNED: A significant improvement in postoperative AHI was observed in Group I (p<0.05). The prevalence of AHI <1 was significantly higher in Group I compared with Group II (p<0.05). Additionally, the amount of postoperative residual adenoid was significantly less in Group I (3/30 of Grade 3 and 4 adenoid size) than in Group II (7/15, p<0.05). Furthermore, a reduction in postoperative AHI was proportionally associated with a decrease in residual adenoid.
UNASSIGNED: The newly developed microdebrider adenoidectomy technique for pediatric OSA patients with adenotonsillar hypertrophy demonstrated greater accuracy and efficacy in ameliorating sleep apnea symptoms compared with the standard adenoidectomy approach.

The purpose of this study was to evaluate changes in mandibular position during midface distraction. Midface distraction was performed in patients with syndromic craniosynostosis to increase upper airway volume. Although this treatment resulted in changes in occlusion, the concomitant changes in mandibular position were poorly understood. In this retrospective study, three-dimensional (3D) cephalograms were obtained before and after midface distraction in 15 patients with syndromic craniosynostosis. Perioperative polysomnography scores and changes in maxillary and mandibular position, mandibular volume, and upper airway volume were analyzed. Results showed a significant improvement in apnea-hypopnea index (AHI) (from 20.6 ± 21.3 to 6.9 ± 5.1, p < 0.05) and upper airway volume (from 2951.65 ± 2286.38 to 5218.04 ± 3150.05 mm3, p < 0.001). When the lowest point of the sella turcica was set as the reference point, the mandible moved significantly in an anterior direction (from 47.9 ± 11.5 to 51.9 ± 9.8 mm, p < 0.05). Mandibular volume did not change significantly perioperatively (from 32530.19 ± 10726.01 to 35590.50 ± 14879.21 mm3, p = 0.10). There were positive correlations between the rates of improvement in AHI and the amount of mandibular movement in the anterior and inferior directions (both p < 0.05). Within the limitations of the study, it seems that the mandible moved in the anterior-inferior direction after midface distraction, and the amount of movement correlated with improvement in respiratory function. Therefore, it is important to consider the position of the mandible when determining the direction of midface distraction, as it may influence the therapeutic effect.

OBJECTIVE: This study aimed to explore the association between anti-mullerian hormone (AMH) levels and obstructive sleep apnea (OSA) severity.
METHODS: A cross-sectional design was employed to evaluate AMH levels in 68 premenopausal women diagnosed with OSA at Van Yüzüncü Yıl University Faculty of Medicine. OSA severity was scored according to the 2018 AASM guidelines using a 16-channel Embla device. AMH levels were measured from blood samples using a commercially available kit.
RESULTS: The study found that AMH levels in OSA patients were significantly lower than those in the healthy control group. A statistically significant negative correlation between AMH and AHI levels was observed. When stratified by OSA severity, the lowest AMH levels were found in the severe OSA group.
CONCLUSIONS: OSA may have potential endocrine implications, especially concerning reproductive health. Decreased AMH levels in OSA patients could indicate future risks of infertility or early menopause.

OBJECTIVE: The objective of this study was to assess the accuracy of automatic diagnosis of obstructive sleep apnea (OSA) with a new, small, acoustic-based, wearable technology (AcuPebble SA100), by comparing it with standard type 1 polysomnography (PSG) diagnosis.
METHODS: This observational, prospective study was carried out in a Spanish hospital sleep apnea center. Consecutive subjects who had been referred to the hospital following primary care suspicion of OSA were recruited and underwent in-laboratory attended PSG, together with the AcuPebble SA100 device simultaneously overnight from January to December 2022.
RESULTS: A total of 80 patients were recruited for the trial. The patients had a median Epworth scoring of 10, a mean of 10.4, and a range of 0-24. The mean AHI obtained with PSG plus sleep clinician marking was 23.2, median 14.3 and range 0-108. The study demonstrated a diagnostic accuracy (based on AHI) of 95.24%, sensitivity of 92.86%, specificity of 97.14%, positive predictive value of 96.30%, negative predictive value of 94.44%, positive likelihood ratio of 32.50 and negative likelihood ratio of 0.07.
CONCLUSIONS: The AcuPebble SA100 (EU) device has demonstrated an accurate automated diagnosis of OSA in patients undergoing in-clinic sleep testing when compared against the gold-standard reference of in-clinic PSG.

Background and Objectives: The Baveno classification represents a new approach to the assessment of the severity of OSA (Obstructive sleep apnea), which takes significant comorbidities into account: atrial fibrillation, arterial hypertension, heart failure, stroke, diabetes mellitus, and OSA symptoms expressed through the Epworth sleepiness scale (ESS). The authors believe that the Baveno classification facilitates a better stratification of patients with OSA and can be a good guide for deciding on the therapeutic approach and clinical monitoring of patients with OSA, compared to the AHI (apnea-hypopnea index) itself. The aim of this paper is to confirm the advantage of applying the Baveno classification to the evaluation of symptoms of anxiety and depression in the OSA patients compared to the application of the AHI as a single parameter. Materials and Methods: This research represents an observational retrospective study that was performed at the Pulmonology Clinic of the University Clinical Center in Kragujevac, Serbia. The study sample included 104 patients with diagnosed OSA. Patients were divided into four categories retrogradely according to the Baveno classification (A, B, C, and D). Statistical data processing was performed using the IBM SPSS Statistics version 25.0 program. Results: In our study, we proved that the Baveno classification is better at predicting the depressive disorder in OSA patients compared to the AHI itself, according to abnormal BDI-II (Beck Depression Inventory) score (value greater than ten) and HADS-D (Hospital anxiety and depression) scale (value greater than eight). The average AHI in the entire group of examined patients was 44.3 ± 19.8, while in category A the average AHI was 25.2 ± 10, in category B, 53.4 ± 20.6; in category C, 38.2 ± 18.5; and in category D, 48.1 ± 19.2. In the total sample, AHI did not correlate with the depressive episodes, but individually, the highest frequency of the depressive symptoms was precisely in the categories with the highest AHI (group D and B), where more than half of the subjects had an abnormal score. The frequency of the anxiety disorder (HADS-A) between the analyzed groups did not differ significantly, although the largest number of patients with significant anxiety were in category B, according to the Baveno classification. Conclusions: We proved that the Baveno classification is applicable in real life, and it is better at evaluating anxiety and depression using questionnaires and can identify new patients who need CPAP therapy, independently of other OSAS symptoms, primarily daytime sleepiness.