BACKGROUND: Investigating the co-occurrence of obstructive sleep apnea (OSA) and primary aldosteronism (PA) is crucial for understanding their interrelation.
OBJECTIVE: This work aimed to evaluate the prevalence of OSA in individuals diagnosed with PA and to assess the prevalence of PA within the OSA population, with a specific focus on hypertensive individuals.
METHODS: An exhaustive search was performed across PubMed, Embase, CINAHL, Scopus, and Web of Science up to September 2023, without restrictions on language or publication date. Studies were selected based on their focus on the prevalence of OSA in PA patients and vice versa, specifically in hypertensive individuals. Data were extracted using standard guidelines, focusing on patient characteristics, prevalence rates, and other relevant clinical parameters.
RESULTS: Proportional meta-analysis using a random-effects model revealed a 59.8% prevalence of OSA in hypertensive PA patients, with 45.4% exhibiting moderate-to-severe OSA. Meta-regression showed no significant effect of age, sex, body mass index, antihypertensive medication, systolic blood pressure, diastolic blood pressure, or serum potassium on OSA prevalence. However, a significant positive association was found with the glomerular filtration rate (GFR) (P < .001). Subgroup analysis also revealed that a hyperfiltration rate (GFR ≥ 100 mL/min per 1.73 m2) may be associated with a higher prevalence of OSA (71%, P value for interaction < .01). Among hypertensive OSA patients, 11.2% had PA.
CONCLUSIONS: A substantial prevalence of OSA in individuals with PA was identified, demonstrating a complex interplay between these conditions in hypertensive patients. Notably, the prevalence of OSA was significantly associated with kidney hyperfiltration.

OBJECTIVE: Hypoglossal nerve stimulation (HGNS) therapy has historically had strict eligibility requirements including a body mass index (BMI) < 32 kg/m2. However, recent Food and Drug Administration approval expanded indications to a BMI < 40 kg/m2. There is a wide variability in body fat distribution. This study sought to determine if neck circumference is a better surrogate predictive variable for HGNS outcomes than BMI.
METHODS: A retrospective chart review was conducted at a tertiary care center on adults who underwent HGNS implantation by a single surgeon from March 2017 to October 2021. Baseline demographic data including neck circumference, diagnostic sleep studies and post-implantation HGNS titration studies were collected. Linear regression and Spearman\'s Correlation Coefficient (SCC) analysis were utilized to compare neck circumference (NC), percentage of predicted neck circumference (PPNC) and BMI with the apnea-hypopnea index at effective voltage (AHI-v).
RESULTS: This study included 43 patients who were middle aged (61.1 years), predominantly male (76.7%), with severe obstructive sleep apnea (median AHI 35) and mean neck circumference of 15.3 inches. Utilizing the NC and PPNC, positive correlations with AHI-v were observed (p = 0.0033, SCC = .438, and p = 0.0029, SCC = .444). While controlling for BMI, a 1-inch increase in neck circumference was associated with a 35% increase in AHI-v (p = 0.0411).
CONCLUSIONS: A larger neck circumference was independently associated with worse HGNS outcomes. Further research is needed to support and confirm these findings, particularly across sexes.

OBJECTIVE: There is limited knowledge regarding the progression or consistency of symptoms in OSA over time. Our objective was to examine the changes in symptom subtypes and identify predictors over a span of 5 years.
METHODS: Data of 2,643 participants of the Sleep Heart Health Study with complete baseline and 5-year follow-up visits were analyzed. Latent Class Analysis on 14 symptoms at baseline and follow-up determined symptom subtypes. Individuals without OSA (AHI<5) were incorporated as a known class at each time point. Multinomial logistic regression assessed the effect of age, sex, body mass index (BMI) and AHI on specific class transitions.
RESULTS: The sample consisted of 1,408 women (53.8%) and mean (SD) age 62.4 (10.5) years. We identified four OSA symptom subtypes at both baseline and follow-up visits: minimally symptomatic, disturbed sleep, moderately sleepy, and excessively sleepy. Nearly half (44.2%) of the sample transitioned to a different subtype; transitions to moderately sleepy were the most common (77% of all transitions). A five-year older age was associated with a 50% increase in odds to transit from excessively sleepy to moderately sleepy [OR (95% CI: 1.52 (1.17, 1.97)]. Women had 1.97 times higher odds (95% CI: 1.21, 3.18) to transition from moderately sleepy to minimal symptoms. A 5-unit increase in BMI was associated with 2.39 greater odds (95% CI: 1.30, 4.40) to transition from minimal symptoms to excessively sleepy. Changes in AHI did not significantly predict any transitions.
CONCLUSIONS: The symptoms of OSA may fluctuate or remain stable over time. Knowledge of symptom progression in OSA may support clinicians with treatment decisions.

The study of neurological symptoms and signs connected with neoplasms and antitumor therapy is relevant in the context of an increasing prevalence of cancer. The COVID-19 pandemic and social factors have increased the number of patients suffering from insomnia. Sleep disorders is an unfavorable prognostic factor for neoplasms. The review presents risk factors and mechanisms of sleep disturbance, their relationship with inflammation and dysfunction of the immune system in cancer. In particular, dysfunction of the melatonergic system is discussed as a risk factor for the development of insomnia and cancer. The relevance of developing measures aimed at the rehabilitation of patients in order to restore normal sleep, which plays a fundamental role in maintaining a person\'s mental and physical health, is emphasized.
В условиях увеличения распространенности онкологических заболеваний актуально изучение неврологических симптомов и признаков, ассоциированных с новообразованиями и проводимой по поводу них терапии. Пандемия новой коронавирусной инфекции (COVID-19) и социальные факторы способствовали увеличению числа пациентов, страдающих от бессонницы, которая является неблагоприятным прогностическим фактором при новообразованиях. В обзоре представлены факторы риска и механизмы нарушения сна, их связь с воспалением и дисфункцией иммунной системы при онкологических заболеваниях. В частности, обсуждается нарушение функции мелатонинергической системы как фактор риска развития бессонницы и онкологических заболеваний. Подчеркнута актуальность разработки мероприятий, направленных на реабилитацию пациентов с целью восстановления нормального сна, который играет фундаментальную роль в поддержании психического и физического здоровья человека.

OBJECTIVE: Analysis of factors affecting adherence to continuous positive airway pressure (CPAP) therapy in patients with obstructive sleep apnea (OSA).
METHODS: The literature search was carried out using the databases PubMED, Google Scholar, E-library, Cyberleninka for the period 2013-2023 and included reviews and original articles.
RESULTS: The main groups of factors affecting adherence to CPAP therapy in patients with OSA have been established. These include sociodemographic and socioeconomic factors, the severity of OSA and the severity of clinical symptoms, and psychosocial factors. Strategies that can improve adherence were identified (educational technologies for patients, telemedicine technologies, behavioral therapy, modern technical interventions).
CONCLUSIONS: Factors that improve adherence to CPAP therapy are high levels of education and income, more severe OSA forms accompanied by daytime sleepiness, support from the patient\'s spouse and social support. Factors such as low levels of education and income, smoking, symptoms of depression and hypochondria, as well as side-effects worsen adherence to CPAP therapy, including refusal to continue treatment. It should be noted that all the identified factors are very closely associated with each other, so it is necessary to evaluate them comprehensively in each patient with OSA.
UNASSIGNED: Анализ факторов, оказывающих влияние на приверженность неинвазивной вентиляции постоянным положительным давлением воздушного потока во время сна (CPAP-терапия) пациентов с СОАС.
UNASSIGNED: Поиск литературы проводился с помощью поисковых систем PubMed, Google Scholar, eLIBRARY, Киберленинка за период 2013—2023 гг. и включал обзорные и оригинальные статьи.
UNASSIGNED: Установлены основные группы факторов, оказывающих влияние на приверженность CPAP-терапии пациентов с СОАС. К ним относятся социально-демографические и социально-экономические факторы, степень тяжести СОАС и выраженность клинических симптомов, психосоциальные факторы. Выявлены мероприятия, направленные на улучшение приверженности (обучающие технологии для пациентов, телемедицинские технологии, поведенческая терапия, современные технические решения).
UNASSIGNED: Исходя из вышеизложенного, факторами, улучшающими приверженность CPAP-терапии, являются высокие уровни образованности и доходов пациентов, более тяжелые формы СОАС, сопровождающиеся дневной сонливостью, поддержка супруга пациента и социальная поддержка. А такие факторы, как низкие уровни образования и доходов, курение, наличие симптомов депрессии и ипохондрии, а также возникающие побочные эффекты, ухудшают приверженность CPAP-терапии вплоть до отказа от продолжения лечения. Следует отметить, что все выявленные факторы очень тесно взаимосвязаны друг с другом, поэтому необходимо оценивать их комплексно у каждого пациента с СОАС.

OBJECTIVE: To develop and validate machine learning (ML) and deep learning (DL) models using drug-induced sleep endoscopy (DISE) images to predict the therapeutic efficacy of hypoglossal nerve stimulator (HGNS) implantation.
METHODS: Patients who underwent DISE and subsequent HGNS implantation at a tertiary care referral center were included. Six DL models and five ML algorithms were trained on images from the base of tongue (BOT) and velopharynx (VP) from patients classified as responders or non-responders as defined by Sher\'s criteria (50% reduction in apnea-hypopnea index (AHI) and AHI < 15 events/h). Precision, recall, F1 score, and overall accuracy were evaluated as measures of performance.
RESULTS: In total, 25,040 images from 127 patients were included, of which 16,515 (69.3%) were from responders and 8,262 (30.7%) from non-responders. Models trained on the VP dataset had greater overall accuracy when compared to BOT alone and combined VP and BOT image sets, suggesting that VP images contain discriminative features for identifying therapeutic efficacy. The VCG-16 DL model had the best overall performance on the VP image set with high training accuracy (0.833), F1 score (0.78), and recall (0.883). Among ML models, the logistic regression model had the greatest accuracy (0.685) and F1 score (0.813).
CONCLUSIONS: Deep neural networks have potential to predict HGNS therapeutic efficacy using images from DISE, facilitating better patient selection for implantation. Development of multi-institutional data and image sets will allow for development of generalizable predictive models.
METHODS: N/A Laryngoscope, 2024.

UNASSIGNED: Sleep has important effects on breathing and gas exchange that may have negative consequences in patients with chronic obstructive pulmonary disease (COPD). COPD and obstructive sleep apnea (OSA) are highly prevalent and may coexist, which is referred to as the overlap syndrome.
UNASSIGNED: The probability of OSA-COPD overlap represents the balance of protective and promoting factors such as hyperinflation and fluid retention; thus, different clinical COPD phenotypes influence the likelihood of comorbid OSA. The clinical presentation of OSA-COPD overlap is nonspecific, and the diagnosis requires clinical awareness to identify patients needing overnight studies. Both COPD and OSA are associated with a range of overlapping physiological and biological disturbances including hypoxia and inflammation that contribute to cardiovascular comorbidities. The management of OSA-COPD overlap patients differs from those with COPD alone and the survival of overlap patients treated with positive airway pressure (PAP) is superior to those untreated.
UNASSIGNED: The recognition of OSA-COPD overlap has important clinical relevance because of its impact on outcomes and management. Management of the overlap should address both sleep quality and disordered gas exchange. PAP therapy has demonstrated reductions in COPD exacerbations, hospitalizations, healthcare costs and mortality in overlap patients.

Background/Objectives: Polysomnography and cephalometry have been used for studying obstructive sleep apnea (OSA) etiology. The association between craniofacial skeleton and OSA severity remains controversial. To study OSA\'s etiology, cephalometry, fiberoptic pharyngoscopy, polysomnography, and sleep endoscopy have been used; however, airway obstructions cannot be located. Recent research suggested ultrasonography for OSA screening and upper airway obstruction localization. Thus, this study aims to investigate the relationship between specific craniofacial cephalometric and ultrasonic airway parameters in adults at high risk of OSA. Methods: To assess craniofacial structure, lateral cephalograms were taken from thirty-three adults over 18 with a STOP-Bang questionnaire score of three or higher and a waist-to-height ratio (WHtR) of 0.5 or higher. Airway parameters were assessed through submental ultrasound. Results: NSBA correlated with tongue base airspace width, while MP-H correlated with oropharynx, tongue base, and epiglottis airspace width. SNA, SNB, and NSBA correlated with tongue width at the oropharynx. At tongue base, ANB and MP-H correlated with tongue width. SNB and NSBA were associated with deep tissue thickness at the oropharynx, while MP-H correlated with superficial tissue thickness at velum and oropharynx. Conclusions: Cephalometric parameters (SNA, SNB, ANB, NSBA, and MP-H) were correlated with ultrasonic parameters in the velum, oropharynx, tongue base, and epiglottis.

BACKGROUND: Obstructive sleep apnea (OSA) is associated with an increased risk of hypertension, coronary artery disease, heart failure (HF), and atrial fibrillation (AF).
METHODS: A total of 179 patients aged 34-81 years were included in the study. The median age was 63 years (interquartile range: 56-69 years). Of these patients, 105 (58.7%) were men, and 74 (41.3%) were women; there were cases of paroxysmal (n = 99), persistent (n = 64), and permanent AF (n = 16). All patients underwent investigations including respiratory sleep monitoring, echocardiography, and 24 h Holter electrocardiography monitoring. Statistical analyses were performed using IBM SPSS Statistics 26.0.
RESULTS: OSA was detected in 131 (73.2%) patients. In patients with OSA, paroxysmal AF was commonest (n = 65), followed by persistent AF (n = 51) and permanent AF (n = 15). The patients with sleep apnea had increased body mass index (33.6 kg/m2; p = 0.02), waist circumference (114 cm; p < 0.001), and neck circumference (42 cm; p < 0.001) values. HF (OR 2.9; 95% CI: 1.4-5.9; p = 0.004) and type 2 diabetes (OR 3.6; 95% CI: 1.5-8.3; p = 0.001) were more common in patients with AF and OSA. The STOP-BANG scale (AUC = 0.706 ± 0.044; 95% CI: 0.619-0.792; p < 0.001) and the Berlin questionnaire (AUC = 0.699 ± 0.044; 95% CI: 0.614-0.785) had a higher predictive ability for identifying sleep apnea.
CONCLUSIONS: Patients with AF demonstrate a high prevalence of OSA and an increased association with cardiovascular comorbidities. The STOP-BANG scale and the Berlin questionnaire can be used to screen for OSA in patients with AF.

BACKGROUND: Overlap syndrome (OS), the coexistence of chronic obstructive pulmonary disease and obstructive sleep apnea, is frequently characterized by the presence of daytime hypercapnia (pCO2 ≥ 45 mmHg). The aim of this study was to investigate potential differences in anthropometric, sleep and respiratory characteristics between hypercapnic and normocapnic patients with OS.
METHODS: Consecutive patients who underwent polysomnography, pulmonary function testing and arterial blood gases and had been diagnosed with OS were enrolled in the study.
RESULTS: According to pCO2 levels in wakefulness, the patients were divided into group A, consisting of OS patients without hypercapnia (n = 108) or group B, consisting of OS patients with hypercapnia (n = 55). The majority of included patients in both groups were males (n = 92 in group A vs. n = 50 in group B). Group B had increased BMI (p = 0.001), neck (p = 0.017) and waist circumference (p = 0.013), higher scores in Epworth sleepiness scale (ESS) (p = 0.008), increased sleep efficiency (p = 0.033), oxygen desaturation index (p = 0.004) and time with oxyhemoglobin saturation <90% (p = 0.006) than group A. Also, Group B had decreased average and minimum oxyhemoglobin saturation during sleep (p < 0.001). Hypercapnic patients had lower FEV1% (p = 0.003), FVC% (p = 0.004), pO2 and pCO2 (p < 0.001 for both) values compared with normocapnic patients. In binary regression analysis, which assessed various predictors on the likelihood of having hypercapnia, it was found that BMI (OR: 1.313, 95% CI: 1.048-1.646, p = 0.018) and FVC (OR: 0.913, 95% CI: 0.845-0.986, p = 0.020) were the major determinants of hypercapnia in OS patients.
CONCLUSIONS: Hypercapnic OS patients were more obese and sleepy and presented worse respiratory function in wakefulness and sleep hypoxia characteristics compared with normocapnic OS patients.