Determinants of Slow-Wave Activity in Overweight and Obese Adults: Roles of Sex, Obstructive Sleep Apnea and Testosterone Levels

Screening for sleep apnoea risk in testosterone-treated transgender men

Introduction

Obstructive sleep apnoea (OSA) is more prevalent in men. Several studies suggested that higher testosterone levels were associated with a greater risk of OSA. We aimed to determine whether testosterone administration in transgender men would accentuate symptoms of OSA.

Methods

The study involved 94 adult people undergoing a female-to-male transition with testosterone administration. The participants answered the Berlin Questionnaire (BQ) and a separate question on snoring before starting testosterone treatment and after at least 1 year of being on testosterone treatment.

Results

A higher proportion of participants at the follow-up answered positively to the first category of BQ devoted to snoring. A lower proportion of participants at follow-up answered positively to the second category of BQ devoted to tiredness. The percentage of subjects with a high risk of sleep apnoea, according to BQ, and of those who answered the question on snoring positively did not change significantly.

Conclusion

An increased number of transgender men who reported snoring in BQ after testosterone administration indicate a higher risk of OSA development.

REM-OSA as a Tool to Understand Both the Architecture of Sleep and Pathogenesis of Sleep Apnea-Literature Review

Sleep is a complex physiological state, which can be divided into the non-rapid eye movement (NREM) phase and the REM phase. Both have some unique features and functions. This difference is best visible in electroencephalography recordings, respiratory system activity, arousals, autonomic nervous system activity, or metabolism. Obstructive sleep apnea (OSA) is a common condition characterized by recurrent episodes of pauses in breathing during sleep caused by blockage of the upper airways. This common condition has multifactorial ethiopathogenesis (e.g., anatomical predisposition, sex, obesity, and age). Within this heterogenous syndrome, some distinctive phenotypes sharing similar clinical features can be recognized, one of them being REM sleep predominant OSA (REM-OSA). The aim of this review was to describe the pathomechanism of REM-OSA phenotype, its specific clinical presentation, and its consequences. Available data suggest that in this group of patients, the severity of specific cardiovascular and metabolic complications is increased. Due to the impact of apneas and hypopneas predominance during REM sleep, patients are more prone to develop hypertension or glucose metabolism impairment. Additionally, due to the specific function of REM sleep, which is predominantly fragmented in the REM-OSA, this group presents with decreased neurocognitive performance, reflected in memory deterioration, and mood changes including depression. REM-OSA clinical diagnosis and treatment can alleviate these outcomes, surpassing the traditional treatment and focusing on a more personalized approach, such as using longer therapy of continuous positive airway pressure or oral appliance use.

Nonalcoholic fatty liver disease and obstructive sleep apnea in women with polycystic ovary syndrome

Nonalcoholic fatty liver disease (NAFLD) and obstructive sleep apnea are frequently associated with polycystic ovary syndrome (PCOS) but remain underrecognized. Women with PCOS have a 2-4 times higher risk of NAFLD independent of body mass index than healthy weight-matched controls. Insulin resistance and hyperandrogenemia together play a central role in the pathogenesis of NAFLD. Timely diagnosis of NAFLD is important because its progression can lead to nonalcoholic steatohepatitis and/or advanced liver fibrosis that can eventually result in liver-related mortality. The presence of NAFLD has also been associated with increased risks of type 2 diabetes, cardiovascular events, overall mortality, and extrahepatic cancers. The treatment of NAFLD in PCOS should include lifestyle interventions. Glucagon-like peptide 1 receptor agonists have shown promising results in patients with PCOS and NAFLD, but future randomized trails are needed to confirm this benefit. Likewise, the use of combined oral estrogen-progestin contraceptives may provide a benefit by decreasing hyperandrogenemia. Sleep disordered breathing is common among women with PCOS and is responsible for a number of cardiometabolic derangements. Obstructive sleep apnea is most often found in overweight and obese women with PCOS, but as is the case with NAFLD, its prevalence exceeds that of women who are of similar weight without PCOS. Left untreated, obstructive sleep apnea can precipitate or exacerbate insulin resistance, glucose intolerance, and hypertension.

Alzheimer's disease neuropathology in the hippocampus and brainstem of people with obstructive sleep apnea

Obstructive sleep apnea (OSA) involves intermittent cessations of breathing during sleep. People with OSA can experience memory deficits and have reduced hippocampal volume; these features are also characteristic of Alzheimer's disease (AD), where they are accompanied by neurofibrillary tangles (NFTs) and amyloid beta (Aβ) plaques in the hippocampus and brainstem. We have recently shown reduced hippocampal volume to be related to OSA severity, and although OSA may be a risk factor for AD, the hippocampus and brainstems of clinically verified OSA cases have not yet been examined for NFTs and Aβ plaques. The present study used quantitative immunohistochemistry to investigate postmortem hippocampi of 34 people with OSA (18 females, 16 males; mean age 67 years) and brainstems of 24 people with OSA for the presence of NFTs and Aβ plaques. OSA severity was a significant predictor of Aβ plaque burden in the hippocampus after controlling for age, sex, body mass index (BMI), and continuous positive airway pressure (CPAP) use. OSA severity also predicted NFT burden in the hippocampus, but not after controlling for age. Although 71% of brainstems contained NFTs and 21% contained Aβ plaques, their burdens were not correlated with OSA severity. These results indicate that OSA accounts for some of the "cognitively normal" individuals who have been found to have substantial Aβ burdens, and are currently considered to be at a prodromal stage of AD.

Development of a support vector machine learning and smart phone Internet of Things-based architecture for real-time sleep apnea diagnosis

Background

The breathing disorder obstructive sleep apnea syndrome (OSAS) only occurs while asleep. While polysomnography (PSG) represents the premiere standard for diagnosing OSAS, it is quite costly, complicated to use, and carries a significant delay between testing and diagnosis.

Methods

This work describes a novel architecture and algorithm designed to efficiently diagnose OSAS via the use of smart phones. In our algorithm, features are extracted from the data, specifically blood oxygen saturation as represented by SpO2. These features are used by a support vector machine (SVM) based strategy to create a classification model. The resultant SVM classification model can then be employed to diagnose OSAS. To allow remote diagnosis, we have combined a simple monitoring system with our algorithm. The system allows physiological data to be obtained from a smart phone, the data to be uploaded to the cloud for processing, and finally population of a diagnostic report sent back to the smart phone in real-time.

Results

Our initial evaluation of this algorithm utilizing actual patient data finds its sensitivity, accuracy, and specificity to be 87.6%, 90.2%, and 94.1%, respectively.

Discussion

Our architecture can monitor human physiological readings in real time and give early warning of abnormal physiological parameters. Moreover, after our evaluation, we find 5G technology offers higher bandwidth with lower delays ensuring more effective monitoring. In addition, we evaluate our algorithm utilizing real-world data; the proposed approach has high accuracy, sensitivity, and specific, demonstrating that our approach is very promising.

Conclusions

Experimental results on the apnea data in University College Dublin (UCD) Database have proven the efficiency and effectiveness of our methodology. This work is a pilot project and still under development. There is no clinical validation and no support. In addition, the Internet of Things (IoT) architecture enables real-time monitoring of human physiological parameters, combined with diagnostic algorithms to provide early warning of abnormal data.

Demographic and Socioeconomic Determinants of Body Mass Index in People of Working Age

Obesity is currently the most common metabolic disease, causing numerous health problems and, if untreated, leading to premature mortality. Obesity is a significant issue among people of working age since their ability to work depends directly on their health condition and psychomotor fitness. Demographic and socioeconomic factors have a significant impact on the body weight of people of working age. The aim of this study is to identify relationships between the body mass index and selected demographic and socioeconomic variables in working-age residents of the city of Wrocław, Poland. The study involved 4315 respondents (2206 women and 2109 men) aged 18–64 years from Wrocław. The sample selection was random and purposive, using multilevel stratification. The applied research tool was the authors’ own cross-sectional diagnostic questionnaire of socioeconomic status. Based on the collected data, the respondents’ body weight was categorized according to WHO criteria. The majority of respondents (60%) had a normal body weight, while 40% were categorized as overweight or obese. The difference was statistically significant (p < 0.001). Sex, age, occupational status, marital status, number of people in the household, having a steady source of income, disposable (net) income, and savings were significantly correlated (p < 0.001) with respondents’ body mass index. Public health programs aimed at promoting healthy lifestyle behaviors should be addressed primarily to groups at the highest risk of overweight and obesity.

Weight Loss as the First-Line Therapy in Patients with Severe Obesity and Obstructive Sleep Apnea Syndrome: the Role of Laparoscopic Sleeve Gastrectomy

PURPOSE

The objective of this study is to investigate the effects of laparoscopic sleeve gastrectomy (LSG) on the polysomnographic parameters related to OSAS.

MATERIALS AND METHODS

We conducted this 3-year prospective cohort study in a tertiary care center between December 2016 and December 2019. In total, we enrolled 31 patients with severe obesity who underwent full-night polysomnography (PSG) before LSG. Later, the patients were re-evaluated by full-night PSG 12 months after the surgery.

RESULTS

The mean age of the patients was 44.1 ± 9.6 years. The mean body mass index (BMI) decreased significantly from a mean value of 49.8 ± 8.5 kg/m² at baseline to 33.2 ± 8.2 kg/m² and a percent BMI (%BMI) reduction of 33.8 ± 10.4% and a percent total weight loss (%TWL) of 35.4 ± 10.8% was achieved on the same day of the postsurgical PSG (p < 0.001). There was a remarkable improvement in the AHI (baseline: 36.1 ± 27.1, 12 months after the surgery: 10.3 ± 11.8; difference: 25.8 ± 22.8 events per hour) (p < 0.001). Importantly, there was a decrease in the percentage of non-rapid eye movement (NREM) 2 (p < 0.001), whereas NREM 3 and REM stages witnessed a significant increase (p = 0.001 and p < 0.001, respectively) after the surgery.

CONCLUSION

The results of this study showed that weight loss after LSG yields improvement not only in AHI but also in many polysomnographic parameters such as sleep quality and desaturation indices.