Coping strategies for obese individuals with obstructive sleep apnea during COVID-19 pandemic: A narrative review

Differentiation Model for Insomnia Disorder and the Respiratory Arousal Threshold Phenotype in Obstructive Sleep Apnea in the Taiwanese Population Based on Oximetry and Anthropometric Features

Insomnia disorder (ID) and obstructive sleep apnea (OSA) with respiratory arousal threshold (ArTH) phenotypes often coexist in patients, presenting similar symptoms. However, the typical diagnosis examinations (in-laboratory polysomnography (lab-PSG) and other alternatives methods may therefore have limited differentiation capacities. Hence, this study established novel models to assist in the classification of ID and low- and high-ArTH OSA. Participants reporting insomnia as their chief complaint were enrolled. Their sleep parameters and body profile were accessed from the lab-PSG database. Based on the definition of low-ArTH OSA and ID, patients were divided into three groups, namely, the ID, low- and high-ArTH OSA groups. Various machine learning approaches, including logistic regression, k-nearest neighbors, naive Bayes, random forest (RF), and support vector machine, were trained using two types of features (Oximetry model, trained with oximetry parameters only; Combined model, trained with oximetry and anthropometric parameters). In the training stage, RF presented the highest cross-validation accuracy in both models compared with the other approaches. In the testing stage, the RF accuracy was 77.53% and 80.06% for the oximetry and combined models, respectively. The established models can be used to differentiate ID, low- and high-ArTH OSA in the population of Taiwan and those with similar craniofacial features.

Natural Dietary and Medicinal Plants with Anti-Obesity Therapeutics Activities for Treatment and Prevention of Obesity during Lock Down and in Post-COVID-19 Era

Overweight and obesity have become global epidemics, especially during the lockdown due to the COVID-19 pandemic. The potential of medicinal plants as a better and safe option in treating obesity and overweight has gained attention in recent years. Obesity and overweight has become a major public health concern, and its incidence rising at an alarming rate. Obesity is one of the major types of metabolic syndrome, resulting in various types of problems such as hypertension, diabetes, dyslipidemia, and excess fat accumulation. The current searching was done by the keywords in main indexing systems including Scopus, PubMed/MEDLINE, the search engine of Google Scholar, and Institute for Scientific Web of Science. The keywords were traditional medicine, health benefits, pharmaceutical science, pomegranate, punicalin, punicalagin, and ellagitannins. Google Scholar was searched manually for possible missing manuscripts, and there was no language restriction in the search. This review was carried out to highlight the importance of medicinal plants which are common in traditional medicinal sciences of different countries, especially Asia to prevent and treatment of obesity and overweight during the global pandemic and the post-COVID-19 era.