The ten countries with the highest population during the pandemic were analyzed for clustering based on the quantitative numbers of COVID-19 and policy plans. The Fuzzy K-Means (FKM) and K-prototype algorithms were used for clustering, and various performance indices such as Partition Coefficient (PC), Partition Entropy (PE), Xie-Beni (XB), and Silhouette Fuzzy (SIL.F) were used for evaluating the clusters. The analysis included variables such as confirmed cases, tests, vaccines, school and workplace closures, event cancellations, gathering restrictions, transport closures, stay-at-home restrictions, international movement restrictions, testing policies, facial coverings, and vaccination policy statuses. PC, PE, XB, and SIL.F indices were used to analyze the performance indices of the clusters. The Elbow method was used to analyze the performance evaluations for the K-prototype. The K-prototype algorithm's performance evaluations were analyzed using the Elbow method, and the optimum number of clusters for both methods was found to be two. The first cluster included Brazil, Mexico, Nigeria, Bangladesh, US, Indonesia, Russia, and Pakistan, while the second cluster comprised India and China. The analysis also examined the relationship between population and confirmed tests and vaccines, and standardization was made for the country with the largest population for significant correlations. The results showed that the FKM method was superior to the K-prototype method in terms of clustering. In conclusion, it is crucial to accurately evaluate COVID-19 data for countries and develop appropriate policies. The clustering analysis using the FKM and K-prototype algorithms provides valuable insights into identifying groups of countries with similar COVID-19 data and policy plans.

Objectives: This study aims to investigate and compare the efficacy of platelet-rich plasma (PRP) injection, corticosteroid injection, and physical therapy in addition to exercise treatment on pain, shoulder functions, and quality of life in patients with subacromial impingement syndrome (SAIS). Patients and methods: Ninety patients (37 males, 53 females; mean age 48.99 years; range, 33 to 60 years) who were diagnosed as Stage 2 SAIS were included in the study. Patients were randomized into three groups. PRP injection was administered into the subacromial space of the affected shoulder in group 1, corticosteroid injection was administered in the subacromial joint space in group 2, and 10 sessions of physical therapy were given in group 3 five times weekly including transcutaneous electrical nerve stimulation, ultrasound, and hot packs. Moreover, an exercise program was administered in all groups. Visual Analog Scale (VAS) was used to determine the resting and moving shoulder pain; while the Shoulder Disability Questionnaire, Quick Disabilities of the Arm, Shoulder, and Hand (QuickDASH) questionnaire, and the University of California, Los Angeles Shoulder Rating Scale (UCLA SRS) were used to evaluate the functionality of patients. Quality of life was analyzed using a generic Short Form 36 (SF-36). Results: All scores improved in all three groups compared with the period before treatment. Comparison of the groups showed higher scores in group 1 compared to groups 2 and 3 at week eight on QuickDASH, UCLA SRS, VAS at rest and during activity, and SF-36 pain subgroup scores. Conclusion: All three treatment modalities were effective in the treatment of SAIS. However, we suggest that the inexpensive and noninvasive methods of physical therapy and exercise should be the first preferred treatment in SAIS owing to causing no adverse events.

It has been suggested that non-uterine endometrial implants can express thyroid-stimulating hormone receptors, thus inducing the formation of thyroid-stimulating immunoglobulin. We aimed to compare the autoantibody positivity in patients with and without endometriosis and to determine whether there is a difference in the incidence of thyroid diseases.

The aim of this study was to investigate associations between serum magnesium levels with insomnia and excessive daytime sleepiness (EDS) in older adults. A total of 938 older outpatients were included in the study. Hypomagnesemia was defined as serum magnesium concentration below <1.6 mg/dL. Patients were divided into two groups: hypomagnesemia and normomagnesia (1.6–2.6 mg/dL). The Epworth Sleepiness Scale was implemented and scores of ≥11 points were categorized as EDS. The Insomnia Severity Index was implemented and scores of ≥8 indicated insomnia. The mean age was 81.1 ± 7.6 years. While the presence of EDS, hypertension, diabetes mellitus, and coronary artery disease were more common in the hypomagnesemia group than the normomagnesia group, Parkinson’s disease was less common (p < 0.05). Hemoglobin and HDL cholesterol were lower, whereas HbA1c, triglyceride, and number of drugs used were higher in the hypomagnesemia group compared to the normomagnesia group (p < 0.05). In both univariate analysis and multivariate analysis adjusted for gender, age and all confounders, there were significant associations between hypomagnesemia and EDS [odds ratio (OR):1.7; 95% confidence interval (CI): 1.6–2.6, and OR: 1.9; 95%CI: 1.2–3.3, respectively (p < 0.05)]. There was no significant relationship between hypomagnesemia and insomnia (p > 0.05). The present study identified an association between hypomagnesemia and EDS in older adults. Therefore, it may be prudent to consider hypomagnesemia when evaluating older adults with EDS and vice versa.