PATIENTS AND METHODS: This study was carried out from March to October 2018 at a tertiary hospital in Kuala Lumpur. The SQOP was translated from English to Malay according to international guidelines. Malay-speaking postmenopausal women ≥50 years were recruited and randomized into control and intervention groups. The intervention group received an osteoporosis prevention information booklet and a 15-minute pharmacist counselling session. All patients were asked to answer the SQOP-M questionnaire at baseline and two weeks later. The control group received the intervention after the study was completed.
RESULTS: Overall, 230/348 patients were recruited (C=115, I=115, response rate=66.1%). Exploratory factor analysis extracted four domains. Cronbach's α ranged from 0.230 to 0.938. Kappa measurement of agreement values ranged from 0.124 to 0.627, where 10/23 (43.5%) items were in moderate to substantial agreement. Wilcoxon signed rank test values were statistically significant (p<0.005) for 4/23 items. Item 17 was an optional question and excluded from analysis. Total satisfaction score was significantly higher for intervention group patients [76.9 (47.6-53.9) vs 50.4 (47.6-53.9), p<0.001] indicating higher satisfaction compared to control group.
CONCLUSION: The SQOP-M was found to be valid and reliable in assessing patient satisfaction of osteoporosis screening and prevention services provided to Malay-speaking patients in Malaysia.
MATERIALS AND METHODS: Literature search was conducted using online databases PubMed, ScienceDirect, and Scopus. A total of 517 records were identified from searches in PubMed, ScienceDirect, and Scopus. From the final exclusions, a total of 26 studies were included for final analysis.
RESULTS: Associated risk factors to getting SFTS infection include occupation, history of bite from a tick, biological susceptibility, and owning of domestic animal. Fatality rates apart from single case reports range from 15.1% to 50% and are contributed by various factors including delay in hospital admission, high viral load, older age group and presence of comorbid and complication.
CONCLUSION: A seroprevalence study can be conducted amongst the high-risk occupation group such as farmers and agricultural workers, as well as testing cases where viral fever is suspected but available tests for other diseases turns out negative.
AIM: We here aimed to find out the frequency of BRAFV600E mutation in a series of Malaysian patients with brain tumors and if any association exists between BRAFV600E mutation and clinicopathological features of patients.
MATERIAL AND METHODS: Fresh frozen tumor tissue samples from 50 Malaysian brain tumor patients were analyzed for BRAFV600E mutational status, and its correlation with clinicopathological features (including age, gender, and tumor localization such as intra-axial: within the brain substance or extra-axial: outside the brain substance) was examined.
RESULTS: The overall BRAFV600E mutation frequency was determined to be 22% (in 11 of 50 patients). BRAFV600E was significantly correlated with the tumor location group, which shows BRAFV600E was more frequent in the intra-axial tumor than the extra-axial tumor group. In this study, we also observed that male patients were slightly more susceptible to BRAFV600E mutation, and this mutation was predominant in patients of the age group
Objective: To assess whether sleep timing and napping behavior are associated with increased obesity, independent of nocturnal sleep length.
Design, Setting, and Participants: This large, multinational, population-based cross-sectional study used data of participants from 60 study centers in 26 countries with varying income levels as part of the Prospective Urban Rural Epidemiology study. Participants were aged 35 to 70 years and were mainly recruited during 2005 and 2009. Data analysis occurred from October 2020 through March 2021.
Exposures: Sleep timing (ie, bedtime and wake-up time), nocturnal sleep duration, daytime napping.
Main Outcomes and Measures: The primary outcomes were prevalence of obesity, specified as general obesity, defined as body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) of 30 or greater, and abdominal obesity, defined as waist circumference greater than 102 cm for men or greater than 88 cm for women. Multilevel logistic regression models with random effects for study centers were performed to calculate adjusted odds ratios (AORs) and 95% CIs.
Results: Overall, 136 652 participants (81 652 [59.8%] women; mean [SD] age, 51.0 [9.8] years) were included in analysis. A total of 27 195 participants (19.9%) had general obesity, and 37 024 participants (27.1%) had abdominal obesity. The mean (SD) nocturnal sleep duration was 7.8 (1.4) hours, and the median (interquartile range) midsleep time was 2:15 am (1:30 am-3:00 am). A total of 19 660 participants (14.4%) had late bedtime behavior (ie, midnight or later). Compared with bedtime between 8 pm and 10 pm, late bedtime was associated with general obesity (AOR, 1.20; 95% CI, 1.12-1.29) and abdominal obesity (AOR, 1.20; 95% CI, 1.12-1.28), particularly among participants who went to bed between 2 am and 6 am (general obesity: AOR, 1.35; 95% CI, 1.18-1.54; abdominal obesity: AOR, 1.38; 95% CI, 1.21-1.58). Short nocturnal sleep of less than 6 hours was associated with general obesity (eg, <5 hours: AOR, 1.27; 95% CI, 1.13-1.43), but longer napping was associated with higher abdominal obesity prevalence (eg, ≥1 hours: AOR, 1.39; 95% CI, 1.31-1.47). Neither going to bed during the day (ie, before 8pm) nor wake-up time was associated with obesity.
Conclusions and Relevance: This cross-sectional study found that late nocturnal bedtime and short nocturnal sleep were associated with increased risk of obesity prevalence, while longer daytime napping did not reduce the risk but was associated with higher risk of abdominal obesity. Strategic weight control programs should also encourage earlier bedtime and avoid short nocturnal sleep to mitigate obesity epidemic.
MATERIALS AND METHODS: This was a cross-sectional, single center study. A total of 110 subjects between 18 to 65 years of age and diagnosed with OSA following sleep study examinations were recruited. Exclusion criteria included seropositive Hepatitis B or Hepatitis C, and significant alcohol intake.
RESULT: The prevalence of NAFLD was 81.8%. The mean CIMT (0.08±0.03 vs 0.06±0.01 cm, p = 0.001), ICAM-1 (334.53±72.86 vs 265.46±102.92 ng/mL, p = 0.001) and Lp(a) (85.41±52.56 vs 23.55±23.66 nmol/L, p<0.001) were significantly higher in the NAFLD group compared to the non-NAFLD group. Comparisons between the different groups showed significantly increasing levels of CIMT, ICAM-1 and Lp(a), lowest within the non-NAFLD, followed by the NAFLD 1 and NAFLD 2+3 groups. There was a significant positive correlation between degree of steatosis and the severity of OSA (r = 0.453, p<0.001). Logistic regression analysis revealed that patients with apnea/hypopnea index (AHI) of >30 were 52.77 (CI 6.34, 439.14) times more likely to have NAFLD compared to those with mild AHI (p<0.001).
CONCLUSION: The prevalence of NAFLD is alarmingly high in this group of OSA patients. The degree of steatosis in patients with NAFLD was significantly correlated with severity of OSA, CIMT measurements, ICAM-1 and Lp(a). Our findings underscore screening for NAFLD in patients with OSA to ensure prompt risk stratification and management.
METHOD: The study used a variety of methods, which involved an on-line survey on the influences of social isolation using a non-probability sampling. More specifically, two techniques were used, namely a convenience sampling (i.e. involving members of the academic community, which are easy to reach by the study team), supported by a snow ball sampling (recruiting respondents among acquaintances of the participants). A total of 711 questionnaires from 41 countries were received. Descriptive statistics were deployed to analyse trends and to identify socio-demographic differences. Inferential statistics were used to assess significant differences among the geographical regions, work areas and other socio-demographic factors related to impacts of social isolation of university staff and students.
RESULTS: The study reveals that 90% of the respondents have been affected by the shutdown and unable to perform normal work or studies at their institution for between 1 week to 2 months. While 70% of the respondents perceive negative impacts of COVID 19 on their work or studies, more than 60% of them value the additional time that they have had indoors with families and others. .
CONCLUSIONS: While the majority of the respondents agree that they suffered from the lack of social interaction and communication during the social distancing/isolation, there were significant differences in the reactions to the lockdowns between academic staff and students. There are also differences in the degree of influence of some of the problems, when compared across geographical regions. In addition to policy actions that may be deployed, further research on innovative methods of teaching and communication with students is needed in order to allow staff and students to better cope with social isolation in cases of new or recurring pandemics.