METHODS: We downloaded COVID-19 outbreak data of the number of confirmed cases in all countries as of October 19, 2020. The IRT-based predictive model was built to determine the pandemic IP for each country. A model building scheme was demonstrated to fit the number of cumulative infected cases. Model parameters were estimated using the Solver add-in tool in Microsoft Excel. The absolute advantage coefficient (AAC) was computed to track the IP at the minimum of incremental points on a given ogive curve. The time-to-event analysis (a.k.a. survival analysis) was performed to compare the difference in IPs among continents using the area under the curve (AUC) and the respective 95% confidence intervals (CIs). An online comparative dashboard was created on Google Maps to present the epidemic prediction for each country.
RESULTS: The top 3 countries that were hit severely by COVID-19 were France, Malaysia, and Nepal, with IP days at 263, 262, and 262, respectively. The top 3 continents that were hit most based on IP days were Europe, South America, and North America, with their AUCs and 95% CIs at 0.73 (0.61-0.86), 0.58 (0.31-0.84), and 0.54 (0.44-0.64), respectively. An online time-event result was demonstrated and shown on Google Maps, comparing the IP probabilities across continents.
CONCLUSION: An IRT modeling scheme fitting the epidemic data was used to predict the length of IP days. Europe, particularly France, was hit seriously by COVID-19 based on the IP days. The IRT model incorporated with AAC is recommended to determine the pandemic IP.
METHODS: This is a systematic review protocol describing essential reporting items based on the PRISMA for systematic review protocols (PRISMA-P) (Registration number: CRD42020220636). We aim to review the effectiveness, tolerability, and safety of hf-rTMS at DLPFC in randomised controlled trials (RCTs) as migraine prophylactic treatment. We will search Scopus, Cumulative Index to Nursing and Allied Health Literature Plus, PubMed, Cochrane Central Register of Controlled Trials and Biomed Central for relevant articles from randomised controlled clinical trials that used hf-rTMS applied at DLPFC for the treatment of migraine. The risk of bias will be assessed using the version 2 "Risk of bias" tool from Cochrane Handbook for Systematic Reviews of Interventions Version 6.1. We will investigate the evidence on efficacy, tolerability and safety and we will compare the outcomes between the hf-rTMS intervention and sham groups.
DISCUSSION: This systematic review will further determine the efficacy, safety, and tolerability of hf-rTMS applied at DLPFC for migraine prophylaxis. It will provide additional data for health practitioners and policymakers about the usefulness of hf-rTMS for migraine preventive treatment.
METHODS: Included trials were assessed using Cochrane risk of bias instrument. We performed meta-analysis with random-effects model and random errors were evaluated with TSA. We performed the search for the eligible randomized controlled trial (RCT) through Medline, Cinahl, Cochrane Central Register of Controlled Trials and also PubMed.
RESULTS: A total of 370 subjects sourced from seven eligible RCTs were entered into the analysis. The pooled results demonstrated the significant reduction with the use of qigong of the systolic blood pressure [weighted mean difference (WMD), - 10.66 mmHg (95% confidence interval (CI) = - 17.69,-3.62, p
METHODS: We systematically searched PubMed, Ovid, Scopus and ScienceDirect for observational studies in Asia from inception to August 2017. We selected cross sectional studies reporting the prevalence and risk factors for GDM. A random effects model was used to estimate the pooled prevalence of GDM and odds ratio (OR) with 95% confidence interval (CI).
RESULTS: Eighty-four studies with STROBE score ≥ 14 were included in our analysis. The pooled prevalence of GDM in Asia was 11.5% (95% CI 10.9-12.1). There was considerable heterogeneity (I2 > 95%) in the prevalence of GDM in Asia, which is likely due to differences in diagnostic criteria, screening methods and study setting. Meta-analysis demonstrated that the risk factors of GDM include history of previous GDM (OR 8.42, 95% CI 5.35-13.23); macrosomia (OR 4.41, 95% CI 3.09-6.31); and congenital anomalies (OR 4.25, 95% CI 1.52-11.88). Other risk factors include a BMI ≥25 kg/m2 (OR 3.27, 95% CI 2.81-3.80); pregnancy-induced hypertension (OR 3.20, 95% CI 2.19-4.68); family history of diabetes (OR 2.77, 2.22-3.47); history of stillbirth (OR 2.39, 95% CI 1.68-3.40); polycystic ovary syndrome (OR 2.33, 95% CI1.72-3.17); history of abortion (OR 2.25, 95% CI 1.54-3.29); age ≥ 25 (OR 2.17, 95% CI 1.96-2.41); multiparity ≥2 (OR 1.37, 95% CI 1.24-1.52); and history of preterm delivery (OR 1.93, 95% CI 1.21-3.07).
CONCLUSION: We found a high prevalence of GDM among the Asian population. Asian women with common risk factors especially among those with history of previous GDM, congenital anomalies or macrosomia should receive additional attention from physician as high-risk cases for GDM in pregnancy.
TRIAL REGISTRATION: PROSPERO (2017: CRD42017070104 ).
METHOD: This online-based cross-sectional study was conducted among 1280 healthcare providers aged ≥18 years from 30 primary care clinics in the state of Selangor, Malaysia. The Fear of COVID-19 Scale was used to assess the level of fear, and the results were analysed using multiple linear regression.
RESULTS: The mean age of the respondents was 36 years, and the mean working experience was 11 years. The majority of the respondents were women (82.4%) and Malays (82.3%). The factors that were significantly correlated with higher levels of fear were underlying chronic disease (ß=1.12, P=0.002, 95% confidence interval [CI]=0.08, 3.15), concern about mortality from COVID-19 (ß=3.3, P<0.001, 95% CI=0.19, 7.22), higher risk of exposure (ß=0.8, P<0.001, 95% CI=0.14, 5.91), concern for self at work (ß=2.8, P=0.002, 95% CI=0.08, 3.10) and work as a nurse (ß=3.6, P<0.001, 95% CI=0.30, 7.52), medical laboratory worker (ß=3.0, P<0.001, 95% CI=0.12, 4.27) and healthcare assistant (ß=3.9, P<0.001, 95% CI=0.17, 5.73). The level of fear was inversely correlated with a higher work-related stress management score (ß=-0.9, P<0.001, 95% CI=-0.14, -5.07) and a higher sleep quality score (ß=-1.8, P<0.001, 95% CI=-0.28, -10.41).
CONCLUSION: Family physicians should be vigilant and identify healthcare providers at risk of developing COVID-19-related fear to initiate early mental health intervention.
METHODS: We obtained the validity and reliability evidence for the SAS-M-SF using a group of 307 pre-university students in Universiti Putra Malaysia (UPM), Serdang, Selangor, Malaysia with a mean age of 18.4±0.2 years (70.4% female and 29.6% male). A questionnaire containing the Malay version of Smartphone Addiction Scale (SAS-M), the Malay version of the short form Smartphone Addiction Scale (SAS-M-SF), and the Malay version of the Internet Addiction Test (IAT-M) was administered on the adolescents.
RESULTS: The SAS-M-SF displayed good internal consistency (Cronbach's α=0.80). Using principle component analysis, we identified a 4-factor SAS-M-SF model. A significant correlation between the SAS-M-SF and the IAT-M was found, lending support for concurrent validity. The prevalence of smartphone addiction was 54.5% based on cut-off score of ≥36 with a sensitivity of 70.2% and a specificity of 72.5%.
CONCLUSIONS: The 10-item SAS-M-SF is a valid and reliable screening tool for smartphone addiction among adolescents. The scale can help clinicians or educators design appropriate intervention and prevention programs targeting smartphone addiction in adolescents at clinical or school settings.
Methods: A systematic literature search was performed using the Medline, Cochrane, and Embase databases from inception to 20 October 2018. Primary outcome for meta-analyses was the changes in hepatic enzyme levels (alanine transaminase, aspartate transaminase, and gamma-glutamyl transpeptidase). We also performed a meta-analysis on changes in insulin resistance, glycemic, and lipid parameters using SGLT2Is as a secondary objective.
Results: Eight eligible randomized controlled studies were eligible for analysis. Meta-analysis showed the efficacy of two SLT2Is, dapagliflozin, and canagliflozin in reducing these enzymes level. TSA showed that canagliflozin significantly reduced the gamma-glutamyl transpeptidase level by weighted mean difference (-5.474, 95% confidence interval (CI): -6.289??-4.659) compared to others comparators, and the evidence is conclusive. Dapagliflozin also had a statistically significant reduction in glycated hemoglobin, which is a parameter of glycemic control and homeostatic model assessment for insulin sensitivity (HOMA-IR), which is a parameter of insulin sensitivity by a weight mean difference, -0.732 (95% CI: -1.087??-0.378) and -0.804 (95% CI: -1.336??0.272), respectively.
Conclusions: This study indicated that canagliflozin effectively improves liver function parameters among patients with diabetes, while dapagliflozin is more effective in improving glycemic indices and insulin sensitivity.