METHODS: A cross-sectional observational study was conducted in the Emergency and Trauma Department, Hospital Kuala Lumpur (ETDHKL). The implementation of a binary triage system separates patients with risk of COVID-19 who present with fever and respiratory symptoms from other patients. Data on exposed HCWs to COVID-19 patients were captured pre-restructuring and post-restructuring of the emergency department and analysed using descriptive statistics.
RESULTS: A total of 846 HCWs were involved in this study. Pre-restructuring reported 542 HCWs exposed to COVID-19 patients while post-restructuring reported 122. Using the four categorical exposure risks for HCWs which are no identifiable risk, low risk, medium risk, and high risk, the number of HCWs exposed during pre-restructuring were 15(1.8%), 504 (59.6%), 15 (1.8%), and 8 (0.9%), respectively, while post-restructuring the numbers were 122 (14.4%), 8 (0.9%), 109 (12.9%), and 5 (0.1%), respectively. There was a 77.5% reduction in the number of exposed HCWs after our implementation of the new system (542 vs 122).
CONCLUSION: A binary triage system based on severity and infectivity and supported with structural reorganization can be effective in reducing HCWs COVID-19 exposure.
METHODS: This cross-sectional study involved 1,404 school adolescents aged 12 years (46% boys and 54% girls). Socio-demographic, dietary and physical activity data were collected using questionnaires whilst body weight and height were measured and body mass index was classified based on WHO BMI-for-age Z-scores cut-off.
RESULTS: A multivariable linear regression model showed that BMI z-score was positively associated with parents' BMI (P<0.001), birth weight (P=0.003), and serving size of milk and dairy products (P=0.036) whilst inversely associated with household size (P=0.022). Overall, 13.1% of the variances in BMI Z-scores were explained by parents' BMI, birth weight, servings of milk and dairy products and household size.
CONCLUSION: This study found important determinants of body weight status among adolescents mainly associated with family and home environmental factor. This evidence could help to form the effective and tailored strategies at the earliest stage to prevent obesity in this population.
METHODS: A total of 200 teeth from 20 patients undergoing fixed orthodontic therapy were assessed and biofilm formation around the brackets were recorded using the Bonded Bracket Index (Plaque index) at baseline and weekly for 6 weeks. The bacterial count and plaque pH at corresponding weekly intervals were also recorded. Following bracket bonding, the patients were cluster randomised to receive chitosan-based varnish-CHS (UNO Gel Bioschell, Germiphene corp., Brantford, Canada) or chlorhexidine-fluoride varnish-CFV (Cervitec F, Ivoclar Vivadent, Schaan, Liechtenstein) every week on the representative teeth respectively. BBI proportions were compared between groups at all time intervals using Chi square test. Mean plaque bacterial count and plaque pH were compared using Mann Whitney U test and Tukey's HSD test respectively.
RESULTS: Baseline characteristics were similar between the groups: Mean age was CHS = 23 and CFV = 21; male to female ratio was CHS = 5/5, CFV = 7/3. At the end of 6 weeks, chitosan-based varnish performed equal to chlorhexidine-fluoride varnish (P > 0.05) with 98% and 95% of teeth with acceptable scores respectively. The plaque bacterial count significantly reduced at 6 weeks for both varnish compared to the baseline; The value for CHS was 0.43 ± 0.4 × 104 and CFV was 0.77 ± 0.64 × 104 CFU (P
METHODS: Population pharmacokinetic models of tacrolimus were selected (n=17) for evaluation from a recent systematic review. The models were transcribed and implemented in NONMEM version 7.4.3. Data from 85 heart transplant recipients (2387 tacrolimus concentrations) administered the oral immediate-release formulation of tacrolimus (Prograf®) were obtained up to 391 days post-transplant. The performance of each model was evaluated using (1) prediction-based assessment (bias and imprecision) of the individual predicted tacrolimus concentration of the fourth dosing occasion (MAXEVAL=0, FOCE-I) from 1-3 prior dosing occasions and (2) simulation-based assessment (prediction-corrected visual predictive check, pcVPC). Both assessments were stratified based on concomitant azole antifungal use.
RESULTS: Regardless of the number of prior dosing occasions (1-3) and concomitant azole antifungal use, all models demonstrated unacceptable individual predicted tacrolimus concentration of the fourth dosing occasion (n=152). The pcVPC graphics indicated these models inadequately predicted observed tacrolimus concentrations.
CONCLUSIONS: All models evaluated were unable to adequately describe tacrolimus pharmacokinetics in adult heart transplant recipients included in this study. Further work is required to describe tacrolimus pharmacokinetics for our heart transplant recipient cohort.