Medicine
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This repository contains the published and unpublished research of the Faculty of Medicine by the staff members of the faculty
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Item Prediction equation for physical activity energy expenditure in 11-13-year-old Sri Lankan children(MDPI Publishing, 2023) Dabare, P.; Wickramasinghe, P.; Waidyatilaka, I.; Devi, S.; Kurpad, A.V.; Samaranayake, D.; de Lanerolle-Dias, M.; Wickremasinghe, R.; Hills, A.P.; Lanerolle, P.This study aimed to develop a regression equation to predict physical activity energy expenditure (PAEE) using accelerometry. Children aged 11-13 years were recruited and randomly assigned to validation (n = 54) and cross-validation (n = 25) groups. The doubly labelled water (DLW) technique was used to assess energy expenditure and accelerometers were worn by participants across the same period. A preliminary equation was developed using stepwise multiple regression analysis with sex, height, weight, body mass index, fat-free mass, fat mass and counts per minute (CPM) as independent variables. Goodness-of-fit statistics were used to select the best prediction variables. The PRESS (predicted residual error sum of squares) statistical method was used to validate the final prediction equation. The preliminary equation was cross-validated on an independent group and no significant (p > 0.05) difference was observed in the PAEE estimated from the two methods. Independent variables of the final prediction equation (PAEE = [0.001CPM] - 0.112) accounted for 70.6% of the variance. The new equation developed to predict PAEE from accelerometry was found to be valid for use in Sri Lankan children.Item Validation of accelerometer-based energy expenditure equations using doubly-labelled water technique in 11-13 year-old Sri Lankan children(Sri Lanka College of Paediatricians, 2021) Dabare, P.M.; Wickramasinghe, P.; Waidyatilaka, I.; Devi, S.; Kurpad, A.V.; Samaranayake, D.; de Lanerolle-Dias, M.; Wickremasinghe, R.; Hills, A.P.; Lanerolle, P.INTRODUCTION: Accelerometer based prediction equations are used to calculate physical activity energy expenditure (PAEE) among children. Currently, accelerometer-derived PAEE prediction equations validated against a criterion method do not exist for Sri Lankan children. Objective: To assess the validity of published prediction equations to estimate PAEE in Sri Lankan children against the doubly labelled water (DLW) technique. Method: Ninety-six children aged 11-13 years from an urban area of Sri Lanka were included in the study. Energy expenditure was assessed using the DLW technique over 10 days and participants wore ActiGraph accelerometers during the same period. Correlation between the measured and predicted PAEE was assessed by the Pearson correlation coefficient. Validity of equations was assessed by the paired t-test and the level of agreement using the Bland Altman analysis. Results: Predicted PAEE values were significantly (p<0.05) correlated with the measured PAEE except for the equations of Treuth and Schmitz. Prediction equations of Ekelund, Freedson, Mattock and Zhu significantly overestimated measured PAEE (p<0.05) whereas, Trost and Puyau equations significantly underestimated PAEE. A wide limit of agreement with a large mean bias was observed in all estimated PAEE, except for the equation of Zhu. Conclusions: Existing accelerometer-based PAEE equations have low accuracy in predicting PAEE in Sri Lankan children.Item Effects of probiotics combined with dietary and lifestyle modification on clinical, biochemical, and radiological parameters in obese children with nonalcoholic fatty liver disease/nonalcoholic steatohepatitis: a randomized clinical trial(Korean Pediatric Society, 2022) Rodrigo, T.; Samaranayake, D.; Seneviratne, S.N.; de Silva, A.P.; Fernando, J.; de Silva, H.J.; Jayasekera; Wickramasinghe, V.P.Background: Childhood obesity is a global problem associated with metabolic abnormalities. The gut-liver axis is thought to play a major role in its pathogenesis. Probiotics are known to alter the gut microbiota and, therefore, could be a therapeutic option in the management of childhood obesity-related complications. Purpose: This double-blind randomized placebo-controlled trial evaluated the effects of probiotics on metabolic derangement in obese children with nonalcoholic fatty liver disease/nonalcoholic steatohepatitis (NAFLD/NASH). Methods: Obese children with NAFLD/NASH treated at the nutrition clinic of the University Paediatric Unit at Lady Ridgeway Hospital, Colombo, were recruited. Anthropometry, body fat, metabolic derangement, and liver ultrasound scan (USS) results were evaluated at baseline and after 6 months. Transient elastography (FibroScan®) was performed on a subsample of these patients. Eighty-four patients were recruited and randomized into the probiotics (n = 43) and placebo (n = 41) groups. The mean age was 11.3±1.9 versus 12.1±1.5 years in the probiotic and placebo groups, respectively. Baseline parameters including liver disease stage on USS, body fat percentage, fasting blood sugar, lipid profile, liver function, and C-reactive protein showed no significant intergroup differences. Results: In the probiotic group, a statistically significant reduction in body mass index was noted from the baseline value. However, the reduction was not significant compared with the placebo group. There was a significant reduction in triglycerides, aspartate transaminase (AST), alanine aminotransferase (ALT), AST/ALT ratio, and alkaline phosphatase in the placebo group over the treatment period. Although the liver disease stage on USS improved from stage II-III to stage I in a small number of patients in the probiotic-treated group, transient elastography performed in a subsample did not demonstrate significant improvement in either group. Conclusion: Our results indicate that probiotics have no advantage over lifestyle modification for improving obesity-associated metabolic derangement in children.Item Seroprevalence of Bordetella pertussis specific Immunoglobulin G antibody levels among asymptomatic individuals aged 4 to 24 years: a descriptive cross sectional study from Sri Lanka(BioMed Central, 2016) Sigera, S.; Perera, J.; Rasarathinam, J.; Samaranayake, D.; Ediriweera, D.