Browsing by Author "Ranasinghe, A."
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Item Assessment of pollution in the St. Sebastian South canal, Orugodawaththa, a case study(Department of Zoology and Environmental Management, University of Kelaniya, 2015) Lekamge, D.; Samarawickrama, D.; Athukorala, U.; Dayananda, N.; Gamagedara, D.; Gnanasinghe, S.; Hansana, N.; Ranasinghe, A.; Ranasinghe, Y.; JayasriItem Can Graduates Increase Earnings by Acquiring Multiple Qualifications?(Sri Lanka Forum of University Economists (SLFUE), Department of Economics, Faculty of Social Sciences, University of Kelaniya, 2016) Pushpakumara, M.; Ranasinghe, A.; Siddhisena, P.Item Community-based cluster randomised trial of safe storage to reduce pesticide self-poisoning in rural Sri Lanka: study protocol(BioMed Central, 2011) Pearson, M.; Konradsen, F.; Gunnell, D.; Dawson, A.H.; Pieris, R.; Weerasinghe, M.; Knipe, D.W.; Jayamanne, S.; Metcalfe, C.; Hawton, K.; Wickremasinghe, A.R.; Atapattu, W.; Bandara, P.; de Silva, D.; Ranasinghe, A.; Mohamed, F.; Buckley, N.A.; Gawarammana, I.; Eddleston, M.A.BACKGROUND: The WHO recognises pesticide poisoning to be the single most important means of suicide globally. Pesticide self-poisoning is a major public health and clinical problem in rural Asia, where it has led to case fatality ratios 20-30 times higher than self-poisoning in the developed world. One approach to reducing access to pesticides is for households to store pesticides in lockable "safe-storage" containers. However, before this approach can be promoted, evidence is required on its effectiveness and safety. METHODS/DESIGN: A community-based cluster randomised controlled trial has been set up in 44,000 households in the North Central Province, Sri Lanka. A census is being performed, collecting baseline demographic data, socio-economic status, pesticide usage, self-harm and alcohol. Participating villages are then randomised and eligible households in the intervention arm given a lockable safe storage container for agrochemicals. The primary outcome will be incidence of pesticide self-poisoning over three years amongst individuals aged 14 years and over. 217,944 person years of follow-up are required in each arm to detect a 33% reduction in pesticide self-poisoning with 80% power at the 5% significance level. Secondary outcomes will include the incidence of all pesticide poisoning and total self-harm. DISCUSSION: This paper describes a large effectiveness study of a community intervention to reduce the burden of intentional poisoning in rural Sri Lanka. The study builds on a strong partnership between provincial health services, local and international researchers, and local communities. We discuss issues in relation to randomisation and contamination, engaging control villages, the intervention, and strategies to improve adherence.Item Development and validation of a cardiovascular risk prediction model for Sri Lankans using machine learning.(Public Library of Science, 2024-10) Mettananda, C.; Sanjeewa, I.; Arachchi, T.B.; Wijesooriya, A.; Chandrasena, C.; Weerasinghe, T.; Solangaarachchige, M.; Ranasinghe, A.; Elpitiya, I.; Sammandapperuma, R.; Kurukulasooriya, S.; Ranawaka, U.; Pathmeswaran, A.; Kasturiratne, A.; Kato, N.; Wickramasinghe, R.; Haddela, P.; De Silva, J.INTRODUCTION AND OBJECTIVES Sri Lankans do not have a specific cardiovascular (CV) risk prediction model and therefore, World Health Organization(WHO) risk charts developed for the Southeast Asia Region are being used. We aimed to develop a CV risk prediction model specific for Sri Lankans using machine learning (ML) of data of a population-based, randomly selected cohort of Sri Lankans followed up for 10 years and to validate it in an external cohort.MATERIAL AND METHODS The cohort consisted of 2596 individuals between 40-65 years of age in 2007, who were followed up for 10 years. Of them, 179 developed hard CV diseases (CVD) by 2017. We developed three CV risk prediction models named model 1, 2 and 3 using ML. We compared predictive performances between models and the WHO risk charts using receiver operating characteristic curves (ROC). The most predictive and practical model for use in primary care, model 3 was named "SLCVD score" which used age, sex, smoking status, systolic blood pressure, history of diabetes, and total cholesterol level in the calculation. We developed an online platform to calculate the SLCVD score. Predictions of SLCVD score were validated in an external hospital-based cohort.RESULTS Model 1, 2, SLCVD score and the WHO risk charts predicted 173, 162, 169 and 10 of 179 observed events and the area under the ROC (AUC) were 0.98, 0.98, 0.98 and 0.52 respectively. During external validation, the SLCVD score and WHO risk charts predicted 56 and 18 respectively of 119 total events and AUCs were 0.64 and 0.54 respectively.CONCLUSIONS SLCVD score is the first and only CV risk prediction model specific for Sri Lankans. It predicts the 10-year risk of developing a hard CVD in Sri Lankans. SLCVD score was more effective in predicting Sri Lankans at high CV risk than WHO risk charts.Item Effect of Sodium chloride (NaCl) salinity on some physiological traits of rice (Oryza sativa L.)(Sri Lanka Association for the Advancement of Science, 1991) Ranasinghe, A.; Peiris, B.Item An Extension of the Theory of Planned Behavior: Explaining Entrepreneurial Intentions of Undergraduates(Sri Lanka Forum of University Economists (SLFUE), Department of Economics, Faculty of Social Sciences, University of Kelaniya, 2016) Jayasundara, C.; Ranasinghe, A.Item Intercultural aspects in translations: Some experiences in translating from German into Sinhala(Sabaragamuwa University of Sri Lanka, 2006) Ranasinghe, A.