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This repository contains the published and unpublished research of the Faculty of Medicine by the staff members of the faculty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 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 Cardiovascular risk in a Sri Lankan community(Sri Lanka Medical Association, 2008) Ranawaka, U.K.; Wijekoon, C.N.; Pathmeswaran, A.; de Silva, L.D.R.; Gunasekara, D.; Chackrewarthy, S.; Mizoue, T.; Kato, N.OBJECTIVE: Identifying the cardiovascular disease (CVD) [coronary heart disease (CHD) and stroke] risk in a community is important in planning preventive strategies, but such data are lacking from Sri Lanka. We sought to describe the CVD and CHD risk in a Sri Lankan community. DESIGN, SETTING AND METHODS: A community survey was conducted in the Ragama Medical Officer of Health area (Ragama Health Study) involving individuals aged 35-65 years, selected by stratified random sampling. Their 10-year CVD and CHD risks were estimated using three widely used risk stratification ALGORITHMS: Framingham score, NCEP-ATP III (National Cholesterol Education Program – Adult Treatment Panel III), and Systematic Coronary Risk Evaluation (SCORE). Results: In the study population (n=2985), 54.5% were females, and the mean age [SD] was 52.4 [7.8] years. According to the Framingham (CHD risk), NCEP-ATP III (CHD risk) and SCORE (total CVD mortality risk) criteria, 11.5%, 37.2% and 9.7% respectively were classified as 'moderate or high risk'. Risks were not significantly different between sexes, except with NCEP-ATP III criteria (M- 54.1%, F- 21%, p55y- 38%, p55y- 64.7%, p<0.001; SCORE: <55y- 9.0%, >55y- 14.6%, PItem Cardiovascular risk profile of the estate population of Sri Lanka(Sri Lanka Medical Association, 2010) Pinidiyapathirage, M.J.; Chackrewarthy, S.; Perera, P.S.; Wijayasinghe, Y.S.; Williams, S.; Williams, S.S.; Kato, N.; Wickremasinghe, A.R.OBJECTIVES: To estimate the prevalence of biochemical and anthropometric risk markers of cardiovascular diseases in the estate population of Sri Lanka. METHODS: Using a cross sectional design, consenting adults aged 35-64 years resident in 3 selected estates in the Nuwara-Eliya District were recruited with the support of estate medical assistants and welfare officers. AH participants were subjected to an interview, blood pressure and anthropometric measurements and collection of fasting blood samples. RESULTS: Of the 401 participants recruited, 53% were females and 99% were cither Indian or Sri Lankan Tamils. The mean age of the participants was 50.3 years (SD 8.5). 47 (12%) participants had a BMI >25, 8 (2%) a BMI >30. 29 males (15%) and 29 females (14%) had a waist circumference [WC] >90cm and >80 cm, respectively. 151 (38%) participants had systolic blood pressure (SBP) > 140mmHg , 127 (32%) had diastolic blood pressure (DBF) > 90mmHg and 170 (42%) had either SBF > 140 or DBF > 90. 41(10%) participants had fasting blood glucose (FBG) >126mg/dL. In 197 (49%) participants, some form of dyslipidaemia was present. Males had a significantly higher mean BMI, FBG and triglyceride (TG) level and a significantly lower high density lipoprotein (HDL) level as compared to females. CONCLUSIONS: Obesity, as defined by BMI or WC, was low in this population as compared to other reported studies from different population groups in the country. But prevalence of hypertension and dyslipidaemia (especially high TG and low HDL levels in males) was high.