Browsing by Author "Wickramasinghe, R."

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    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.
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    Knowledge, attitudes and practices regarding type 2 diabetes mellitus, nutrition and lifestyle in urban Sri Lankan women
    (Sri Lanka Medical Association, 2013) Waidyatilaka, P.H.I.U.; de Silva, A.; Atukorala, S.; Somasundaram, N.; Lanerolle, P.; Wickramasinghe, R.
    AIMS: Data on population specific patterns of knowledge, attitudes and practices (KAP) is essential for the design of effective intervention strategies. The aim of this study was to assess KAP regarding type 2 diabetes mellitus (T2DM), nutrition and lifestyle in Sri Lankan urban women who were unaware of their glycaemic status. Methods: 2800 apparently healthy urban women (30 - 45 years) were screened for dysglycaemia and 345 normoglcaemics and 272 dysglycaemics were selected from Coiombo Municipal Council area by random cluster sampling for a cross sectional study. An interviewer administered questionnaire was used to obtain KAP, demographic information and family history. Chi square test and Student's t- tests were used for categorical variables and for group comparison respectively. RESULTS: KAP on T2DM, nutrition and healthy lifestyle were poor. Knowledge on pre-diabetes and prevention of T2DM was also poor. However majority wanted to improve their knowledge. Women with a family history had better knowledge (p< 0.001) and attitudes (p< 0.05), but lower practice scores (p< 0.05) compared to women without a family history of T2DM. A significant (p< 0.001) proportion of women with a family history of T2DM found it difficult to resist eating foods high in fat and sugar. CONCLUSIONS: Overall KAP was poor, especially about pre-diabetes and prevention. Willingness to learn can be used positively to direct future interventions. Poor practices despite better knowledge and attitudes among women with a family history of T2DM indicate a need for targeted intervention.