Comparison of cardiovascular risk prediction models developed using machine learning based on data from a Sri Lankan cohort with World Health Organization risk charts for predicting cardiovascular risk among Sri Lankans: a cohort study.

Introduction: Models derived from non-Sri Lankan cohorts are used for cardiovascular (CV) risk stratification of Sri Lankans.

Objective: To develop a CV risk prediction model using machine learning (ML) based on data from a Sri Lankan cohort followed up for 10 years, and to compare the predictions with WHO risk charts.

Design: Cohort study.

Predictors of unmet needs among people with diabetes mellitus type 2 in Gampaha district of Sri Lanka.

Diabetes mellitus is a significant contributor to the disease burden in Sri Lanka. Despite government efforts to improve access to care for those with chronic illness, major gaps remain. We assessed the prevalence and correlates of unmet needs among persons with diabetes mellitus type 2 to inform policies on improving healthcare access in a predominantly tax-funded public healthcare system.

Content analysis of policy documents related to non-communicable diseases prevention and control in Sri Lanka: a developing country in the South-East Asia.

Background: Health policies form the foundation for provisioning best level care and are important for all stakeholders including patients and healthcare providers. Health policy analysis and evaluation allows policy makers to improve an existing policy, terminate a non-effective policy and to successfully implement future policies.The objective was to assess the coherence between the two local policy documents on NCD prevention and control in Sri Lanka, the national NCD policy (NCD policy) and the multisectoral action plan (MSAP), and to assess the consistency of MSAP with the global action plan for NCDs.

Development of a Core Outcome Measure Instrument; "LeishCOM_LCL", for Localised Cutaneous Leishmaniasis.

Background: Localized cutaneous leishmaniasis (LCL) is a chronic ulcerating disease. A literature review identified inconsistencies in clinical trials. The aims of this study were to reach a consensus on the most important domains to measure when assessing LCL, agree on parameters to measure the domains, and develop a tool representing a Core Outcome Set (COS), for use in clinical assessment of LCL.