Subclinical atherosclerosis and silent myocardial ischaemia in patients with type 2 diabetes: a protocol of a clinico-observational study

Abstract

IntroductionAtherosclerotic cardiovascular disease is a significant modifiable complication in patients with diabetes and subclinical atherosclerosis is considered a surrogate marker of future vascular events. The clustering of cardiometabolic-risk factors in patients with diabetes and cardiovascular disease is increasingly being recognised. Recent evidence indicates that 20–50% of asymptomatic patients with diabetes may have silent coronary heart disease. However, the identification of subclinical atherosclerosis and silent myocardial ischaemia in patients with diabetes has been less well-explored, especially in low-resource population settings where cost-effective non-invasive clinical tools are available. The objective of this study is to identify patients with physician-diagnosed diabetes who are at risk of developing future cardiovascular events measured as subclinical atherosclerosis and silent myocardial ischaemia in an urban population of Eastern India.Methods and analysisThis is a cross-sectional clinico-observational study. A convenience sampling of approximately 350 consecutive patients with type 2 diabetes based on predefined inclusion and exclusion criteria will be identified at an urban diabetes center. This estimated sample size is based on an expected prevalence of silent myocardial ischaemia of 25% (± 5%), we computed the required sample size using OpenEpi online software assuming an α level of 0.05 (95% CI) to be 289. On factoring 20% non-response the estimated sample size is 350. Previously validated questionnaire tools and well-defined clinical, anthropometric and biochemical measurements will be utilised for data collection. The two primary outcomes—subclinical atherosclerosis and silent myocardial ischaemia will be measured using carotid intima-media thickness and exercise tolerance testing, respectively. Descriptive and multivariate logistic regression statistical techniques will be employed to identify ‘at risk’ patients with diabetes, and adjusted for potential confounders.Ethics and disseminationEthical approval was granted by the institutional review board of Kalinga Institute of Medical Sciences, Bhubaneshwar, India. Data will be presented at academic fora and published in peer-reviewed journals.