Prediction and early detection of cardiovascular disease in South Asians with diabetes mellitus.

Background: Although diabetes mellitus (DM) is no longer considered "coronary heart disease risk equivalent", the risk remains sufficiently high, necessitating early recognition and management of cardiovascular disease (CVD) in these patients. Despite this understanding, the optimum strategy for prediction and early detection of CVD in DM remains debatable.

Methods: Major societal guidelines for prediction and evaluation of CVD in subjects with or without DM were reviewed. Available evidence about various risk stratification strategies-their advantages, disadvantages and current role in clinical practice-were extensively reviewed. Special emphasis was placed on evidence from South Asian/Indian populations.

Results: The inconsistency and variability inherent to the clinical risk algorithms, lack of consensus regarding the incremental value of subclinical atherosclerosis imaging and the lack of sufficient data to demonstrate the benefits of recognizing asymptomatic atherosclerotic disease are some of the reasons underlying prevailing uncertainty about the optimum approach for cardiovascular risk assessment in DM. These challenges notwithstanding, an evidence-based cardiovascular risk stratification strategy incorporating clinical risk algorithms, biomarkers, atherosclerosis imaging, and cardiac stress testing is proposed.

Conclusions: The proposed algorithm should help clinicians in optimizing cardiovascular evaluation and management of their patients with DM. However, this remains a dynamic field; further research into different risk assessment tools, esp. focusing on their impact on improving clinical outcomes, should help refine the evaluation strategy in future.