Introduction

Cardiovascular disease (CVD) remains the most important cause of morbidity and mortality worldwide.1 For prevention of CVD, cardiovascular risk management is advocated in international guidelines.2 3 Many cohort studies and randomised controlled clinical trials (RCTs) have demonstrated the benefits of risk factor management, including smoking cessation, lipid lowering, blood pressure lowering, antithrombotic therapy, glucose lowering and more recently, anti-inflammatory therapies, on CVD risk.4–9 Besides these interventions, healthy lifestyle behaviour should always be promoted at individual and population level. With this growing plethora of choices in cardiovascular prevention, it can be difficult for both healthcare professional and patient to make the most appropriate treatment decisions for each individual person.

Identifying those patients who will benefit most from risk factor treatment is pivotal in the global CVD prevention effort. Risk stratification is a cornerstone in international CVD prevention guidelines, aiming to identify those at highest risk of future CVD in order to most effectively apply preventive strategies. Risk assessment using risk prediction tools can thus play a highly important part in global CVD prevention efforts in choosing the right treatment and the right treatment goals, for the right patient. This narrative review aims to guide clinicians in using risk stratification tools as decision support tool in CVD prevention.