Early detection of cardiovascular disease: From identifying those at risk to making a timely diagnosis

Cardiovascular disease (CVD) is often diagnosed late: at the time of diagnosis, serious and permanent damage has often already occurred. Since evidence-based therapies exist for heart failure (HF), atrial fibrillation (AF) and coronary artery disease (CAD), early detection of these diseases is crucial to ensure that patients receive timely treatment to prevent severe disease.

In Part I of this thesis, we studied who is at risk of which types of CVD: we demonstrated that patients with diabetes, COPD and screen-detected AF are at risk of developing various types of CVD, particularly HF.

In Part II, we developed a brief questionnaire about symptoms of CVD that may help identify patients with previously unrecognized CVD. This questionnaire was included in the RED-CVD trial, in which we demonstrated that a proactive, stepwise diagnostic strategy increased the number of new diagnoses of HF, AF and CAD in primary care patients with diabetes and/or COPD.

In Part III, we demonstrated that relative fat mass (RFM) is a suitable marker of cardiometabolic risk that that performs at least similarly, yet has several important advantages compared to established obesity measures such as BMI and waist circumference.

This thesis highlights the importance of prevention and early detection of CVD – particularly HF – in high-risk populations, including patients with obesity, diabetes, COPD and AF. Although effects on patient outcomes remain to be studied, our results demonstrate that proactive diagnostic strategies are feasible and can improve early detection of CVD in primary care.