Whereas exercise training is key in the management of patients with cardiovascular disease (CVD) risk (obesity, diabetes, dyslipidaemia, hypertension), clinicians experience difficulties in how to optimally prescribe exercise in patients with different CVD risk factors. Therefore, a consensus statement for state-of-the-art exercise prescription in patients with combinations of CVD risk factors as integrated into a digital training and decision support system (the EXercise Prescription in Everyday practice & Rehabilitative Training (EXPERT) tool) needed to be established. EXPERT working group members systematically reviewed the literature for meta-analyses, systematic reviews and/or clinical studies addressing exercise prescriptions in specific CVD risk factors and formulated exercise recommendations (exercise training intensity, frequency, volume and type, session and programme duration) and exercise safety precautions, for obesity, arterial hypertension, type 1 and 2 diabetes, and dyslipidaemia. The impact of physical fitness, CVD risk altering medications and adverse events during exercise testing was further taken into account to fine-tune this exercise prescription. An algorithm, supported by the interactive EXPERT tool, was developed by Hasselt University based on these data. Specific exercise recommendations were formulated with the aim to decrease adipose tissue mass, improve glycaemic control and blood lipid profile, and lower blood pressure. The impact of medications to improve CVD risk, adverse events during exercise testing and physical fitness was also taken into account. Simulations were made of how the EXPERT tool provides exercise prescriptions according to the variables provided. In this paper, state-of-the-art exercise prescription to patients with combinations of CVD risk factors is formulated, and it is shown how the EXPERT tool may assist clinicians. This contributes to an appropriately tailored exercise regimen for every CVD risk patient.

Background Exercise rehabilitation is highly recommended by current guidelines on prevention of cardiovascular disease, but its implementation is still poor. Many clinicians experience difficulties in prescribing exercise in the presence of different concomitant cardiovascular diseases and risk factors within the same patient. It was aimed to develop a digital training and decision support system for exercise prescription in cardiovascular disease patients in clinical practice: the European Association of Preventive Cardiology Exercise Prescription in Everyday Practice and Rehabilitative Training (EXPERT) tool. Methods EXPERT working group members were requested to define (a) diagnostic criteria for specific cardiovascular diseases, cardiovascular disease risk factors, and other chronic non-cardiovascular conditions, (b) primary goals of exercise intervention, (c) disease-specific prescription of exercise training (intensity, frequency, volume, type, session and programme duration), and (d) exercise training safety advices. The impact of exercise tolerance, common cardiovascular medications and adverse events during exercise testing were further taken into account for optimized exercise prescription. Results Exercise training recommendations and safety advices were formulated for 10 cardiovascular diseases, five cardiovascular disease risk factors (type 1 and 2 diabetes, obesity, hypertension, hypercholesterolaemia), and three common chronic non-cardiovascular conditions (lung and renal failure and sarcopaenia), but also accounted for baseline exercise tolerance, common cardiovascular medications and occurrence of adverse events during exercise testing. An algorithm, supported by an interactive tool, was constructed based on these data. This training and decision support system automatically provides an exercise prescription according to the variables provided. Conclusion This digital training and decision support system may contribute in overcoming barriers in exercise implementation in common cardiovascular diseases.