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.

Exercise oscillatory breathing is an independent predictor of SCD in patients with CHF and might help as an additional marker for prioritization of antiarrhythmic strategies.

Background: Estimates of the prevalence of atrial fibrillation (AF ) in heart failure (HF ) originate from patients enrolled in clinical trials. Aims: To assess the prevalence and clinical correlates of AF among HF patients in everyday clinical practice from HF patients screened for the T-wave ALternans in Patients with Heart fAilure (ALPHA) study; to investigate the correlation between AF and functional status. Methods and results: Consecutive patients (N = 3513) seen at nine Heart Failure Clinics were studied; 21.4% were in AF. AF prevalence was greater with increasing age (OR 1.04/year, p b 0.001) in non-ischaemic cardiomyopathy (OR 2.34, p b 0.001) and with increasing NYHA class ( p b 0.0001). Multiple logistic regression predictors of AF were age N70 years (OR 2.35), NYHA class II III or IV vs class I (OR 1.8, 4.4 and 3.1) and non-ischaemic cardiomyopathy (OR 3.2).A logistic model indicated that AF was associated with a 2.5 OR of being in NYHA class III-IV vs I-II while accounting for age, gender, left ventricular ejection fraction (LVEF), and aetiology of HF. Conclusions: The prevalence of AF in HF patients exceeds 20%, and increases with age and functional class. The presence of AF leads to a more severe NYHA class, indicating that AF contributes to the severity of heart failure.

Preoperative PUFA therapy is associated with a decreased incidence of early AF after cardiac surgery but not late AF. Patients undergoing cardiac surgery may benefit from a preventive PUFA approach.

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