TY - JOUR
T1 - The European Association of Preventive Cardiology Exercise Prescription in Everyday Practice and Rehabilitative Training (EXPERT) tool
T2 - A digital training and decision support system for optimized exercise prescription in cardiovascular disease. Concept, definitions and construction methodology
AU - Hansen, Dominique
AU - Dendale, Paul
AU - Coninx, Karin
AU - Vanhees, Luc
AU - Piepoli, Massimo F.
AU - Niebauer, Josef
AU - Cornelissen, Veronique
AU - Pedretti, Roberto
AU - Geurts, Eva
AU - Ruiz, Gustavo R.
AU - Corra, Ugo
AU - Schmid, Jean-Paul
AU - Greco, Eugenio
AU - Davos, Constantinos H.
AU - Edelmann, Frank
AU - Abreu, Ana
AU - Rauch, Bernhard
AU - Ambrosetti, Marco
AU - Braga, Simona S.
AU - Barna, Olga
AU - Beckers, Paul
AU - Bussotti, Maurizio
AU - Fagard, Robert
AU - Faggiano, Pompilio
AU - Garcia-Porrero, Esteban
AU - Kouidi, Evangelia
AU - Lamotte, Michel
AU - Neunhaeuserer, Daniel
AU - Reibis, Rona
AU - Spruit, Martijn A.
AU - Stettler, Christoph
AU - Takken, Tim
AU - Tonoli, Cajsa
AU - Vigorito, Carlo
AU - Voeller, Heinz
AU - Doherty, Patrick
PY - 2017/7
Y1 - 2017/7
N2 - 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.
AB - 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.
KW - Cardiovascular disease
KW - rehabilitation
KW - exercise training
KW - training and decision support system
KW - JOINT TASK-FORCE
KW - CARDIAC REHABILITATION
KW - ESC GUIDELINES
KW - PHYSICAL-ACTIVITY
KW - NATIONAL-SURVEY
KW - HEART-FAILURE
KW - MANAGEMENT
KW - DIAGNOSIS
KW - MODALITIES
KW - SOCIETY
U2 - 10.1177/2047487317702042
DO - 10.1177/2047487317702042
M3 - Article
SN - 2047-4873
VL - 24
SP - 1017
EP - 1031
JO - European Journal of Preventive Cardiology
JF - European Journal of Preventive Cardiology
IS - 10
ER -