Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/23733
Title: | The European Association of Preventive Cardiology Exercise Prescription in Everyday Practice and Rehabilitative Training (EXPERT) tool: A digital training and decision support system for optimized exercise prescription in cardiovascular disease. Concept, definitions and construction methodology. | Authors: | HANSEN, Dominique DENDALE, Paul CONINX, Karin Vanhees, Luc Piepoli, Massimo F. Niebauer, Josef Cornelissen, Veronique Pedretti, Roberto GEURTS, Eva ROVELO RUIZ, Gustavo Corra, U. Schmid, Jean-Paul Greco, Eugenio Davos, Constantinos Edelmann, Frank Abreu, Ana Rauch, Bernhard Ambrosetti, Marco Braga, Simona S. Barna, Olga Beckers, Paul Bussotti, Maurizio Fagard, Robert Faggiano, Pompilio Garcia-Porrero, Esteban Kouidi, Evangelia Lamotte, Michel Neunhauserer, Daniel Reibis, Rona SPRUIT, Martijn A. Stettler, Christoph Takken, Tim Tonoli, Cajsa Vigorito, Carlo Voller, Heinz Doherty, Patrick |
Issue Date: | 2017 | Source: | European journal of preventive cardiology 24 (10), p. 1-15 | Abstract: | 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. | Notes: | Hansen, D (reprint author), FESC Hasselt Univ, Fac Med & Life Sci, REVAL, Rehabil Res Ctr Agoralaan, Bldg A, B-3590 Diepenbeek, Belgium. dominique.hansen@uhasselt.be | Keywords: | cardiovascular disease; rehabilitation; exercise training; training and decision support system | Document URI: | http://hdl.handle.net/1942/23733 | ISSN: | 2047-4873 | e-ISSN: | 2047-4881 | DOI: | 10.1177/2047487317702042 | ISI #: | 000403615200003 | Rights: | (C) The European Society of Cardiology 2017 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2018 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
EAPC EXPERT paper 1 R1.pdf | Peer-reviewed author version | 915.41 kB | Adobe PDF | View/Open |
2047487317702042 (1).pdf Restricted Access | Published version | 450.08 kB | Adobe PDF | View/Open Request a copy |
SCOPUSTM
Citations
66
checked on Sep 3, 2020
WEB OF SCIENCETM
Citations
127
checked on Sep 28, 2024
Page view(s)
130
checked on Jun 12, 2022
Download(s)
154
checked on Jun 12, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.