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Eur J Prev Cardiol. 2017 Jul;24(10):1017-1031. doi: 10.1177/2047487317702042. Epub 2017 Apr 18.

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.

Author information

1
1 Heart Centre Hasselt, Jessa Hospital, Belgium.
2
2 BIOMED-REVAL-Rehabilitation Research Centre, Hasselt University, Belgium.
3
3 Expertise Centre for Digital Media, Hasselt University, Belgium.
4
4 Department of Rehabilitation Sciences, University Leuven, Belgium.
5
5 Heart Failure Unit, Guglielmo da Saliceto Hospital, Italy.
6
6 Institute of Sports Medicine, Prevention and Rehabilitation, Paracelsus Medical University Salzburg, Austria.
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7 Research Group of Cardiovascular Rehabilitation, KU Leuven, Belgium.
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8 Department of Medicine and Cardiorespiratory Rehabilitation, Istituti Clinici Scientifici Maugeri, Italy.
9
9 Cardiologic Rehabilitation Department, Istituti Clinici Scientifici Salvatore Maugeri, Italy.
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10 Cardiology Clinic, Tiefenau Hospital, Switzerland.
11
11 University of Bern, Switzerland.
12
12 Fuscaldo (CS), Italy.
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13 Cardiovascular Research Laboratory, Academy of Athens, Greece.
14
14 Department of Internal Medicine with Cardiology, Charité-Universitaetsmedizin Berlin, Germany.
15
15 Department of Cardiology and Pneumology, University of Göttingen, Germany.
16
16 Cardiology Department, Hospital Santa Marta, Portugal.
17
17 Institut für Herzinfarktforschung Ludwigshafen, Germany.
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18 Cardiovascular Rehabilitation Unit, Le Terrazze Clinic, Italy.
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19 Family Medicine Department, National O.O. Bogomolets Medical University, Ukraine.
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20 Antwerp University Hospital, Department of Cardiology, Belgium.
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21 Unit of Cardiorespiratory Rehabilitation, Istituti Clinici Maugeri, Italy.
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22 Hypertension and Cardiovascular Rehabilitation Unit, KU Leuven University, Belgium.
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23 Cardiology Department, Spedali Civili, Italy.
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24 Cardiology Service, Complejo Hospitalario Universitario de León, Spain.
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25 Laboratory of Sports Medicine, Aristotle University of Thessaloniki, Greece.
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26 CUB Erasme Hospital, Belgium.
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27 Sport and Exercise Medicine Division, University of Padova, Italy.
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28 Cardiological Outpatient Clinics, Park Sanssouci, Germany.
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29 Department of Research and Education, CIRO+, the Netherlands.
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30 Department of Respiratory Medicine, Maastricht University Medical Centre, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht, the Netherlands.
31
31 Division of Endocrinology, Diabetes and Clinical Nutrition, University Hospital/Inselspital, Switzerland.
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32 Division of Pediatrics, Child Development & Exercise Center, Wilhelmina Children's Hospital, the Netherlands.
33
33 Department of Rehabilitation Science and Physiotherapy, Ghent University, Belgium.
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34 Internal Medicine and Cardiac Rehabilitation, University of Naples Federico II, Italy.
35
35 Department of Cardiology, Klinik am See, Germany.
36
36 Center of Rehabilitation Research, University of Potsdam, Germany.
37
37 Department of Health Sciences, University of York, UK.

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.

KEYWORDS:

Cardiovascular disease; exercise training; rehabilitation; training and decision support system

PMID:
28420250
DOI:
10.1177/2047487317702042
[Indexed for MEDLINE]
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