TY  - GEN
A1  - Morel, T.
A1  - Castro, Norberto
A1  - Fossati, Luca
A1  - Hubrig, Swetlana
A1  - Langer, N.
A1  - Przybilla, Norbert
A1  - Schöller, Markus
A1  - Carroll, Thorsten Anthony
A1  - Ilyin, Ilya
A1  - Irrgang, Andreas
A1  - Oskinova, Lida
A1  - Schneider, Fabian R. N.
A1  - Simon Díaz, Sergio
A1  - Briquet, Maryline
A1  - González, Jean-Francois
A1  - Kharchenko, Nina
A1  - Nieva, M.-F.
A1  - Scholz, Ralf-Dieter
A1  - de Koter, Alexander
A1  - Hamann, Wolf-Rainer
A1  - Herrero, Artemio
A1  - Maíz Apellániz, Jesus
A1  - Sana, Hugues
A1  - Arlt, Rainer
A1  - Barbá, Rodolfo H.
A1  - Dufton, Polly
A1  - Kholtygin, Alexander
A1  - Mathys, Gautier
A1  - Piskunov, Anatoly E.
A1  - Reisenegger, Andreas
A1  - Spruit, H.
A1  - Yoon, S.-C.
T1  - The B fields in OB stars (BOB) survey
T2  - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
N2  - The B fields in OB stars (BOB) survey is an ESO large programme collecting spectropolarimetric observations for a large number of early-type stars in order to study the occurrence rate, properties, and ultimately the origin of magnetic fields in massive stars. As of July 2014, a total of 98 objects were observed over 20 nights with FORS2 and HARPSpol. Our preliminary results indicate that the fraction of magnetic OB stars with an organised, detectable field is low. This conclusion, now independently reached by two different surveys, has profound implications for any theoretical model attempting to explain the field formation in these objects. We discuss in this contribution some important issues addressed by our observations (e.g., the lower bound of the field strength) and the discovery of some remarkable objects.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 821 
KW  - magnetic fields
KW  - stars: early-type
KW  - stars: magnetic fields
KW  - stars: individual (HD 164492C, CPD –57 ◦ 3509, HD 54879, β CMa, ε CMa)
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-415238
SN  - 1866-8372
IS  - 821
ER  - 
TY  - JOUR
A1  - Hansen, Dominique
A1  - Niebauer, Josef
A1  - Cornelissen, Veronique
A1  - Barna, Olga
A1  - Neunhaeuserer, Daniel
A1  - Stettler, Christoph
A1  - Tonoli, Cajsa
A1  - Greco, Eugenio
A1  - Fagard, Robert
A1  - Coninx, Karin
A1  - Vanhees, Luc
A1  - Piepoli, Massimo F.
A1  - Pedretti, Roberto
A1  - Ruiz, Gustavo Rovelo
A1  - Corra, Ugo
A1  - Schmid, Jean-Paul
A1  - Davos, Constantinos H.
A1  - Edelmann, Frank
A1  - Abreu, Ana
A1  - Rauch, Bernhard
A1  - Ambrosetti, Marco
A1  - Braga, Simona Sarzi
A1  - Beckers, Paul
A1  - Bussotti, Maurizio
A1  - Faggiano, Pompilio
A1  - Garcia-Porrero, Esteban
A1  - Kouidi, Evangelia
A1  - Lamotte, Michel
A1  - Reibis, Rona Katharina
A1  - Spruit, Martijn A.
A1  - Takken, Tim
A1  - Vigorito, Carlo
A1  - Völler, Heinz
A1  - Doherty, Patrick
A1  - Dendale, Paul
T1  - Exercise prescription in patients with different combinations of cardiovascular disease risk factors
BT  - a consensus statement from the EXPERT working group
JF  - Sports medicine
N2  - 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.
Y1  - 2018
U6  - https://doi.org/10.1007/s40279-018-0930-4
SN  - 0112-1642
SN  - 1179-2035
VL  - 48
IS  - 8
SP  - 1781
EP  - 1797
PB  - Springer
CY  - Northcote
ER  - 
TY  - JOUR
A1  - Hansen, Dominique
A1  - Dendale, Paul
A1  - Coninx, Karin
A1  - Vanhees, Luc
A1  - Piepoli, Massimo F.
A1  - Niebauer, Josef
A1  - Cornelissen, Veronique
A1  - Pedretti, Roberto
A1  - Geurts, Eva
A1  - Ruiz, Gustavo R.
A1  - Corra, Ugo
A1  - Schmid, Jean-Paul
A1  - Greco, Eugenio
A1  - Davos, Constantinos H.
A1  - Edelmann, Frank
A1  - Abreu, Ana
A1  - Rauch, Bernhard
A1  - Ambrosetti, Marco
A1  - Braga, Simona S.
A1  - Barna, Olga
A1  - Beckers, Paul
A1  - Bussotti, Maurizio
A1  - Fagard, Robert
A1  - Faggiano, Pompilio
A1  - Garcia-Porrero, Esteban
A1  - Kouidi, Evangelia
A1  - Lamotte, Michel
A1  - Neunhaeuserer, Daniel
A1  - Reibis, Rona Katharina
A1  - Spruit, Martijn A.
A1  - Stettler, Christoph
A1  - Takken, Tim
A1  - Tonoli, Cajsa
A1  - Vigorito, Carlo
A1  - Völler, Heinz
A1  - Doherty, Patrick
T1  - 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
JF  - European journal of preventive cardiology : the official ESC journal for primary & secondary cardiovascular prevention, rehabilitation and sports cardiology
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.
KW  - Cardiovascular disease
KW  - rehabilitation
KW  - exercise training
KW  - training and decision support system
Y1  - 2017
U6  - https://doi.org/10.1177/2047487317702042
SN  - 2047-4873
SN  - 2047-4881
VL  - 24
SP  - 1017
EP  - 1031
PB  - Sage Publ.
CY  - London
ER  -