Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/23247
Title: Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP)
Authors: Rossello, Xavier 
Dorresteijn, Jannick An 
Janssen, Arne 
Lambrinou, Ekaterini 
Scherrenberg, Martijn 
Bonnefoy-Cudraz, Eric 
Cobain, Mark 
Piepoli, Massimo F. 
Visseren, Frank Lj 
Dendale, Paul 
Major Field of Science: Medical and Health Sciences
Field Category: Health Sciences
Keywords: Risk prediction;Cardiovascular disease;Patient;Prevention;Risk assessment
Issue Date: Aug-2020
Source: European heart journal: Acute cardiovascular care, 2020, vol. 9, no. 5, pp. 522–532
Volume: 9
Issue: 5
Start page: 522
End page: 532
Journal: European heart journal: Acute cardiovascular care 
Abstract: Risk assessment and risk prediction have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of - usually interactive and online available - tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.
URI: https://ktisis.cut.ac.cy/handle/10488/23247
ISSN: 2048-8734
DOI: 10.1177/2048872619858285
Rights: © The European Society of Cardiology
Attribution-NonCommercial-NoDerivatives 4.0 International
Type: Article
Affiliation : Cyprus University of Technology 
Centro Nacional de Investigaciones Cardiovasculares (CNIC) 
CIBER - Centro de Investigacion Biomedica en Red 
Utrecht University 
Jessa Hospital 
Hasselt University 
Imperial College London 
Guglielmo da Saliceto Hospital 
University of Southern California 
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