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)

Author:

Rossello Xavier12,Dorresteijn Jannick AN3,Janssen Arne4,Lambrinou Ekaterini45,Scherrenberg Martijn67,Bonnefoy-Cudraz Eric8,Cobain Mark9,Piepoli Massimo F10,Visseren Frank LJ2,Dendale Paul67,This paper is a co-publication betw

Affiliation:

1. Centro Nacional de Investigaciones Cardiovasculares (CNIC), Spain

2. Centro de Investigación Biomédica en Red en Enfermedades Cardiovasculares (CIBERCV), Spain

3. Department of Vascular Medicine, University Medical Center Utrecht, The Netherlands

4. Clinical Research Department Cardiology, Heartcentre Hasselt, Jessa Hospital, Hasselt, Belgium

5. Department of Nursing, Cyprus University of Technology, Cyprus

6. Jessa Hospital, Heartcentre Hasselt, Belgium

7. Faculty of Medicine and Life Sciences, Hasselt University, Belgium

8. Department of Cardiology, Hoŝpital cardiologique de Lyon, France

9. Department of Cardiovascular Medicine, Imperial College, UK

10. Heart Failure Unit, Cardiology, G da Saliceto Hospital, ItalyKeck School of Medicine, University of Southern California, Los Angeles, CA, USA

Abstract

Risk assessment 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.

Publisher

Oxford University Press (OUP)

Subject

Cardiology and Cardiovascular Medicine,Epidemiology

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