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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 A. N. JANSSEN, Arne Lambrinou, Ekaterini SCHERRENBERG, Martijn Bonnefoy-Cudraz, Eric Cobain, Mark Piepoli, Massimo F. Visseren, Frank L. J. DENDALE, Paul |
Issue Date: | 2019 | Publisher: | SAGE PUBLICATIONS LTD | Source: | EUROPEAN JOURNAL OF PREVENTIVE CARDIOLOGY, 26(14), p. 1534-1544 | 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. | Notes: | [Rossello, Xavier] CNIC, Madrid, Spain. [Rossello, Xavier; Visseren, Frank L. J.] Ctr Invest Biomed Red Enfermedades Cardiovasc CIB, Barcelona, Spain. [Dorresteijn, Jannick A. N.] Univ Med Ctr Utrecht, Dept Vasc Med, Utrecht, Netherlands. [Janssen, Arne; Lambrinou, Ekaterini] Jessa Hosp, Heartctr Hasselt, Clin Res Dept Cardiol, Hasselt, Belgium. [Lambrinou, Ekaterini] Cyprus Univ Technol, Dept Nursing, Limassol, Cyprus. [Scherrenberg, Martijn; Dendale, Paul] Jessa Hosp, Heartctr Hasselt, Hasselt, Belgium. [Scherrenberg, Martijn; Dendale, Paul] Hasselt Univ, Fac Med & Life Sci, Hasselt, Belgium. [Bonnefoy-Cudraz, Eric] Hosp Cardiol Lyon, Dept Cardiol, Lyon, France. [Cobain, Mark] Imperial Coll, Dept Cardiovasc Med, London, England. [Piepoli, Massimo F.] Guglielmo da Saliceto Hosp, Heart Failure Unit, Cardiol, Piacenza, Italy. [Piepoli, Massimo F.] Univ Southern Calif, Keck Sch Med, Los Angeles, CA USA. | Keywords: | Risk prediction; risk assessment; cardiovascular disease; prevention; patient;Risk prediction; risk assessment; cardiovascular disease; prevention; patient | Document URI: | http://hdl.handle.net/1942/29998 | ISSN: | 2047-4873 | e-ISSN: | 2047-4881 | DOI: | 10.1177/2047487319846715 | ISI #: | 000482056800013 | Rights: | The European Society of Cardiology 2019 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2020 |
Appears in Collections: | Research publications |
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