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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)
- Source :
- European Heart Journal: Acute Cardiovascular Care, European Heart Journal: Acute Cardiovascular Care, SAGE Publications, 2020, 9 (5), pp.522-532. ⟨10.1177/2048872619858285⟩, European Journal of Cardiovascular Nursing, 18(7), 534. Elsevier, European Journal of Preventive Cardiology, 26(14), 1534. SAGE Publications Ltd, European Heart Journal: Acute Cardiovascular Care, 2020, 9 (5), pp.522-532. ⟨10.1177/2048872619858285⟩
- Publication Year :
- 2020
- Publisher :
- HAL CCSD, 2020.
-
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 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. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: this paper was produced within the framework of the ESC Prevention of Cardiovascular Disease Programme which is 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). The ESC Prevention of Cardiovascular Disease Programme is supported by unrestricted educational grants. The authors received no financial support for the research, authorship, and/or publication of this article. Rossello, X (corresponding author), Ctr Nacl Invest Cardiovasc CNIC Carlos III, Melchor Fernandez Almagro 3, Madrid 28029, Spain. fjrossello@cnic.es
- Subjects :
- Male
Time Factors
Epidemiology
[SDV]Life Sciences [q-bio]
Allied Health Personnel
Disease
030204 cardiovascular system & hematology
Critical Care and Intensive Care Medicine
Medical and Health Sciences
0302 clinical medicine
prevention
Risk Factors
cardiovascular disease
Preventive Health Services
Advanced and Specialised Nursing
030212 general & internal medicine
Cardiovascular nursing
Societies, Medical
Aged, 80 and over
biology
risk assessment
General Medicine
Middle Aged
Prognosis
Risk prediction
3. Good health
[SDV] Life Sciences [q-bio]
Preventive cardiology
Europe
Primary Prevention
Medical–Surgical Nursing
Cardiovascular Diseases
Practice Guidelines as Topic
Female
patient
Cardiology and Cardiovascular Medicine
Risk assessment
Algorithms
Adult
Cardiovascular Nursing
medicine.medical_specialty
Critical Care
Clinical Decision-Making
Cardiology
Decision Support Techniques
03 medical and health sciences
Predictive Value of Tests
Health Sciences
Medical–Surgical
medicine
Humans
Medical history
Intensive care medicine
Association (psychology)
Aged
Advanced and Specialized Nursing
patient Keywords Risk prediction
Acca
Models, Statistical
business.industry
biology.organism_classification
Lifetime risk
business
Forecasting
Subjects
Details
- Language :
- English
- ISSN :
- 20488726, 20488734, 14745151, and 20474873
- Database :
- OpenAIRE
- Journal :
- European Heart Journal: Acute Cardiovascular Care, European Heart Journal: Acute Cardiovascular Care, SAGE Publications, 2020, 9 (5), pp.522-532. ⟨10.1177/2048872619858285⟩, European Journal of Cardiovascular Nursing, 18(7), 534. Elsevier, European Journal of Preventive Cardiology, 26(14), 1534. SAGE Publications Ltd, European Heart Journal: Acute Cardiovascular Care, 2020, 9 (5), pp.522-532. ⟨10.1177/2048872619858285⟩
- Accession number :
- edsair.doi.dedup.....215ad92ad6e984782fb63815a77a577c
- Full Text :
- https://doi.org/10.1177/2048872619858285⟩