scholarly journals 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)

2019 ◽  
Vol 9 (5) ◽  
pp. 522-532 ◽  
Author(s):  
Xavier Rossello ◽  
Jannick AN Dorresteijn ◽  
Arne Janssen ◽  
Ekaterini Lambrinou ◽  
Martijn Scherrenberg ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Clinical Practice ◽  
Risk Prediction ◽  
European Association ◽  
Risk Measures ◽  
Preventive Cardiology ◽  
Prediction Tools ◽  
Risk Algorithm ◽  
Preventive Medication ◽  
The Right

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.

scholarly journals 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)

2019 ◽  
Vol 18 (7) ◽  
pp. 534-544 ◽  
Author(s):  
Xavier Rossello ◽  
Jannick AN Dorresteijn ◽  
Arne Janssen ◽  
Ekaterini Lambrinou ◽  
Martijn Scherrenberg ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Clinical Practice ◽  
Risk Prediction ◽  
European Association ◽  
Risk Measures ◽  
Preventive Cardiology ◽  
Prediction Tools ◽  
Risk Algorithm ◽  
Preventive Medication ◽  
The Right

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.

scholarly journals 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)

2019 ◽  
Vol 26 (14) ◽  
pp. 1534-1544 ◽  
Author(s):  
Xavier Rossello ◽  
Jannick AN Dorresteijn ◽  
Arne Janssen ◽  
Ekaterini Lambrinou ◽  
Martijn Scherrenberg ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Clinical Practice ◽  
Risk Prediction ◽  
European Association ◽  
Risk Measures ◽  
Preventive Cardiology ◽  
Prediction Tools ◽  
Risk Algorithm ◽  
Preventive Medication ◽  
The Right

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.

Cardiovascular Disease Risk Prediction - Integration into Clinical Practice

2013 ◽  
Vol 7 (5) ◽  
pp. 346-353 ◽  
Author(s):  
Thura T. Abd ◽  
Michael J. Blaha ◽  
Roger S. Blumenthal ◽  
Parag H. Joshi
Keyword(s):  
Cardiovascular Disease ◽  
Clinical Practice ◽  
Risk Prediction ◽  
Disease Risk ◽  
Cardiovascular Disease Risk

Stress bei Patienten: Stress als Prognosefaktor für Re-Infarkte bei koronarer Herzkrankheit

2018 ◽  
Vol 7 (05) ◽  
pp. 379-383
Author(s):  
Jian Li ◽  
Peter Angerer
Keyword(s):  
Cardiovascular Disease ◽  
Clinical Practice ◽  
Disease Prevention ◽  
Cardiac Rehabilitation ◽  
European Society ◽  
European Association ◽  
Cardiovascular Prevention ◽  
Cardiovascular Disease Prevention ◽  
European Guidelines ◽  
European Society Of Cardiology

ZusammenfassungBisher wurde Stress als Prognosefaktor bei koronarer Herzkrankheit nur wenig beachtet. Wir möchten in diesem Artikel einen aktualisierten und umfassenden Überblick darüber geben, welche Rolle Stress bei der Prognose der koronaren Herzkrankheit spielen könnte. Stress wurde in unterschiedlichen Domänen gemessen. Die Synthese der Forschungsevidenz lässt vermuten, dass Stress das Risiko für wiederholte klinische Ereignisse bei Patienten mit koronarer Herzkrankheit um 55% (95%-Konfidenzintervall 32 – 83%) erhöhen kann. Die „European Guidelines on Cardiovascular Disease Prevention in Clinical Practice“, 2016 von der European Society of Cardiology veröffentlicht, weisen besonders auf die Rolle von Stress und psychosozialen Risikofaktoren hin. Insbesondere die „Cardiac Rehabilitation Section“ der European Association of Cardiovascular Prevention and Rehabilitation schlägt eine 2-stufige Evaluation eines potenziellen Risikos durch Stress für die klinisch-kardiologische Praxis vor.

scholarly journals Update on cardiovascular prevention in clinical practice: A position paper of the European Association of Preventive Cardiology of the European Society of Cardiology

2019 ◽  
Vol 27 (2) ◽  
pp. 181-205 ◽  
Author(s):  
Massimo F Piepoli ◽  
Ana Abreu ◽  
Christian Albus ◽  
Marco Ambrosetti ◽  
Carlos Brotons ◽  
...  
Keyword(s):  
Clinical Practice ◽  
European Society ◽  
European Association ◽  
Task Force ◽  
Cardiovascular Prevention ◽  
Population Level ◽  
Population Based ◽  
Preventive Cardiology ◽  
European Society Of Cardiology ◽  
Disease Specific

European guidelines on cardiovascular prevention in clinical practice were first published in 1994 and have been regularly updated, most recently in 2016, by the Sixth European Joint Task Force. Given the amount of new information that has become available since then, components from the task force and experts from the European Association of Preventive Cardiology of the European Society of Cardiology were invited to provide a summary and critical review of the most important new studies and evidence since the latest guidelines were published. The structure of the document follows that of the previous document and has six parts: Introduction (epidemiology and cost effectiveness); Cardiovascular risk; How to intervene at the population level; How to intervene at the individual level; Disease-specific interventions; and Settings: where to intervene? In fact, in keeping with the guidelines, greater emphasis has been put on a population-based approach and on disease-specific interventions, avoiding re-interpretation of information already and previously considered. Finally, the presence of several gaps in the knowledge is highlighted.

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