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1. 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

Xavier Rossello, Jannick AN Dorresteijn, Arne Janssen, Ekaterini Lambrinou, Martijn Scherrenberg, Eric Bonnefoy-Cudraz, Mark Cobain, Massimo F Piepoli, Frank LJ Visseren, Paul Dendale, null This paper is a co-publication betw, Centro Nacional de Investigaciones Cardiovasculares Carlos III [Madrid, Spain] (CNIC), Instituto de Salud Carlos III [Madrid] (ISC), Centro de Investigación Biomédica en Red en Enfermedades Cardiovasculares (CIBERCV), University Medical Center [Utrecht], Jessa Ziekenhuis [Hasselt], Cyprus University of Technology, Hasselt University (UHasselt), Cardiovasculaire, métabolisme, diabétologie et nutrition (CarMeN), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Hospices Civils de Lyon (HCL), Service de Cardiologie Lyon (Hôpital Louis Pradel [CHU - HCL]), Hôpital Louis Pradel [CHU - HCL], Hospices Civils de Lyon (HCL)-Hospices Civils de Lyon (HCL), Imperial College London, University of Southern California (USC), Rossello, Xavier/0000-0001-6783-8463, 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, CarMeN, laboratoire, Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

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
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

Published
2020
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2. Physical functional performance and prognosis in patients with heart failure: a systematic review and meta-analysis

Author

Antonio Cuesta-Vargas, Ricardo Gómez-Huelgas, María Rosa Bernal-López, Iván José Fuentes-Abolafio, Brendon Stubbs, Luis M. Pérez-Belmonte, [Fuentes-Abolafio,IJ, Cuesta-Vargas,AI] Department of Physiotherapy, Faculty of Health Science, University of Malaga, The Institute of Biomedical Research in Malaga (IBIMA), Clinimetric Group FE-14, Malaga, Spain. [Stubbs,B] Physiotherapy Department, South London and Maudsley NHS Foundation Trust, Denmark Hill, London, UK. [Stubbs,B] Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK. [Stubbs,B] Positive Ageing Research Intitute (PARI), Faculty of Health Social Care and Education, Anglia Ruskin University, Chelmsford, UK. [Pérez-Belmonte,LM, Bernal-López,MR, Gómez-Huelgas,R] Internal Medicine Department, Instituto de Investigación Biomédica de Malaga (IBIMA), Regional University Hospital of Málaga, Málaga, Spain. [Pérez-Belmonte,LM] Unidad de Neurofisiología Cognitiva, Centro de Investigaciones Médico Sanitarias (CIMES), Instituto de Investigación Biomédica de Málaga (IBIMA), Universidad de Málaga (UMA), Campus de Excelencia Internacional (CEI) Andalucía Tech, Málaga, Spain. [Pérez-Belmonte,LM] Centro de Investigación Biomédica en Red Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain. [Bernal-López,MR, Gómez-Huelgas,R] CIBER Fisio-patología de la Obesidad y la Nutrición, Instituto de Salud Carlos III, Madrid, Spain. [Cuesta-Vargas,AI] School of Clinical Sciences, Faculty of Health at the Queensland University of Technology, Brisbane, Queensland, Australia., and Brendon Stubbs is supported by a Clinical Lectureship (ICA-CL-2017-03-001) jointly funded by Health Education England (HEE) and the National Institute for Health Research (NIHR). Brendon Stubbs is part funded by the NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust. Brendon Stubbs is also supported by the Maudsley Charity, King’s College London and the NIHR South London Collaboration for Leadership in Applied Health Research and Care (CLAHRC) funding. This paper presents independent research. The views expressed in this publication are those of the authors and not necessarily those of the acknowledged institutions. María Rosa Bernal-López was supported by 'Miguel Servet Type I' program (CP15/00028) from the ISCIII-Madrid (Spain), cofinanced by the Fondo Europeo de Desarrollo Regional-FEDER.

Subjects
Male, lcsh:Diseases of the circulatory (Cardiovascular) system, Hospitalización, Health Care::Health Care Quality, Access, and Evaluation::Quality of Health Care::Health Care Evaluation Mechanisms::Statistics as Topic::Probability::Risk::Risk Assessment [Medical Subject Headings], Walking, 030204 cardiovascular system & hematology, Organisms::Eukaryota::Animals::Chordata::Vertebrates::Mammals::Primates::Haplorhini::Catarrhini::Hominidae::Humans [Medical Subject Headings], 0302 clinical medicine, Risk Factors, Physical functional performance, Hospitalisation, Medicine, 030212 general & internal medicine, Phenomena and Processes::Musculoskeletal and Neural Physiological Phenomena::Musculoskeletal Physiological Phenomena::Musculoskeletal Physiological Processes::Movement::Motor Activity::Exercise::Walking [Medical Subject Headings], Persons::Persons::Age Groups::Adult::Aged [Medical Subject Headings], Aged, 80 and over, Insuficiencia cardíaca, Pronóstico, Middle Aged, Prognosis, Cardiac surgery, Hospitalization, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Therapeutics::Patient Care::Hospitalization [Medical Subject Headings], Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Epidemiologic Research Design::Sensitivity and Specificity::Predictive Value of Tests [Medical Subject Headings], Meta-analysis, Female, Gait Analysis, Cardiology and Cardiovascular Medicine, Research Article, medicine.medical_specialty, Check Tags::Male [Medical Subject Headings], Walk Test, Functional tests, Heart failure, CINAHL, Health Care::Health Care Quality, Access, and Evaluation::Quality of Health Care::Health Care Evaluation Mechanisms::Statistics as Topic::Probability::Risk::Risk Factors [Medical Subject Headings], Risk Assessment, 03 medical and health sciences, Predictive Value of Tests, Humans, In patient, Mortality, Aged, Angiology, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Diagnosis::Diagnostic Techniques and Procedures::Diagnostic Techniques, Cardiovascular::Heart Function Tests::Exercise Test [Medical Subject Headings], business.industry, Diseases::Cardiovascular Diseases::Heart Diseases::Heart Failure [Medical Subject Headings], Persons::Persons::Age Groups::Adult::Middle Aged [Medical Subject Headings], Evidence-based medicine, medicine.disease, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Diagnosis::Diagnostic Techniques and Procedures::Physical Examination::Gait [Medical Subject Headings], Functional Status, Check Tags::Female [Medical Subject Headings], lcsh:RC666-701, Persons::Persons::Age Groups::Adult::Aged::Aged, 80 and over [Medical Subject Headings], Mortalidad, Physical therapy, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Diagnosis::Prognosis [Medical Subject Headings], Observational study, business, Rendimiento físico funcional
Abstract

Background Patients with Heart Failure (HF) show impaired functional capacities which have been related to their prognosis. Moreover, physical functional performance in functional tests has also been related to the prognosis in patients with HF. Thus, it would be useful to investigate how physical functional performance in functional tests could determine the prognosis in patients with HF, because HF is the leading cause of hospital admissions for people older than 65 years old. This systematic review and meta-analysis aims to summarise and synthesise the evidence published about the relationship between physical functional performance and prognosis in patients with HF, as well as assess the risk of bias of included studies and the level of evidence per outcome. Methods Major electronic databases, such as PubMed, AMED, CINAHL, EMBASE, PEDro, Web of Science, were searched from inception to March 2020 for observational longitudinal cohort studies (prospective or retrospective) examining the relationship between physical functional performance and prognosis in patients with HF. Results 44 observational longitudinal cohort studies with a total of 22,598 patients with HF were included. 26 included studies reported a low risk of bias, and 17 included studies showed a moderate risk of bias. Patients with poor physical functional performance in the Six Minute Walking Test (6MWT), in the Short Physical Performance Battery (SPPB) and in the Gait Speed Test showed worse prognosis in terms of larger risk of hospitalisation or mortality than patients with good physical functional performance. However, there was a lack of homogeneity regarding which cut-off points should be used to stratify patients with poor physical functional performance from patients with good physical functional performance. Conclusion The review includes a large number of studies which show a strong relationship between physical functional performance and prognosis in patients with HF. Most of the included studies reported a low risk of bias, and GRADE criteria showed a low and a moderate level of evidence per outcome.

Published
2020