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1. Can individual fatty acids be used as functional biomarkers of dairy fat consumption in relation to cardiometabolic health? A narrative review.

Author

Sellem L, Jackson KG, Paper L, Givens ID, and Lovegrove JA

Subjects
Animals, Humans, Fatty Acids, Prospective Studies, Cross-Sectional Studies, Dietary Fats, Dairy Products, Biomarkers, Diabetes Mellitus, Type 2, Cardiovascular Diseases
Abstract

In epidemiological studies, dairy food consumption has been associated with minimal effect or decreased risk of some cardiometabolic diseases (CMD). However, current methods of dietary assessment do not provide objective and accurate measures of food intakes. Thus, the identification of valid and reliable biomarkers of dairy product intake is an important challenge to best determine the relationship between dairy consumption and health status. This review investigated potential biomarkers of dairy fat consumption, such as odd-chain, trans- and branched-chain fatty acids (FA), which may improve the assessment of full-fat dairy product consumption. Overall, the current use of serum/plasma FA as biomarkers of dairy fat consumption is mostly based on observational evidence, with a lack of well-controlled, dose-response intervention studies to accurately assess the strength of the relationship. Circulating odd-chain SFA and trans-palmitoleic acid are increasingly studied in relation to CMD risk and seem to be consistently associated with a reduced risk of type 2 diabetes in prospective cohort studies. However, associations with CVD are less clear. Overall, adding less studied FA such as vaccenic and phytanic acids to the current available evidence may provide a more complete assessment of dairy fat intake and minimise potential confounding from endogenous synthesis. Finally, the current evidence base on the direct effect of dairy fatty acids on established biomarkers of CMD risk (e.g. fasting lipid profiles and markers of glycaemic control) mostly derives from cross-sectional, animal and in vitro studies and should be strengthened by well-controlled human intervention studies.

Published
2022
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2. 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 X, Dorresteijn JA, Janssen A, Lambrinou E, Scherrenberg M, Bonnefoy-Cudraz E, Cobain M, Piepoli MF, Visseren FL, Dendale P, and This Paper Is A Co-Publication Between European Journal Of Preventive Cardiology European Heart Journal Acute Cardiovascular Care And European Journal Of Cardiovascular Nursing

Subjects
Cardiovascular Diseases diagnosis, Cardiovascular Diseases epidemiology, Clinical Decision-Making, Humans, Predictive Value of Tests, Prognosis, Risk Assessment, Risk Factors, Time Factors, Algorithms, Cardiovascular Diseases prevention & control, Decision Support Techniques, Preventive Health Services
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.

Published
2019
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3. Prevalence of cardiovascular risk factors among 28,000 employees.

Author

Scheerbaum M, Langenbach C, Scheerbaum P, Heidemann F, Rieß HC, Heigel H, Debus SE, and Behrendt CA

Subjects
Adolescent, Adult, Aged, Cardiovascular Diseases diagnosis, Cross-Sectional Studies, Diabetes Mellitus diagnosis, Diabetes Mellitus epidemiology, Female, Germany epidemiology, Health Surveys, Humans, Hypercholesterolemia diagnosis, Hypercholesterolemia epidemiology, Hypertension diagnosis, Hypertension epidemiology, Male, Middle Aged, Obesity diagnosis, Prevalence, Prognosis, Risk Assessment, Risk Factors, Smoking adverse effects, Smoking epidemiology, Time Factors, Young Adult, Cardiovascular Diseases epidemiology, Obesity epidemiology, Occupational Health
Abstract

Background: Cardiovascular diseases are the leading cause of death in Germany. The knowledge of causal risk factors and their distribution is of utmost importance to design screening programs., Probands and Methods: In this cross-sectional study design we used STROBE criteria to achieve the highest comparability possible. Anthropometric measures (height and weight), total cholesterol, glucose level, and blood pressure were measured. Probands' history was collected by using a standardized questionnaire. The data was age- and gender-adjusted for the working population 16 to 70 years of age, derived from the micro census, the 1 %-sample census of the German statistical office. For each study year weight factors were calculated. Logistic regression analysis was conducted regarding the cardiovascular risk factors: smoking, arterial hypertension, diabetes, hypercholesterolemia, and obesity., Results: Between 2006 and 2015 a total of 28,293 employees took part in the ongoing company screenings. The mean age was 42.3 years for both sexes (median: 43 years). The mean body mass index (BMI) was 25.6 kg/m 2 (men: 26.5 kg/m 2 , women: 24.7 kg/m 2 ). A history of hypertension was present in 16 % of the employees (men: 17.8 %, women: 13.8 %). Of the respondents 2 % suffered from diabetes (men: 2.4 %, women: 1.6 %). Lipid-lowering drugs were taken by 2.8 % of all employees (3.6 % men and 1.9 % women). 23.3 % of the men and women indicated to be active smokers. In the regression analysis obesity was associated with a four times higher risk of hypertension and a three times higher risk of elevated glucose levels, thus manifesting as main contributor for vascular diseases. Meanwhile the risk for obesity was 140 % higher in probands who are former smokers., Conclusions: We regard obesity as the number one cardiovascular risk which should be assessed by various medical, legislative, and socio-economic actions to limit future mortality and health-care costs in Germany.

Published
2017
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5. 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

6. Blunting periprocedural myocardial necrosis: Rationale and design of the randomized ALPHEUS study

Author

François Jourda, Christophe Saint-Etienne, Luc Christiaens, Grégoire Rangé, Benoit Lattuca, Philippe Brunel, Paul Guedeney, Hervé Le Breton, Marie Hauguel-Moreau, Eric Vicaut, Anne Bellemain-Appaix, Jean-Louis Georges, Guillaume Cayla, Christophe Pouillot, Christophe Caussin, Gregory Ducrocq, Ziad Boueri, Farzin Beygui, Johanne Silvain, Thibault Lhermusier, Gilles Montalescot, Jean-Noël Labèque, Jean-Philippe Collet, Zuzana Motovska, Franck Boccara, Mohamad El Kasty, Raphaelle Dumaine, Jean-Guillaume Dillinger, Mikael Laredo, Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases [IHU ICAN], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Institut de Cardiométabolisme et Nutrition = Institute of Cardiometabolism and Nutrition [CHU Pitié Salpêtrière] (IHU ICAN), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Hôpital Universitaire Carémeau [Nîmes] (CHU Nîmes), Centre Hospitalier Universitaire de Nîmes (CHU Nîmes), Service de cardiologie et de pathologie vasculaire [CHU Caen], Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Tumorothèque de Caen Basse-Normandie (TCBN), Service de cardiologie [Chartres], Les hôpitaux de Chartres [Chartres], Marqueurs cardiovasculaires en situation de stress (MASCOT (UMR_S_942 / U942)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Groupe Hospitalier Saint Louis - Lariboisière - Fernand Widal [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPC)-Université Sorbonne Paris Nord, Hôpital de Bastia, Service de Cardiologie [Hôpital privé Dijon Bourgogne], Hôpital privé Dijon Bourgogne, Clinique Sainte Clotilde, Centre de Recherche Saint-Antoine (CRSA), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Service de cardiologie [CHU de Poitiers], Centre hospitalier universitaire de Poitiers (CHU Poitiers), Service de cardiologie [Centre Hospitalier de la Côte Basque, Bayonne], Centre Hospitalier de la Côte Basque, CHU Toulouse [Toulouse], Centre Hospitalier de Versailles André Mignot (CHV), Cardiology Department, Centre Hospitalier d'Antibes Juan les Pins, Antibes, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Pontchaillou [Rennes], Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Sud - Paris 11 (UP11)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Trousseau [APHP], Institut Mutualiste de Montsouris (IMM), Hôpital d'Auxerre, Partenaires INRAE, Grand Hôpital de l'Est Francilien (GHEF), Laboratoire de Recherche Vasculaire Translationnelle (LVTS (UMR_S_1148 / U1148)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPC)-Université Sorbonne Paris Nord, AstraZeneca France Novartis Daiichi-Sankyo Bristol-Myers Squibb, BMS Eli Lilly and Company Bayer AstraZeneca France Boston Scientific Corporation, BSC Abbott Laboratories Medtronic Biotronik Fédération Française de Cardiologie, FFC, The ALPHEUS and the Bio-ALPHEUS studies are funded by the Fond de dotation ACTION ( www.action-fonds.org ) and a grant from AstraZeneca . The Bio-ALPHEUS study is also funded by the Institute of Cardiometabolism and Nutrition . The first draft of the paper was developed by Dr Silvain and Dr Montalescot, and all authors subsequently contributed to its development and final content and are solely responsible for the design and conduct of this study, all study analyses, the drafting and editing of the paper, and its final contents. AstraZeneca reviewed the manuscript and was allowed to make suggestions, but final content was determined by the authors., Dr Silvain reports receiving consulting and lecture or travel support from AstraZeneca, Bayer HealthCare SAS, Biotronik, BPI France, Boehringer Ingelheim France, CSL Behring SA, Gilead Science, Sanofi-Aventis France, Terumo France SAS, Abbott Medical France SAS, and Zoll and is a stockholder of Pharmaseeds. Dr Cayla reports speaker or congress fees and has received research grants/consultant fees/lectures fees from Amgen, AstraZeneca, Abbott, Bayer, Biotronik, Bristol-Myers Squibb, Pfizer, and Sanofi-Aventis. Dr Beygui reports receiving consulting and lecture fees from Astrazeneca, Bristol-Myers Squibb, Medtronic, Biosensors, Boston Scientific Institutional and research grants from Medtronic, Biosensors, Acist, and Boston scientific. Dr Rangé reports receiving speaker’s and/or consulting fees from Abbott. Dr Lattuca has received research grants from Biotronik, Boston Scientific, Daiichi-Sankyo, Fédération Française de Cardiologie, and Institute of CardioMetabolism and Nutrition, consultant fees from Daiichi-Sankyo and Eli Lilly, and lecture fees from AstraZeneca, Medtronic, and Novartis. Dr Collet reports receiving consulting and lecture fees from AstraZeneca, Bayer, Bristol-Myers Squibb, Fédération Française de Cardiologie, Lead-Up, Medtronic, MSD, Sanofi-Aventis, and WebMD. Dr Dillinger reports receiving consulting and lecture fees from AstraZeneca, Bayer, Boehringer-Ingelheim, Bristol-Myers Squibb/Pfizer, and Sanofi and grants from Bayer, Bristol-Myers Squibb/Pfizer, and Biosensors. Dr Boueri reports receiving consulting and lecture fees from Novartis and Astra Zeneca. Dr Boccara reports consulting or speaker fees from Amgen, Gilead, ViiV Healthcare, Amgen, Sanofi, MSD, and Servier outside the submitted work. Dr Christiaens reports consulting or speaker fees from Astra Zeneca. Dr Lhermusier reports consulting or speaker fees from Astra Zeneca, Boston Scientifics, and Abbott and a research grant from Astra Zeneca. Dr Georges reports consulting or speaker fees from AstraZeneca France, Sanofi-Aventis, Amgen, and Merck Sharpe and Dohme. Dr Bellemain-Appaix reports consulting or speaker fees from Astra Zeneca, Novartis, and Pfizer. Dr Saint-Etienne reports consulting or speaker fees from Abbott, Medtronic, Edwards, and Biotronik. Dr Motovska reports consulting or speaker fees from Astrazeneca. Dr Laredo reports fellowship grants from Medtronic, Biotronik, and Boston Scientific. Dr Ducrocq reports consulting or speaker fees from Amgen, Astra Zeneca, Bayer, BMS, Janssen, Sanofi, and Terumo, proctoring: Boston scientific, CEC: Novo Nordisk, and travel fees: Astra Zeneca, Bayer, and BMS. Dr Vicaut reports consulting or speaker fees from Abbott, Bristol Myers Squibb, Celgene, Edwards, Pfizer, Sanofi, and Novartis. Dr Montalescot reports consulting or speaker fees from Abbott, AIM group, Amgen, Actelion, American College of Cardiology Foundation, Astrazeneca, Axis-Santé, Bayer, Boston-Scientific, Bristol-Myers Squibb, Beth Israel Deaconess Medical, Brigham Women’s Hospital, Fréquence Médicale, ICOM, Idorsia, Elsevier, Fédération Française de Cardiologie, Fréquence Médicale, Institute of Cardiometabolism and Nutrition, Lead-Up, Menarini, Medtronic, MSD, Novo-Nordisk, Pfizer, Quantum Genomics, Sanofi-Aventis, SCOR global life, Servier, and WebMD. Other authors have no conflict of interest to report., Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Université Sorbonne Paris Nord, Centre de Recherche Saint-Antoine (CR Saint-Antoine), Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Saint-Antoine [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris-Sud - Paris 11 (UP11)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Université Sorbonne Paris Nord, Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, Centre Hospitalier de la Côte Basque (CHCB), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre hospitalier d'Auxerre (CHA), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord

Subjects
medicine.medical_specialty, Ticlopidine, medicine.medical_treatment, Myocardial Infarction, Coronary Disease, 030204 cardiovascular system & hematology, Coronary Angiography, Loading dose, Coronary artery disease, 03 medical and health sciences, 0302 clinical medicine, Percutaneous Coronary Intervention, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Internal medicine, medicine, Humans, 030212 general & internal medicine, Myocardial infarction, cardiovascular diseases, Aged, Aspirin, business.industry, Percutaneous coronary intervention, medicine.disease, Clopidogrel, 3. Good health, Conventional PCI, Cardiology, Purinergic P2Y Receptor Antagonists, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Cardiology and Cardiovascular Medicine, business, Ticagrelor, Platelet Aggregation Inhibitors, medicine.drug
Abstract

International audience; Background: Clopidogrel associated with aspirin is the recommended treatment for patients undergoing elective percutaneous coronary intervention (PCI). Although severe PCI-related events are rare, evidence suggests that PCI-related myocardial infarction and myocardial injury are frequent complications that can impact the clinical prognosis of the patients. Antiplatelet therapy with a potent P2Y12 receptor inhibitor such as ticagrelor may reduce periprocedural ischemic complications while maintaining a similar safety profile as compared with conventional dual antiplatelet therapy by aspirin and clopidogrel in this setting. Methods: Assessment of Loading with the P2Y12 inhibitor ticagrelor or clopidogrel to Halt ischemic Events in patients Undergoing elective coronary Stenting (ALPHEUS) (NCT02617290) is an international, multicenter, randomized, parallel-group, open-label study in patients with stable coronary artery disease who are planned for an elective PCI. In total, 1,900 patients will be randomized before a planned PCI to a loading dose of ticagrelor 180 mg or a loading dose of clopidogrel (300 or 600 mg) in addition to aspirin. Patients will then receive a dual antiplatelet therapy with aspirin and ticagrelor 90 mg twice daily or clopidogrel 75 mg once daily for 30 days. The primary ischemic end point is PCI-related myocardial infarction (myocardial infarction type 4a or 4b) or major myocardial injury within 48 hours (or at hospital discharge if earlier) after elective PCI/stent. Safety will be evaluated by major bleeding events (Bleeding Academic Research Consortium type 3 or 5) at 48 hours (or discharge if it occurs earlier). Conclusion: ALPHEUS is the first properly sized trial comparing ticagrelor to clopidogrel in the setting of elective PCI and is especially designed to show a reduction in periprocedural events, a surrogate end point for mortality.

Published
2020

7. Long-term risk of stroke and its predictors in transient ischaemic attack patients in Germany

Author

Karel Kostev, Louis Jacob, Christian Tanislav, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), and The authors have received no financial support for the research, authorship and/or publication of this paper.

Subjects
Male, associated predictors, Cohort Studies, 0302 clinical medicine, general practices, Germany, Atrial Fibrillation, 030212 general & internal medicine, Stroke, Aged, 80 and over, Incidence, Hazard ratio, Age Factors, Atrial fibrillation, Middle Aged, stroke, 3. Good health, Neurology, Ischemic Attack, Transient, Hypertension, Cohort, Platelet aggregation inhibitor, Female, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Risk, medicine.medical_specialty, transient ischaemic attack, 03 medical and health sciences, Sex Factors, Diabetes mellitus, Internal medicine, parasitic diseases, medicine, Humans, long-term risk, In patient, cardiovascular diseases, Aged, Ischemic Stroke, business.industry, Anticoagulants, Protective Factors, medicine.disease, nervous system diseases, Long term risk, Neurology (clinical), business, Platelet Aggregation Inhibitors, 030217 neurology & neurosurgery
Abstract

International audience; Background and purpose: Little is known about the long-term association between transient ischaemic attack (TIA) and stroke. Therefore, the goal of this study was to analyze the long-term risk of stroke and associated predictors in a large cohort of TIA patients followed in general practices in Germany. Methods: This study included patients with an initial TIA diagnosis and subsequently followed up in one of 1262 general practices in Germany between January 2007 and December 2016 (N = 19 824 patients). The primary outcome of the study was the risk of ischaemic stroke within 10 years of the initial diagnosis of TIA. The secondary outcome was the identification of demographic, clinical and pharmaceutical variables significantly associated with stroke in TIA patients. Results: Within 10 years of the initial TIA diagnosis, 18.3% of individuals were diagnosed with stroke. Age was positively associated with stroke, with hazard ratios ranging from 1.88 in patients aged 51–60 years to 4.00 in those aged >80 years (reference group: patients aged ≤50 years). Furthermore, male sex, hypertension, diabetes mellitus, atrial fibrillation and ischaemic heart diseases had an additional impact on the risk of stroke. Finally, new oral anticoagulants, heparins, diuretics, angiotensin II receptor blockers and platelet aggregation inhibitors were identified as protective factors. Conclusions: In a cohort of almost 20 000 TIA patients, 18.3% were diagnosed with stroke within 10 years after the TIA index event. Several demographic, clinical and pharmaceutical variables significantly predicted the long-term risk of stroke in TIA patients.

Published
2020

8. Cluster Analysis of Physical Activity Patterns, and Relationship with Sedentary Behavior and Healthy Lifestyles in Prepubertal Children: Genobox Cohort

Author

Gloria Bueno, Francisco Jesus Llorente-Cantarero, Concepción M. Aguilera, Juan Jose Bedoya-Carpente, Augusto Anguita-Ruiz, Mercedes Gil-Campos, Jose Manuel Jurado-Castro, Rosaura Leis, Azahara Iris-Rupérez, Rocío Vázquez-Cobela, Universidade de Santiago de Compostela. Departamento de Ciencias Forenses, Anatomía Patolóxica, Xinecoloxía e Obstetricia, e Pediatría, [Leis,R, Bedoya-Carpente,JJ, Vázquez-Cobela,R] Unidad de Investigación en Nutrición, Crecimiento y Desarrollo Humano de Galicia, Departamento de Pediatría, Hospital Clínico Universitario de Santiago, Universidad de Santiago de Compostela, IDIS, Santiago de Compostela, Spain. [Leis,R, Llorente-Cantarero,FJ, Anguita-Ruiz,A, Vázquez-Cobela,R, Aguilera,CM, Bueno,G, Gil-Campos,M] CIBEROBN, (Physiopathology of Obesity and Nutrition) Institute of Health Carlos III (ISCIII), Madrid, Spain. [Jurado-Castro,JM, Gil-Campos,M] Metabolism and Investigation Unit, Reina Sofia University Hospital, Maimónides Institute of Biomedicine Research of Córdoba (IMIBIC), University of Córdoba, Córdoba, Spain. [Llorente-Cantarero,FJ] Department of Artistic and Corporal Education, Faculty of Education, University of Córdoba, Córdoba, Spain. [Anguita-Ruiz,A, Aguilera,CM] Department of Biochemistry and Molecular Biology II, Institute of Nutrition and Food Technology 'José Mataix', Center of Biomedical Research, University of Granada, Armilla, Granada, Spain. [Anguita-Ruiz,A, Aguilera,CM] Instituto de Investigación Biosanitaria ibs, Granada, Spain. [Iris-Rupérez,A] GENUD Research Group, University of Zaragoza, Instituto Agroalimentario de Aragón (IA2), Instituto de Investigación Sanitaria (IIS) Aragón, Zaragoza, Spain. [Bueno,G] Unidad de Endocrinología Pediátrica, Hospital Clínico Lozano Blesa, Facultad de Medicina, Universidad de Zaragoza, Zaragoza, Spain., and This work was supported bythe Plan Nacional de Investigación Científica, Desarrollo e InnovaciónTecnológica (I + D + I), Instituto de Salud Carlos III-Health Research Funding (FONDOS FEDER) (PI051968, PI1102042 and PI1600871) and Redes temáticas de investigación cooperativa RETIC (Red SAMID RD12/0026/0015). The authors also acknowledge Instituto de Salud Carlos III for personal funding of A.A.-R: Contratos i-PFIS: doctorados IIS empresa en ciencias y tecnologías de la salud de la convocatoria 2017 de la Acción Estratégica en Salud 2013–2016 (IFI17/00048).This paper will be included in J.M.J.-C. doctorate, under the 'Social and Legal Sciences Program' at theUniversity of Córdoba, Spain.

Subjects
Male, obesity, Mediterranean diet, Health Behavior, Obesidad, Child Behavior, Diet, Mediterranean, Organisms::Eukaryota::Animals::Chordata::Vertebrates::Mammals::Primates::Haplorhini::Catarrhini::Hominidae::Humans [Medical Subject Headings], Cohort Studies, 0302 clinical medicine, Surveys and Questionnaires, Cluster Analysis, Insulin, 030212 general & internal medicine, skin and connective tissue diseases, Child, Chemicals and Drugs::Lipids::Glycerides::Triglycerides [Medical Subject Headings], Nutrition and Dietetics, exercise, Psychiatry and Psychology::Behavior and Behavior Mechanisms::Behavior::Health Behavior [Medical Subject Headings], Analytical, Diagnostic and Therapeutic Techniques and Equipment::Therapeutics::Nutrition Therapy::Diet Therapy::Diet, Mediterranean [Medical Subject Headings], Analytical, Diagnostic and Therapeutic Techniques and Equipment::Equipment and Supplies::Electrical Equipment and Supplies [Medical Subject Headings], Conducta sedentaria, Ejercicio físico, Cardiovascular diseases, Psychiatry and Psychology::Behavior and Behavior Mechanisms::Behavior::Child Behavior [Medical Subject Headings], Cohort, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Data Collection::Health Surveys::Nutrition Surveys::Diet Surveys [Medical Subject Headings], Female, Anthropology, Education, Sociology and Social Phenomena::Human Activities::Leisure Activities::Recreation::Sports [Medical Subject Headings], Club, Enfermedades cardiovasculares, lcsh:Nutrition. Foods and food supply, Sports, musculoskeletal diseases, Electrical Equipment and Supplies, Anatomy::Digestive System::Pancreas::Islets of Langerhans::Insulin-Secreting Cells [Medical Subject Headings], Physical activity, Check Tags::Male [Medical Subject Headings], 030209 endocrinology & metabolism, lcsh:TX341-641, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Statistics as Topic::Cluster Analysis [Medical Subject Headings], Disease cluster, Article, Information Science::Information Science::Data Collection::Questionnaires [Medical Subject Headings], 03 medical and health sciences, Screen time, Environmental health, Anthropology, Education, Sociology and Social Phenomena::Human Activities::Exercise [Medical Subject Headings], medicine, Humans, Persons::Persons::Age Groups::Child [Medical Subject Headings], Healthy Lifestyle, Obesity, Exercise, Triglycerides, business.industry, Psychiatry and Psychology::Behavior and Behavior Mechanisms::Psychology, Social::Life Style [Medical Subject Headings], Anthropometry, medicine.disease, Dieta mediterránea, cardiovascular diseases, stomatognathic diseases, Check Tags::Female [Medical Subject Headings], Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Epidemiologic Study Characteristics as Topic::Epidemiologic Studies::Cohort Studies [Medical Subject Headings], Sedentary Behavior, business, Food Science
Abstract

The authors would like to thank the children and parents who participated in the study and Ana Yara Postigo-Fuentes for the assistance with the English editing., Sedentary habits during childhood are associated with adverse health outcomes. The aim of this work was to cluster lifestyle behaviors and metabolic biomarkers to establish different patterns in children. Their physical and sedentary activities were evaluated by accelerometry, and questionnaires that included lifestyle behaviors, such as adherence to a Mediterranean diet, anthropometry and blood biochemical markers. Cluster analysis was performed to establish different groups based on physical activity levels. A total of 489 children were finally selected. Cluster 1 included children with a mostly sedentary state, whereas Cluster 3 included the most active children and Cluster 2 included children that did not fit into either the sedentary or the highly active groups. In Cluster 3, 56% of children were in a sports club, and a lower percentage used electronic devices in their rooms compared to the other groups. Cluster 1 children exhibited higher insulin, HOMA-IR and triacylglycerides with respect to the other groups. No differences were found regarding adherence to a Mediterranean diet. The choice to practice an extracurricular sport could be an influencing factor to increase exercise and ensure an active lifestyle in children. Reducing or limiting screen time mainly in children’s rooms could contribute to an active lifestyle., Plan Nacional de Investigacion Cientifica, Desarrollo e InnovacionTecnologica (I + D + I), Instituto de Salud Carlos III-Health Research Funding (FONDOS FEDER) PI051968 PI1102042 PI1600871, Redes tematicas de investigacion cooperativa RETIC (Red SAMID) RD12/0026/0015, Instituto de Salud Carlos III IFI17/00048

Published
2020