José Miguel Rivera-Caravaca1,2, Olivier Piot3, Inmaculada Roldán-Rabadán4, Arnaud Denis5, Manuel Anguita6, Jacques Mansourati7, Alejandro Pérez-Cabeza8, Eloi Marijon9, Javier García-Seara10, Christophe Leclercq11, Ignacio García-Bolao12, Nicolas Lellouche13, Tatjana Potpara14,15, Giuseppe Boriani16, Laurent Fauchier17, Gregory Y H Lip2,18, Francisco Marín2. 1. Department of Cardiology, Hospital Clínico Universitario Virgen de la Arrixaca, University of Murcia, Instituto Murciano de Investigación Biosanitaria (IMIB-Arrixaca), CIBERCV, Murcia, Spain. 2. Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart and Chest Hospital, Liverpool, United Kingdom. 3. Département de Rythmologie-Cardiologie 2, Centre Cardiologique du Nord, Saint-Denis, France. 4. Department of Cardiology, Hospital Universitario La Paz, Madrid, Spain. 5. Département de Rythmologie, CHU Bordeaux, LIRYC Institute, Bordeaux-Pessac, France. 6. Department of Cardiology, Hospital Universitario Reina Sofía, Universidad de Córdoba, Instituto Maimónides de Investigación Biomédica (IMIBIC), Córdoba, Spain. 7. Department of Cardiology, Hôpital Cavale Blanche, CHRU Brest, Brest, France. 8. Department of Cardiology, Hospital Clínico Universitario Virgen de la Victoria, CIBERCV, Málaga, Spain. 9. Department of Cardiology, European Georges Pompidou Hospital, Paris, France. 10. Department of Cardiology, Hospital Universitario de Santiago de Compostela, CIBERCV, Santiago de Compostela, Spain. 11. Department of Cardiology, University of Rennes, CHU Rennes, Rennes, France. 12. Department of Cardiology, Clínica Universidad de Navarra, IdiSNA, Navarra Institute for Health Research, Pamplona, Spain. 13. Department of Cardiology, Hôpital Henri Mondor, Assistance Publique Hôpitaux de Paris, Creteil, France. 14. School of Medicine, Belgrade University, Belgrade, Serbia. 15. Cardiology Clinic, Clinical Centre of Serbia, Belgrade, Serbia. 16. Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, Modena, Italy. 17. Department of Cardiology, Centre Hospitalier Universitaire Trousseau et Faculté de Médecine, EA7505, Université de Tours, France. 18. Department, Denmarkof Clinical Medicine, Aalborg Thrombosis Research Unit, Aalborg University, Aalborg, Denmark.
Abstract
AIMS: The 4S-AF scheme [Stroke risk, Symptom severity, Severity of atrial fibrillation (AF) burden, Substrate severity] has recently been described as a novel approach to in-depth characterization of AF. We aim to determine if the 4S-AF scheme would be useful for AF characterization and provides prognostic information in real-world AF patients. METHODS AND RESULTS: The Spanish and French cohorts of the EORP-AF Long-Term General Registry were included. The baseline 4S-AF scheme was calculated and related to the primary management strategy (rhythm or rate control). Follow-up was performed at 1-year with all-cause mortality and the composite of ischaemic stroke/transient ischaemic attack/systemic embolism, major bleeding, and all-cause death, as primary endpoints. A total of 1479 patients [36.9% females, median age 72 interquartile range (IQR 64-80) years] were included. The median 4S-AF scheme score was 5 (IQR 4-7). The 4S-AF scheme, as continuous and as categorical, was associated with the management strategy decided for the patient (both P < 0.001). The predictive performances of the 4S-AF scheme for the actual management strategy were appropriate in its continuous [c-index 0.77, 95% confidence interval (CI) 0.75-0.80] and categorical (c-index 0.75, 95% CI 0.72-0.78) forms. Cox regression analyses showed that 'red category' classified patients in the 4S-AF scheme had a higher risk of all-cause death (aHR 1.75, 95% CI 1.02-2.99) and composite outcomes (aHR 1.60, 95% CI 1.05-2.44). CONCLUSION: Characterization of AF by using the 4S-AF scheme may aid in identifying AF patients that would be managed by rhythm or rate control and could also help in identifying high-risk AF patients for worse clinical outcomes in a 'real-world' setting. Published on behalf of the European Society of Cardiology. All rights reserved.
AIMS: The 4S-AF scheme [Stroke risk, Symptom severity, Severity of atrial fibrillation (AF) burden, Substrate severity] has recently been described as a novel approach to in-depth characterization of AF. We aim to determine if the 4S-AF scheme would be useful for AF characterization and provides prognostic information in real-world AF patients. METHODS AND RESULTS: The Spanish and French cohorts of the EORP-AF Long-Term General Registry were included. The baseline 4S-AF scheme was calculated and related to the primary management strategy (rhythm or rate control). Follow-up was performed at 1-year with all-cause mortality and the composite of ischaemic stroke/transient ischaemic attack/systemic embolism, major bleeding, and all-cause death, as primary endpoints. A total of 1479 patients [36.9% females, median age 72 interquartile range (IQR 64-80) years] were included. The median 4S-AF scheme score was 5 (IQR 4-7). The 4S-AF scheme, as continuous and as categorical, was associated with the management strategy decided for the patient (both P < 0.001). The predictive performances of the 4S-AF scheme for the actual management strategy were appropriate in its continuous [c-index 0.77, 95% confidence interval (CI) 0.75-0.80] and categorical (c-index 0.75, 95% CI 0.72-0.78) forms. Cox regression analyses showed that 'red category' classified patients in the 4S-AF scheme had a higher risk of all-cause death (aHR 1.75, 95% CI 1.02-2.99) and composite outcomes (aHR 1.60, 95% CI 1.05-2.44). CONCLUSION: Characterization of AF by using the 4S-AF scheme may aid in identifying AF patients that would be managed by rhythm or rate control and could also help in identifying high-risk AF patients for worse clinical outcomes in a 'real-world' setting. Published on behalf of the European Society of Cardiology. All rights reserved.