Javier de Juan Bagudá1, Juan J Gavira Gómez2, Marta Pachón Iglesias3, Rocío Cózar León4, Vanessa Escolar Pérez5, Óscar González Fernández6, Nuria Rivas Gándara7, Josebe Goirigolzarri Artaza8, Beatriz Díaz Molina9, Alfonso Macías Gallego10, Virgilio Martínez Mateo11, Juan G Martínez Martínez12, Natalia Marrero Negrín13, Gonzalo L Alonso Salinas14, Luis González Torres15, Juan F Delgado Jiménez16, Paula Sánchez-Aguilera3, Ernesto Díaz Infante4, María F Arcocha Torres5, Laura Peña Conde6, Ana B Méndez Fernández7, Nicasio Pérez Castellano8, José M Rubín López9, Inés Madrazo Delgado10, Manuel J Fernández-Anguita11, Pablo Ramos Ruiz17, Olga Medina Moreno13, David Cordero Pereda18, Carlos de Diego Rus15, Fernando Arribas Ynsaurriaga16, Ignacio García Bolao2, Rafael Salguero Bodes16. 1. Servicio de Cardiología, Hospital Universitario 12 de Octubre, Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), Madrid, Spain; Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Spain; Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Spain. Electronic address: javierdejuan166@hotmail.com. 2. Servicio de Cardiología, Clínica Universidad de Navarra, Pamplona, Navarra, Spain. 3. Servicio de Cardiología, Complejo Hospitalario Universitario de Toledo, Toledo, Spain. 4. Servicio de Cardiología, Hospital Universitario Virgen Macarena, Sevilla, Spain. 5. Servicio de Cardiología, Hospital Universitario de Basurto, Bilbao, Vizcaya, Spain. 6. Servicio de Cardiología, Hospital Universitario La Paz, Madrid, Spain. 7. Servicio de Cardiología, Hospital Universitario Vall d'Hebron, Barcelona, Spain. 8. Servicio de Cardiología, Hospital Universitario Clínico San Carlos, Madrid, Spain. 9. Servicio de Cardiología, Hospital Universitario Central de Asturias, Oviedo, Asturias, Spain. 10. Servicio de Cardiología, Talavera de la Reina, Toledo, Spain. 11. Servicio de Cardiología, Hospital La Mancha Centro, Ciudad Real, Spain. 12. Servicio de Cardiología, Hospital General Universitario de Alicante, Alicante, Spain. 13. Servicio de Cardiología, Hospital Universitario Insular de Gran Canaria, Las Palmas de Gran Canaria, Spain. 14. Servicio de Cardiología, Complejo Hospitalario de Navarra, Pamplona, Navarra, Spain. 15. Servicio de Cardiología, Hospital Universitario de Torrevieja, Torrevieja, Alicante, Spain. 16. Servicio de Cardiología, Hospital Universitario 12 de Octubre, Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), Madrid, Spain; Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Spain; Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Spain. 17. Servicio de Cardiología, Hospital Universitario Santa Lucía, Cartagena, Murcia, Spain. 18. Servicio de Cardiología, Hospital Universitario Ramón y Cajal, Madrid, Spain; Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Spain.
Abstract
INTRODUCTION AND OBJECTIVES: HeartLogic is a multiparametric algorithm incorporated into implantable cardioverter-defibrillators (ICD). The associated alerts predict impending heart failure (HF) decompensations. Our objective was to analyze the association between alerts and clinical events and to describe the implementation of a protocol for remote management in a multicenter registry. METHODS: We evaluated study phase 1 (the investigators were blinded to the alert state) and phases 2 and 3 (after HeartLogic activation, managed as per local practice and with a standardized protocol, respectively). RESULTS: We included 288 patients from 15 centers. In phase 1, the median observation period was 10 months and there were 73 alerts (0.72 alerts/patient-y), with 8 hospitalizations and 2 emergency room admissions for HF (0.10 events/patient-y). There were no HF hospitalizations outside the alert period. In the active phases, the median follow-up was 16 (95%CI, 15-22) months and there were 277 alerts (0.89 alerts/patient-y); 33 were associated with HF hospitalizations or HF death (n=6), 46 with minor decompensations, and 78 with other events. The unexplained alert rate was 0.39 alerts/patient-y. Outside the alert state, there was only 1 HF hospitalization and 1 minor HF decompensation. Most alerts (82% in phase 2 and 81% in phase 3; P=.861) were remotely managed. The median NT-proBNP value was higher within than outside the alert state (7378 vs 1210 pg/mL; P <.001). CONCLUSIONS: The HeartLogic index was frequently associated with HF-related events and other clinically relevant situations, with a low rate of unexplained events. A standardized protocol allowed alerts to be safely and remotely detected and appropriate action to be taken on them.
INTRODUCTION AND OBJECTIVES: HeartLogic is a multiparametric algorithm incorporated into implantable cardioverter-defibrillators (ICD). The associated alerts predict impending heart failure (HF) decompensations. Our objective was to analyze the association between alerts and clinical events and to describe the implementation of a protocol for remote management in a multicenter registry. METHODS: We evaluated study phase 1 (the investigators were blinded to the alert state) and phases 2 and 3 (after HeartLogic activation, managed as per local practice and with a standardized protocol, respectively). RESULTS: We included 288 patients from 15 centers. In phase 1, the median observation period was 10 months and there were 73 alerts (0.72 alerts/patient-y), with 8 hospitalizations and 2 emergency room admissions for HF (0.10 events/patient-y). There were no HF hospitalizations outside the alert period. In the active phases, the median follow-up was 16 (95%CI, 15-22) months and there were 277 alerts (0.89 alerts/patient-y); 33 were associated with HF hospitalizations or HF death (n=6), 46 with minor decompensations, and 78 with other events. The unexplained alert rate was 0.39 alerts/patient-y. Outside the alert state, there was only 1 HF hospitalization and 1 minor HF decompensation. Most alerts (82% in phase 2 and 81% in phase 3; P=.861) were remotely managed. The median NT-proBNP value was higher within than outside the alert state (7378 vs 1210 pg/mL; P <.001). CONCLUSIONS: The HeartLogic index was frequently associated with HF-related events and other clinically relevant situations, with a low rate of unexplained events. A standardized protocol allowed alerts to be safely and remotely detected and appropriate action to be taken on them.
Authors: Juan Carlos López-Azor; Noelia de la Torre; María Dolores García-Cosío Carmena; Pedro Caravaca Pérez; Catalina Munera; Irene MarcoClement; Rocío Cózar León; Jesús Álvarez-García; Marta Pachón; Fernando Arribas Ynsaurriaga; Rafael Salguero Bodes; Juan Francisco Delgado Jiménez; Javier de Juan Bagudá Journal: Card Fail Rev Date: 2022-04-21