Home monitoring for the detection of atrial fibrillation in hypertensive patients. BP/AF MODE study

Daniel Piskorz, Institute of Cardiology, Sanatorio Británico SA, Santa Fe, Rosario, Argentina
Ricardo López-Santi, Sociedad Interamericana de Cardiología, Mexico City, Mexico
Gonzalo Piskorz, Business Inteligence, Data IQ, Ciudad Autónoma de Buenos Aires, Argentina
Jorge Juárez-Lloclla, Department of Cardiology, Hospital de la Amistad Perú-Corea, Santa Rosa II-2, Piura, Peru
Silvia Palomo-Piñón, Grupo de Expertos en Hipertensión Arterial México (GREHTA), Mexico City, Mexico
Claudia Anchique-Santos, Department of Cardiology, Mediagnóstica, Duitama, Colombia
Juan Cárdenas-Castellanos, Teaching Department, Universidad Tecnológica de Pereira, Pereira, Colombia
Patricia Nuriulú, Department of Cardiology, Instituto Cardiovascular de Hidalgo, Pachuca, Hgo., Mexico
Henry De Las Salas-Pérez, Department of Cardiology, Clínica Alemana de Santiago, Santiago de Chile, Chile
Mauro Ruise, Faculty of Medical Sciences, Teaching Department, Universidad Nacional de Santiago Del Estero, Santiago del Estero, Argentina
Sofía Brondello, Department of Cardiology, Certus Med & Gym, Centro de Prevención Cardiovascular, Rehabilitación y Entrenamiento, Villa María, Córdoba, Argentina
Mildren del Sueldo, Department of Cardiology, Certus Med & Gym, Centro de Prevención Cardiovascular, Rehabilitación y Entrenamiento, Villa María, Córdoba, Argentina
Yan Duarte-Vera, Department of Teaching and Research, Universidad de Guayaquil, Guayaquil, Ecuador
Ana Múnera-Echeverri, Department of Cardiology, Clínica Rosario-Cardioestudio, Medellín, Colombia
Diego Celis, Department of Cardiology, Hospital de Castro, Chiloe, Chile
Gonzalo Miranda, Department of Cardiology, Certus Med & Gym, Centro de Prevención Cardiovascular, Rehabilitación y Entrenamiento, Villa María, Córdoba, Argentina
Luis M. Norabuena-Rossel, Department of Cardiology, Hospital de la Amistad Perú-Corea, Santa Rosa II-2, Piura, Peru
Mónica Marino, Institute of Cardiology, Sanatorio Británico SA, Santa Fe, Rosario, Argentina
Humberto Álvarez-López, Department of Cardiology, Hospital Puerta de Hierro Andares, Zapopan, Jal., Mexico
María J. Cedeño-Zambrano, Department of Cardiology, Hospital de Especialidades Alfredo Paulson, Guayaquil, Ecuador
Luis Rocha-Enciso, Department of Cardiology, Instituto Cardiovascular de Hidalgo, Pachuca, Hgo., Mexico
Héctor Galván-Oseguera, Grupo de Expertos en Hipertensión Arterial México (GREHTA), Mexico City, Mexico
Francisco Ramos-Carrillo, Regional General Hospital No. 220 General José Vicente Villada, IMSS, Toluca, Mexico State, Mexico
Miguel Peñaherrera-Oviedo, Department of Cardiology, Hospital de Especialidades Alfredo Paulson, Guayaquil, Ecuador

Objective: To determine the usefulness of home blood pressure (BP) and heart rhythm monitoring strategies in the detection of subclinical atrial fibrillation (AF) to build a predictive risk score through deep learning. Methods: Observational, cohort, prospective, multicenter study involving 25 researchers from six Latin American countries. Home BP monitoring and single-lead electrocardiogram (ECG) recording will be performed in a population at moderate-to-high risk of developing AF. Results: A minimum of twenty 30-s electrocardiographic and BP recordings over 7 days using an Omron Complete Hem-7530 T ECG device will be uploaded from a mobile phone app and then sent to a database for analysis. Conclusions: The results of this study can provide a simple and accessible home monitoring system for detecting subclinical AF and for optimizing the predictive capacity of arrhythmia risk scores through deep learning. ClinicalTrials.gov identifier: NCT07058831.

Keywords: Hypertension. Atrial fibrillation. Home monitoring. Artificial intelligence.