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Early discharge programme after transcatheter aortic valve implantation based on close follow-up supported by telemonitoring using artificial intelligence: the TeleTAVI study

Título :
Early discharge programme after transcatheter aortic valve implantation based on close follow-up supported by telemonitoring using artificial intelligence: the TeleTAVI study
Autor :
Herrero-Brocal, Marta  
Samper Perez, Raquel  
Riquelme, Jorge
Pineda, Javier
BORDES SISCAR, PASCUAL  
Torres Mezcua, Fernando José  
Valencia, José
Torres-Saura, Francisco
González Manso, María
Ajo Ferrer, Raquel  
Arenas, Juan
Feliu, Eloísa
Martínez, Juan Gabriel
Ruiz-Nodar, Juan  
Editor :
Oxford University Press
Departamento:
Departamentos de la UMH::Patología y Cirugía
Fecha de publicación:
2024-10
URI :
https://hdl.handle.net/11000/38911
Resumen :
Aims: Evidence regarding the safety of early discharge following transcatheter aortic valve implantation (TAVI) is limited. The aim of this study was to evaluate the safety of very early (<24) and early discharge (24-48 h) as compared to standard discharge (>48 h), supported by the implementation of a voice-based virtual assistant using artificial intelligence (AI) and natural language processing. Methods and results: Single-arm prospective observational study that included consecutive patients who underwent TAVI in a tertiary hospital in 2023 and were discharged under an AI follow-up programme. Primary endpoint was a composite of death, pacemaker implantation, readmission for heart failure, stroke, acute myocardial infarction, major vascular complications, or major bleeding, at 30-day follow-up. A total of 274 patients were included. 110 (40.1%) patients were discharged very early (<24 h), 90 (32.9%) early (24-48 h), and 74 (27.0%) were discharged after 48 h. At 30-day follow-up, no significant differences were found among patients discharged very early, early, and those discharged after 48 h for the primary endpoint (very early 9.1% vs. early 11.1% vs. standard 9.5%; P = 0.88). The AI platform detected complications that could be effectively addressed. The implementation of this follow-up system was simple and satisfactory for TAVI patients. Conclusion: Early and very early discharge in patients undergoing TAVI, supported by close follow-up using AI, were shown to be safe. Patients with early and very early discharge had similar 30-day event rates compared to those with longer hospital stays. The AI system contributed to the early detection and resolution of complications.
Palabras clave/Materias:
Transcatheter aortic valve implantation (TAVI)
Early discharge
Artificial intelligence (AI)
Telemedicine
Post-discharge monitoring
Complication detection
Área de conocimiento :
CDU: Ciencias aplicadas: Medicina
Tipo de documento :
info:eu-repo/semantics/article
Derechos de acceso:
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
DOI :
https://doi.org/10.1093/ehjdh/ztae089
Publicado en:
European Heart Journal - Digital Health, 6(1), 73-81 - November 2024
Aparece en las colecciones:
Artículos Patología y Cirugía



Creative Commons La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.