Repositorio Institucional
Repositorio Institucional
CONICET Digital
  • Inicio
  • EXPLORAR
    • AUTORES
    • DISCIPLINAS
    • COMUNIDADES
  • Estadísticas
  • Novedades
    • Noticias
    • Boletines
  • Ayuda
    • General
    • Datos de investigación
  • Acerca de
    • CONICET Digital
    • Equipo
    • Red Federal
  • Contacto
JavaScript is disabled for your browser. Some features of this site may not work without it.
  • INFORMACIÓN GENERAL
  • RESUMEN
  • ESTADISTICAS
 
Evento

A Computational Study of Aortic Insufficiency in Patients Supported with Left Ventricular Assist Devices

Grinstein, J.; Blanco, P. J.; Bulant, Carlos AlbertoIcon ; Torii, R.; Bourantas, C. V.; Lemos, P. A.; Garcia Garcia, H.
Tipo del evento: Reunión
Nombre del evento: International Society for Heart and Lung Transplantation Annual Meeting
Fecha del evento: 27/04/2022
Institución Organizadora: International Society for Heart & Lung Transplantation;
Título de la revista: The Journal of Heart and Lung Transplantation
Editorial: Elsevier
ISSN: 1053-2498
Idioma: Inglés
Clasificación temática:
Otras Ingeniería Médica; Otras Ciencias de la Computación e Información

Resumen

Purpose Aortic insufficiency (AI) following left ventricular assist device (LVAD) implantation is common. Speed augmentation to overcome the regurgitant flow (RF) is used but this leads to progressive AI and may have deleterious effects on shear stress (SS) and the right ventricle (RV). Methods We employed a closed-loop mathematical model of the cardiovascular system to generate boundary conditions for blood flow simulations performed in a three-dimensional (3D) model of the aortic arch. AI was introduced and the impact of speed augmentation and blood pressure control on SS and RV oxygen consumption (MVO2) were determined in a model with a coupled and uncoupled RV. Results Addition of severe AI to the coupled RV at 5500 RPM led to a reduction in net flow from 5.4 L/min (no AI) to 2.1 L/min (severe). Increasing speed to 6400 RPM in the severe AI and coupled RV, led to a 42% increase in net flow and a 16% increase in RF with a nominal decrease of 0.9% in RV MVO2. Blood pressure control with the coupled RV with severe AI at 5500 RPM led to an 81% increase in net flow with a 15% reduction RF and an 8% reduction in RV MVO2 (Fig A). With an uncoupled RV, addition of severe AI at 5500 RPM led to a reduction in net flow from 5.0 L/min (no AI) to 1.8 L/min (severe). Increasing speed to 6400 RPM with severe AI and uncoupled RV increased net flow by 45%, RF by 15% and RV MVO2 by 4.2%. For the uncoupled RV with severe AI, blood pressure control alone led to a 22% increase in net flow, 4.2% reduction in RF and 6.1% reduction in RV MVO2; whereas combined BP control and pulmonary vasodilation led to a 113% increase in net flow, 20% reduction in RF and 41% reduction in RV MVO2 (Fig B). Compared to speed augmentation, blood pressure control consistently resulted in a reduction in SS (Fig C). Conclusion Speed augmentation to overcome AI in patients supported by CF-LVAD will augment flow but at the expense of RV MVO2, RF and SS. Aggressive blood pressure control and pulmonary vasodilation can improve net flow with more advantageous effects on the RV and aortic valve integrity.
Palabras clave: IMAGE SEGMENTATION , COMPUTATIONAL FLUID DYNAMICS , AORTIC INSUFFICIENCY
Ver el registro completo
 
Archivos asociados
Tamaño: 646.2Kb
Formato: PDF
.
Solicitar
Licencia
info:eu-repo/semantics/restrictedAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/247232
URL: https://linkinghub.elsevier.com/retrieve/pii/S1053249822000900
DOI: http://dx.doi.org/10.1016/j.healun.2022.01.072
Colecciones
Eventos(CCT - TANDIL)
Eventos de CTRO CIENTIFICO TECNOLOGICO CONICET - TANDIL
Citación
A Computational Study of Aortic Insufficiency in Patients Supported with Left Ventricular Assist Devices; International Society for Heart and Lung Transplantation Annual Meeting; Boston; Estados Unidos; 2022; 32-33
Compartir
Altmétricas
 

Enviar por e-mail
Separar cada destinatario (hasta 5) con punto y coma.
  • Facebook
  • X Conicet Digital
  • Instagram
  • YouTube
  • Sound Cloud
  • LinkedIn

Los contenidos del CONICET están licenciados bajo Creative Commons Reconocimiento 2.5 Argentina License

https://www.conicet.gov.ar/ - CONICET

Inicio

Explorar

  • Autores
  • Disciplinas
  • Comunidades

Estadísticas

Novedades

  • Noticias
  • Boletines

Ayuda

Acerca de

  • CONICET Digital
  • Equipo
  • Red Federal

Contacto

Godoy Cruz 2290 (C1425FQB) CABA – República Argentina – Tel: +5411 4899-5400 repositorio@conicet.gov.ar
TÉRMINOS Y CONDICIONES