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Jorge Pagola Pérez Blanca

Institutions of which they are part

Main researcher
Stroke research
Vall Hebron Institut de Recerca

Jorge Pagola Pérez Blanca

Institutions of which they are part

Main researcher
Stroke research
Vall Hebron Institut de Recerca

Projects

ESCALA DE RIESGO DE ICTUS EN PACIENTES CON FIBRILACIÓN AURICULAR Y ANTICOAGULANTES ORALES DIRECTOS

IP: Jorge Pagola Pérez Blanca
Collaborators: José Alvarez Sabin, Noelia Rodríguez Villatoro, Jaume Francisco Pascual, Hug Cuellar Calabria, Ruben Fernández Galera, Federica Rizzo, Claudia Meza Burgos
Funding agency: Instituto de Salud Carlos III
Funding: 61250
Reference: PI24/00333
Duration: 01/01/2025 - 31/12/2027

NexTOLL: A Phase IIb Clinical Trial to evaluate the neuroprotective effect of ApTOLL in stroke patients

IP: Marc Ribó Jacobi
Collaborators: Marta Aurora Rubiera Del Fueyo, Jorge Pagola Pérez Blanca, Carlos Molina Cateriano, Mª Ángeles Muchada López
Funding agency: Ministerio de Ciencia e Innovación-MICINN
Funding: 498435
Reference: CPP2022-009778
Duration: 09/03/2023 - 08/03/2026

Ministerio de Ciencia

VALIDACIÓN DIAGNÓSTICA DE UNA PULSERA INTELIGENTE PARA LA DETECCIÓN DE FIBRIL

IP: Jorge Pagola Pérez Blanca
Collaborators: Nuria Rivas Gandara, José Alvarez Sabin, Jaume Francisco Pascual
Funding agency: Instituto de Salud Carlos III
Funding: 85910
Reference: PI20/01210
Duration: 01/01/2021 - 30/06/2025

ITACAT: Impact of Thrombus Analysis in stroke patients in CATalonia.

IP: Carlos Molina Cateriano
Collaborators: Santiago Ramon y Cajal Agüeras, Jorge Pagola Pérez Blanca, Carlos Palacio García, Noelia Rodríguez Villatoro, David Rodriguez Luna
Funding agency: Fundació La Marató de TV3
Funding: 197973.69
Reference: 20171930
Duration: 01/01/2018 - 31/01/2022

Related news

The Stroke Research and the Neurovascular Diseases groups lead innovative research projects in both clinical and translational areas.

The team will develop a new medical tool to facilitate the removal of blood clots in blood vessels after a stroke in a safer and more effective manner.

A retrospective study has been carried out with data from 11,000 patients to train artificial intelligence algorithms and adapt the Nora mobile application to different patient profiles.

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