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Mª Ángeles Muchada López

Institutions of which they are part

Main researcher
Stroke research
Vall Hebron Institut de Recerca

Mª Ángeles Muchada López

Institutions of which they are part

Main researcher
Stroke research
Vall Hebron Institut de Recerca

Projects

Impact of time to achieve blood pressure control on hematoma expansion in patients with acute intracerebral hemorrhage

IP: David Rodriguez Luna
Collaborators: Maria Mar Hernandez Guillamon, Mª Ángeles Muchada López
Funding agency: Fundació La Marató de TV3
Funding: 177052.88
Reference: 20173030
Duration: 01/01/2018 - 31/01/2022

Tenecteplase versus Alteplase for Stroke Thrombolysis Evaluation (TASTE) Trial

IP: Carlos Molina Cateriano
Collaborators: Marta Aurora Rubiera Del Fueyo, David Rodriguez Luna, Mª Ángeles Muchada López
Funding agency: National Health and Medical Res Council (NHMR
Funding: 1950
Reference: TASTE_HMRI2012101
Duration: 19/04/2017 - 16/04/2018

The Chemical Optimization of Cerebral Embolectomy (CHOICE) Trial

IP: Mª Ángeles Muchada López
Collaborators: -
Funding agency: Fundació La Marató de TV3
Funding: 104600
Reference: 20170733
Duration: 01/01/2018 - 31/12/2021

Malalties Neurovasculars (GRC)

IP: Joan Montaner Villalonga
Collaborators: Marta Aurora Rubiera Del Fueyo, Jorge Pagola Pérez Blanca, José Alvarez Sabin, Anna Penalba Morenilla, Maria Mar Hernandez Guillamon, Marc Ribó Jacobi, Maria Pilar Delgado Martínez, Carlos Molina Cateriano, Anna Rosell Novel, David Rodriguez Luna, Mª Ángeles Muchada López, Estevo Santamarina Pérez, Manuel Quintana Luque
Funding agency: Agència Gestió Ajuts Universitaris i de Recerca
Funding: 48000
Reference: 2014 SGR 686
Duration: 01/01/2014 - 31/12/2016

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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