Autonomous Robotics for Transcatheter Cardiac Procedures
NCT ID: NCT04787757
Last Updated: 2025-08-17
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
401 participants
OBSERVATIONAL
2021-03-15
2024-06-21
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Percutaneous cardiac procedures
Patients undergoing percutaneous cardiac procedures
Percutaneous cardiac procedure
Collection and analysis of intraprocedural information to provide artificial intelligence algorithms
Interventions
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Percutaneous cardiac procedure
Collection and analysis of intraprocedural information to provide artificial intelligence algorithms
Eligibility Criteria
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Inclusion Criteria
* patients admitted to hospital undergoing percutaneous cardiac procedure
* patients able to give informed consent
Exclusion Criteria
* refuse to give informed consent
18 Years
ALL
No
Sponsors
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Politecnico di Milano
OTHER
Scuola Superiore di Studi Universitari e di Perfezionamento Sant'Anna
OTHER
KU Leuven
OTHER
SwissVortex
UNKNOWN
Artiness SRL
INDUSTRY
FBGS
UNKNOWN
IRCCS Ospedale San Raffaele
OTHER
Università Vita-Salute San Raffaele
OTHER
Responsible Party
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Giovanni Landoni
MD, Associate Professor
Locations
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Università Vita-Salute San Raffaele
Milan, MI, Italy
Countries
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References
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Munafo R, Saitta S, Tondi D, Ingallina G, Denti P, Maisano F, Agricola E, Votta E. Automatic 4D mitral valve segmentation from transesophageal echocardiography: a semi-supervised learning approach. Med Biol Eng Comput. 2025 Jan 11. doi: 10.1007/s11517-024-03275-w. Online ahead of print.
Other Identifiers
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ARTERY/08/2021
Identifier Type: -
Identifier Source: org_study_id
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