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NCT06341361

OCT-based Machine Learning FFR for Predicting Post-PCI FFR

Status unknown Last updated 2 April 2024
What this trial tests

trial testing OCT-based machine learning FFR in Tomography, Optical Coherence in 82 participants. Status unknown.

Timeline
15 April 2024
Primary endpoint
30 April 2024
15 October 2025

Quick facts

Lead sponsorYonsei University
StatusStatus unknown
Study typeOBSERVATIONAL
Enrollment82
Start date15 April 2024
Primary completion30 April 2024
Estimated completion15 October 2025

Drugs / interventions tested

Conditions studied

Sponsor

Yonsei University

Who can join

19 and older, any sex, with Tomography, Optical Coherence or Fractional Flow Reserve, Myocardial. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

This study aims to compare the diagnostic accuracy of the fractional flow reserve (FFR) model derived by machine learning based on optical coherence tomography (OCT) exam after coronary artery stent implantation with the wire-based FFR.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other recruiting trials for Tomography, Optical Coherence

Currently open trials in the same condition.

Other Yonsei University trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06341361.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing