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NCT05479617 Clinical Trial

Personalised Prediction Of Disease Course In Ulcerative Colitis Using Multimodal Machine Learning - Part Of The Presager Project

Ulcerative Colitis Clinical Trial

— Presager II  

Official title:
Personalised Prediction Of Disease Course In Ulcerative Colitis Using Multimodal Machine Learning - Part Of The Presager Project

Clinical Trial Details — Status: Recruiting

Administrative data
NCT number NCT05479617
Other study ID # H-21020965
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date June 20, 2022
Est. completion date December 30, 2025

Study information
Verified date September 2023
Source Copenhagen University Hospital, Hvidovre
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

In patients achieving clinical remission following a flare, artificial intelligence can reliably predict a new flare within the next 12 months utilizing clinical and objective information at day 0 and week 8. Secondary endpoints: - An artificial intelligence model's precision in predicting a new flare within 2 and 3 years - An artificial intelligence model's precision to rule out patients who will not experience a new flare within 1, 2 and 3 year

Recruitment information / eligibility
Status Recruiting
Enrollment 400
Est. completion date December 30, 2025
Est. primary completion date June 30, 2025
Accepts healthy volunteers No
Gender All
Age group 18 Years and older
Eligibility Inclusion criteria: - Signed informed consent - Diagnosis of UC for at least 1 year - Relapse due to UC. - First endoscopic and histological evaluation of the flare Exclusion criteria - Well-founded doubt that the flare is due to other than the patients UC

Study Design

Related Conditions & MeSH terms

Intervention

Other:
• Deep learning model
Use of deep learning model to predict individual patients disease course

Locations
Country Name City State
Denmark Gastrounit, medical section, Copenhagen University Hospital Hvidovre Hvidovre

Sponsors (1)
Lead Sponsor Collaborator
Copenhagen University Hospital, Hvidovre

Country where clinical trial is conducted

Denmark, 

Outcome
Type Measure Description Time frame Safety issue
Primary Flare I Evaluate the accuracy in predicting a flare within 1 year after the patient's initial flare using machine learning methods. within 1 year
Secondary Flare II Evaluate the accuracy in predicting a flare within 2 years, after the patient's initial flare, using machine learning methods. within 2 years
Secondary Flare III Evaluate the accuracy in predicting a flare within 3 years, after the patient's initial flare, using machine learning methods. within 3 years
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