Status:
RECRUITING
Application of Machine Learning Models to Reduce Need for Diagnostic EUS or MRCP in Patients With Intermediate Likelihood of Choledocholithiasis
Lead Sponsor:
Asian Institute of Gastroenterology, India
Conditions:
Choledocholithiasis
Eligibility:
All Genders
18-80 years
Brief Summary
Machine learning predictive model can help in stratifying heterogenous intermediate likelihood group to reduce need for EUS or MRCP in selected subgroup of patients.
Detailed Description
The current guidelines for suspected choledocholithiasis are aimed to reduce the risk of patient receiving diagnostic ERCP and reduce the risk of post ERCP adverse events. In this process there is app...
Eligibility Criteria
Inclusion
- • Individual 18 years or older with a suspected choledocholithiasis satisfying either ASGE or ESGE risk stratification criteria of intermediate likelihood undergoing EUS or MRCP
Exclusion
- Patients having co-exiting disease of pancreato biliary system other than gall stones and choledocholithiasis which include chronic pancreatitis, biliary stricture, pancreatobiliary malignancy, portal biliopathy
- Patients having underlying chronic liver diseases
- Pregnancy and breast feeding
- Previous history of cholecystectomy
Key Trial Info
Start Date :
October 1 2023
Trial Type :
OBSERVATIONAL
Allocation :
ESTIMATED
End Date :
October 30 2026
Estimated Enrollment :
1000 Patients enrolled
Trial Details
Trial ID
NCT06066372
Start Date
October 1 2023
End Date
October 30 2026
Last Update
January 6 2026
Active Locations (1)
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1
Asian Institute of Gastroenterology
Hyderabad, Telangana, India, 500032