Actively Recruiting
Application of Machine Learning Models to Reduce Need for Diagnostic EUS or MRCP in Patients With Intermediate Likelihood of Choledocholithiasis - A Prospective, Open Label, Diagnostic Study
Led by Asian Institute of Gastroenterology, India · Updated on 2026-01-06
1000
Participants Needed
1
Research Sites
17 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
Researchers are studying patients with suspected choledocholithiasis, a condition involving gallstones in the bile duct, who fall into an intermediate likelihood group based on current risk criteria. The study aims to evaluate how a machine learning model can help predict choledocholithiasis and potentially reduce the need for additional diagnostic procedures like Endoscopic Ultrasound (EUS) or Magnetic Resonance Cholangiopancreatography (MRCP). This approach may lower healthcare use and costs for these patients. This observational study uses a machine learning-based predictive model to stratify patients who otherwise might undergo EUS or MRCP. Participants are those aged 18 to 80 years with intermediate risk of choledocholithiasis. The model's performance in predicting the condition will be assessed, focusing on accuracy and receiver operating characteristic curve analysis within one month. Participants will be monitored through diagnostic evaluations including EUS or MRCP as needed, with data collected to validate the machine learning model. Researchers will measure the model's accuracy and compare it to the diagnostic tests. The study will track outcomes over one month, assessing how well the model predicts the presence of choledocholithiasis and its potential to reduce unnecessary diagnostic procedures.
CONDITIONS
Brief Title
Application of Machine Learning Models to Reduce Need for Diagnostic EUS or MRCP in Patients With Intermediate Likelihood of Choledocholithiasis
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Individual 18 years or older with suspected choledocholithiasis
- Must meet ASGE or ESGE intermediate risk criteria
- Undergoing EUS or MRCP as part of diagnosis
You will not qualify if you...
- Having other pancreato biliary diseases besides gallstones or choledocholithiasis, including chronic pancreatitis, biliary stricture, pancreatobiliary cancer, or portal biliopathy
- Having chronic liver diseases
- Pregnant or breastfeeding
- Previous gallbladder removal (cholecystectomy)
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Your Study Journey
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person)
Duration - Up to 1 month
Participants undergo diagnostic procedures including Endoscopic Ultrasound (EUS) or Magnetic Resonance Cholangiopancreatography (MRCP) to assess for choledocholithiasis.
1 to 2 visits depending on diagnostic procedure
Duration - 1 month
Participants are monitored to evaluate the performance of the machine learning prediction model and diagnostic accuracy over a 1-month period.
Follow-up visits as needed during 1 month
Trial Site Locations
Total: 1 location
1
Asian Institute of Gastroenterology
Hyderabad, Telangana, India, 500032
Actively Recruiting
Research Team
N
Nitin G Jagtap, MD
H
Hardik Rughwani, MD
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
0
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