Development and Validation of a Machine Learning Model to Differentiate Drug-induced Liver Injury and Autoimmune Hepatitis
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Drug-induced Liver Injury
- Sponsor
- Beijing Friendship Hospital
- Enrollment
- 2583
- Locations
- 1
- Primary Endpoint
- Accuracy of the model in the differential diagnosis of DILI and AIH
- Status
- Completed
- Last Updated
- 2 years ago
Overview
Brief Summary
A retrospective, multi-center, non-interventional cohort study has been going to explore whether artificial intelligence can discriminate Drug-induced liver injury and Autoimmune hepatitis.
A machine learning-based tool will be developed and validated to help clinicians to differentiate between Drug-induced liver injury and Autoimmune hepatitis
Detailed Description
Research Objectives: 1. To develop a machine learning-based model from retrospective data. 2. To validate the machine learning-based model from internal dataset and external datasets nationwide. 3. To setup a website or application based on the above model to discriminate Drug-induced liver injury and Autoimmune hepatitis.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Drug-induced liver injury
- •RUCAM ≥6 and met one of the following biochemical conditions: a.) ALT≥5 ULN, b.) or ALP ≥2 ULN, iii) or ALT≥3 ULN and TBil≥2 ULN.
- •RUCAM was between 3-5, the medical records were further reviewed by the three authors to determine the eligibility.
- •Autoimmune hepatitis
- •The revised International Autoimmune Hepatitis Group (IAIHG) diagnostic score≥6 points.
- •Liver biopsy available, which is compatible with typical features of AIH.
- •If liver biopsy was unavailable, patients who achieved biochemical resolution after sustained immunosuppressive therapy.
Exclusion Criteria
- •Drug-induced liver injury
- •Hepatotropic viral infection: hepatitis A, B, C, D and E.
- •Non-hepatotropic viral infection: cytomegalovirus (CMV) and Epstein-Barr virus (EBV), etc.
- •Hypoxic ischemic hepatitis and congestive liver disease.
- •Alcohol consumption: male \>40g/d, female \>20g/d, and ≥5 years.
- •Biliary obstruction, primary biliary cholangitis; primary sclerosing cholangitis.
- •Autoimmune hepatitis.
- •Parasitic infection.
- •Previous liver transplantation or bone marrow transplantation.
- •Pregnancy or lactation.
Outcomes
Primary Outcomes
Accuracy of the model in the differential diagnosis of DILI and AIH
Time Frame: May 31, 2023
The ratio of the correct number of forecasts to the total number of forecasts
The confidence of the model in the differential diagnosis of DILI and AIH
Time Frame: May 31, 2023
The confidence and 95% confidence internal of the model in determining whether each case is DILI or AIH