CIRI – Cirrhosis Risk Identifier
CIRI is a scientific machine-learning model developed for the non-invasive estimation of the risk of first hepatic decompensation in patients with compensated advanced chronic liver disease.
This website is provided in connection with the publication "A Machine Learning Approach to Non-Invasively Predict Hepatic Decompensation in Advanced Chronic Liver Disease: the CIRI Model". It is intended to support scientific transparency and reproducibility of the published findings and to enable interested academic research groups to apply the CIRI model.
A publicly accessible web-based calculator of the CIRI score will be made available on this website. Until this calculator becomes available, interested academic research groups may request application of CIRI to their own research data upon reasonable request.
Application of CIRI requires a pseudonymized dataset containing the following variables:
Age, years
Sex
Hemoglobin, g/dL
Platelet count, G/L
Potassium, mmol/L
Alkaline phosphatase, U/L
Alanine aminotransferase, U/L
Aspartate aminotransferase, U/L
Albumin, g/L
Bilirubin, mg/dL
Glucose, mg/dL
Requests for application of CIRI may be directed to the contact address below. Following execution of a Data Transfer Agreement, the dataset may be transferred to the Medical University of Vienna. CIRI will then be applied and the resulting values will be returned to the requesting researchers.
Disclaimer
This calculator is provided for academic purposes only and to enhance understanding of the tenets of the associated publication on "A Machine Learning Approach to Non-Invasively Predict Hepatic Decompensation in Advanced Chronic Liver Disease: the CIRI Model". It is not intended for use in diagnosis, monitoring, prediction, or prognosis of disease or other condition, not intended for the benefit of an individual patient, and not otherwise indicated for any other medical purpose and thus, is intended to not qualify as medical device in accordance with the applicable regulatory framework.
Contact:
georg.kramer@meduniwien.ac.at
thomas.reiberger@meduniwien.ac.at