FindTrial
Sign In

Development of artificial intelligence based model to predict mortality in patients with acute-on-chronic liver failure

Development, validation and deployment of a novel prediction model utilizing artificial intelligence on clinical and proteomic features to predict mortality among patients with acute-on-chronic liver failure

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2021/11/038131
Enrollment
200
Registered
2021-11-18
Start date
Unknown
Completion date
Unknown
Last updated
2022-10-17

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: K74- Fibrosis and cirrhosis of liver

Interventions

None listed

Sponsors

IHUB Anubhuti IITD Foundation TIH
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Patients with a confirmed diagnosis of ACLF either by EASL criteria or by APASL criteria

Exclusion criteria

Exclusion criteria: Patients with HIV infection, pregnant or lactating women, patients having any active malignancy or previous organ-transplantation and those refusing to give a consent will be excluded

Design outcomes

Primary

MeasureTime frame
Derivation of AI/ML model for prediction of mortality in ACLF patientsTimepoint: After establishment of clinical and proteomic database, model derivation phase will began in first one and a half year—

Secondary

MeasureTime frame
Development of web application for AI model deploymentTimepoint: After internal validation of model, a validation cohort will be recruited and for model validation and refinement in next one and a half year—

Countries

India

Contacts

Public ContactDr Nipun Verma

PGIMER, Chandigarh

nipun29j@gmail.com9914208562

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026