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The aim of this study was to developed and validated models to predict hepatic decompensation and survivals in pediatric patients with cirrhosis and compared these models with currently available models.
Noninvasive liver fibrosis tests such as the NAFLD fibrosis score (NFS), Hepascore, and transient elastography were specifically developed to predict fibrosis and can help predict patients with NAFLD at the highest risk of developing liver-related complications. These tests have been widely applied in adult cirrhosis. The accuracy of these models, however, may be influenced by patient factors including age, body mass index, and diabetes, potentially limiting their prognostic accuracy and clinical practicability in children. Therefore, it is currently unknown how to best predict hepatic decompensation and survival outcomes among pediatric patients with cirrhosis. To fill this knowledge gap, the investigators performed a retrospective-prospective cohort study with the aim of developing and validating a clinical model to predict liver-related complications and survival outcomes in pediatric patients with biopsy-proven with cirrhosis. Secondly, the investigators aimed to compare the predictive accuracy with currently available noninvasive model.
Age
0 - 18 years
Sex
ALL
Healthy Volunteers
No
West China Hospital, Sichuan University
Chengdu, Sichuan, China
Start Date
January 1, 2021
Primary Completion Date
December 31, 2024
Completion Date
December 31, 2024
Last Updated
January 20, 2022
400
ESTIMATED participants
Prediction model
OTHER
Lead Sponsor
West China Hospital
NCT05597488
NCT06932783
Data Source & Attribution
This clinical trial information is sourced from ClinicalTrials.gov, a service of the U.S. National Institutes of Health.
Modifications: This data has been reformatted for display purposes. Eligibility criteria have been parsed into inclusion/exclusion sections. Location data has been geocoded to enable distance-based search. For the authoritative and most current information, please visit ClinicalTrials.gov.
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View ClinicalTrials.gov Terms and ConditionsNCT06306963