ArticleJHEP reports : innovation in hepatology2021
Development and validation of a dynamic survival prediction model for patients with acute-on-chronic liver failure.
Article in JHEP reports : innovation in hepatology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Prediction models for mortality in patients with acute on chronic liver failure: systematic review and critical appraisal.Frontiers in medicine · 2026Pooled it
- [Impact of key indicator dynamic change on 90-day prognosis for patients with acute-on-chronic liver failure].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2026Article
- Predicting prognosis of patients with hepatitis B virus-related acute-on-chronic liver failure from longitudinal ultrasound images using a multi-task deep learning approach.Annals of medicine · 2025Article
- Development and validation of a prediction model for in-hospital mortality in patients with sepsis.Nursing in critical care · 2025Article
- External validation and longitudinal application of the DO-GAP index to individualise survival prediction in idiopathic pulmonary fibrosis.ERJ open research · 2023Article
- Growing Evidence for Survival Benefit with Plasma Exchange to Treat Liver Failure.Journal of clinical and experimental hepatologyReview
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Authors and funding
8 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND &
aimsAcute-on-chronic liver failure (ACLF) is usually associated with a precipitating event and results in the failure of other organ systems and high short-term mortality. Current prediction models fail to adequately estimate prognosis and need for liver transplantation (LT) in ACLF. This study develops and validates a dynamic prediction model for patients with ACLF that uses both longitudinal and survival data.
methodsAdult patients on the UNOS waitlist for LT between 11.01.2016-31.12.2019 were included. Repeated model for end-stage liver disease-sodium (MELD-Na) measurements were jointly modelled with Cox survival analysis to develop the ACLF joint model (ACLF-JM). Model validation was carried out using separate testing data with area under curve (AUC) and prediction errors. An online ACLF-JM tool was created for clinical application.
resultsIn total, 30,533 patients were included. ACLF grade 1 to 3 was present in 16.4%, 10.4% and 6.2% of patients, respectively. The ACLF-JM predicted survival significantly (
conclusionsThe ACLF-JM dynamically predicts outcome based on current and past disease severity. Prediction performance is excellent over time, even in patients with ACLF-3. Therefore, the ACLF-JM could be used as a clinical tool in the evaluation of prognosis and treatment in patients with ACLF. LAY SUMMARY: Acute-on-chronic liver failure (ACLF) progresses rapidly and often leads to death. Liver transplantation is used as a treatment and the sickest patients are treated first. In this study, we develop a model that predicts survival in ACLF and we show that the newly developed model performs better than the currently used model for ranking patients on the liver transplant waiting list.
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