ReviewWorld journal of clinical cases2022
Animal models applied to acute-on-chronic liver failure: Are new models required to understand the human condition?
Review in World journal of clinical cases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Extracellular vesicles as potential biomarkers and treatment options for liver failure: A systematic review up to March 2022.Frontiers in immunology · 2023Pooled it
- Acute-on-chronic liver failure and immune dysregulation: Systemic inflammation and immunoparesis paradox.Hepatology communications · 2026Review
- Hepatic Inflammation and Liver Injury in a Model of Bacterial Infection Triggered Acute-on-Chronic Liver Injury.Journal of gastroenterology and hepatology · 2025Article
- Crosstalk of TNF-α, IFN-γ, NF-kB, STAT1 and redox signaling in lipopolysaccharide/d-galactosamine/dimethylsulfoxide-induced fulminant hepatic failure in mice.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2023Article
- Utility of neutrophil-lymphocyte ratio and platelet-lymphocyte ratio in predicting acute-on-chronic liver failure survival.Open life sciences · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The liver is a multifaceted organ; its location and detoxifying function expose this organ to countless injuries. Acute-on-chronic failure liver (ACLF) is a severe syndrome that affects the liver due to acute decompensation in patients with chronic liver disease. An infection environment, ascites, increased liver enzymes and prothrombin time, encephalopathy and fast-evolving multiorgan failure, leading to death, usually accompany this. The pathophysiology remains poorly understand. In this context, animal models become a very useful tool in this regard, as understanding; the disease may be helpful in developing novel therapeutic methodologies for ACLF. However, although animal models display several similarities to the human condition, they do not represent all ACLF manifestations, resulting in significant challenges. An initial liver cirrhosis framework followed by the induction of an acute decompensation by administering lipopolysaccharide and D-GaIN, potentiating liver damage supports the methodologies applied to induce experimental ACLF. The entire methodology has been described mostly for rats. Nevertheless, a quick PubMed database search indicates about 30 studies concerning ACFL models and over 1000 regarding acute liver failure models. These findings demonstrate the clear need to establish easily reproducible ACFL models to elucidate questions about this quickly established and often fatal syndrome.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.