Evidence map›Paper›PMID 41809486›Full record

ArticleWorld journal of hepatology2026

Dynamic inflammation-based prognostication in acute-on-chronic liver failure: The COSSH-CAR model as a step forward in personalized risk stratification.

Noura A A Ebrahim, Thoraya A Farghaly, Soliman M A Soliman

Abstract readEditorial
In one paragraph

Article in World journal of hepatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Noura A A EbrahimDepartment of Oncologic Pathology, National Cancer Institute, Cairo University, Cairo 11796, Al Qāhirah, Egypt. npathologist@gmail.com.
Thoraya A FarghalyDepartment of Chemistry, Faculty of Science, Umm Al-Qura University, Makkah 21955, Saudi Arabia.
Soliman M A SolimanDepartment of Chemistry, Faculty of Science, Cairo University, Cairo 12613, Al Qāhirah, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute-on-chronic liver failure (ACLF) is a swiftly deteriorating condition characterized by profound systemic inflammation and failure of multiple organ systems, leading to high early mortality. There remains a critical need for more effective biomarkers to facilitate timely and accurate risk assessment. Recent findings by Zhu and Yan demonstrated that evaluating temporal changes in the C-reactive protein to albumin ratio (CAR), especially the 7-day variation, offers superior prediction of 28-day mortality compared with single baseline measurements. By integrating the 7-day variation of CAR with the model for end-stage liver disease sodium score and the grade of hepatic encephalopathy, the Chinese Group on Study of Severe Hepatitis B (COSSH)-CAR model was created, which surpassed traditional prognostic tools such as the Child-Pugh, model for end-stage liver disease, and COSSH-ACLF. This comment highlights the importance of using dynamic biomarker trajectories rather than static values for prognostic evaluation. CAR is biologically compelling because it captures both the inflammatory burden and the patient's nutritional/physiological reserve. While the COSSH-CAR model is promising and based on routinely obtainable laboratory data, its widespread adoption will depend on validation in larger, diverse, and non-hepatitis B virus-related cohorts. Future work should examine CAR kinetics in prospective and interventional studies and consider how they may support individualized management strategies. Collectively, these observations suggest that the CAR could represent an important addition to current ACLF prognostic frameworks.

Indexed as

Acute-on-chronic liver failureChinese Group on Study of Severe Hepatitis B-CARC-reactive protein to albumin ratio (CAR)Dynamic biomarkersHepatic encephalopathyRisk stratificationSystemic inflammation

Identifiers

PMID41809486
PMCPMC12968705

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Registered trials

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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.