Evidence map›Paper›PMID 42736474›Full record

SynthesisJournal of clinical apheresis2026

The Optimal Therapeutic Window for Nonbioartificial Liver Support in Acute-On-Chronic Liver Failure: A Meta-Analysis and Meta-Regression Based on Baseline MELD Score.

Jiahao Li, Yang Liu, Jianying Shao, Yali Cheng, Xiangkai Zeng, Han Li, Haoqian Tan, Junying Liu

Abstract readMeta-Analysis
In one paragraph

Synthesis in Journal of clinical apheresis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Jiahao LiZhoukou Central Hospital Affiliated to Henan Medical University, Zhoukou, Henan Province, China.ORCID https://orcid.org/0009-0001-8636-9065
Yang LiuZhoukou Central Hospital Affiliated to Henan Medical University, Zhoukou, Henan Province, China.
Jianying ShaoZhoukou Central Hospital Affiliated to Henan Medical University, Zhoukou, Henan Province, China.
Yali ChengZhoukou Central Hospital Affiliated to Henan Medical University, Zhoukou, Henan Province, China.
Xiangkai ZengZhoukou Central Hospital Affiliated to Henan Medical University, Zhoukou, Henan Province, China.
Han LiZhoukou Central Hospital Affiliated to Henan Medical University, Zhoukou, Henan Province, China.
Haoqian TanZhoukou Central Hospital Affiliated to Henan Medical University, Zhoukou, Henan Province, China.
Junying LiuZhoukou Central Hospital Affiliated to Henan Medical University, Zhoukou, Henan Province, China.

Funding

Medical Science and Technology Tackling Program of Henan Province LHGJ20250990
6 · The paper itself

Abstract

NBALS efficacy in ACLF remains controversial. We aimed to determine if a "therapeutic window" exists by stratifying clinical outcomes based on baseline Model for End-Stage Liver Disease (MELD) scores. We searched PubMed, Embase, Cochrane Library, and Web of Science for RCTs and PSM-cohorts comparing NBALS to standard medical therapy (SMT). Primary outcome was 28-day mortality; MELD-stratified subgroup analyses and random-effects meta-regression were performed. Eleven studies (comprising 12 datasets) involving 1958 patients (991 NBALS vs. 967 SMT) were included. Overall, NBALS significantly reduced 28-day mortality compared with SMT (pooled RR 0.72, 95% CI [0.63-0.83], I

Indexed as

Acute-On-Chronic Liver FailureEnd Stage Liver DiseaseHumansRegression AnalysisSeverity of Illness IndexTreatment OutcomeACLFMELD scoremeta‐analysisNBALStherapeutic window

Identifiers

PMID42736474
PMCPMC13574923

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.