Evidence mapPaperPMID 40873071Full record

ReviewZhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology2025

[Metabolic associated fatty liver disease induced cirrhosis: epidemiology, risk factors, and new strategies for precise prevention and control].

X Bai, Q Q Chen, J Li

Abstract readReviewEnglish Abstract
In one paragraph

Review in Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology, 2025. 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

3 authors.

X BaiDepartment of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China.
Q Q ChenDepartment of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China Department of Nephrology, the Affiliated Huai'an Hospital of Xuzhou Medical University and Huai'an Second People's Hospital, Huai'an 223000, China.
J LiDepartment of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China.

Funding

National Natural Science Foundation of China 82170609Natural Science Foundation of Jiangsu Province BK20231118
6 · The paper itself

Abstract

Cirrhosis caused by metabolic associated fatty liver disease (MAFLD) has become a major global health challenge. Genetics, metabolic disorders, viruses, and other factors jointly drive the progression of this disease. The development of high-precision, non-invasive models for these diseases within the context of artificial intelligence is a novel direction for future diagnosis. Therapies that improve metabolism and antifibrosis should be strongly emphasized and urgently implemented to establish a standardized and unified endpoint evaluation system for anti-cirrhosis drug trials and therefore accelerate new drug development. This article systematically explores the epidemiological characteristics, risk factors, and the latest diagnosis and treatment strategies, with the aim to provide a reference basis for clinical practice.

Indexed as

Fatty LiverLiver CirrhosisHumansNon-alcoholic Fatty Liver DiseaseRisk Factors

Identifiers

PMID40873071
PMCPMC12861782

What Socratic 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 Socratic graph.