Evidence map›Paper›PMID 42564411›Full record

ArticleHepatology forum2026

Plasma

Burge Ulukan, Hong Yang, Hande Uludag, Cheng Zhang, Ali Mutlu, Murat Dayangac, Murat Akyildiz, Buket Yigit, Shaghayegh Soleimani, Hale Kirimlioglu and 6 more

Abstract read
In one paragraph

Article in Hepatology forum, 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

16 authors.

Burge UlukanDepartment of Gastroenterology and Hepatology, School of Medicine, Koc University, Istanbul, Turkiye.
Hong YangScience for Life Laboratory, KTH- Royal Institute of Technology, Stockholm, Sweden.
Hande UludagDepartment of Gastroenterology and Hepatology, School of Medicine, Koc University, Istanbul, Turkiye.
Cheng ZhangScience for Life Laboratory, KTH- Royal Institute of Technology, Stockholm, Sweden.
Ali MutluSchool of Medicine, Koc University, Istanbul, Turkiye.
Murat DayangacDepartment of General Surgery, Faculty of Medicine, Medipol University, Istanbul, Turkiye.
Murat AkyildizDepartment of Gastroenterology and Hepatology, School of Medicine, Koc University, Istanbul, Turkiye.
Buket YigitDepartment of Gastroenterology and Hepatology, School of Medicine, Koc University, Istanbul, Turkiye.
Shaghayegh SoleimaniDepartment of Gastroenterology and Hepatology, School of Medicine, Koc University, Istanbul, Turkiye.
Hale KirimliogluDepartment of Pathology, School of Medicine, Acıbadem Mehmet Ali Aydınlar University, Istanbul, Turkiye.
Burcu SakaDepartment of Pathology, School of Medicine, Koc University, Istanbul, Turkiye.
Cigdem Ataizi CelikelDepartment of Medical Pathology, School of Medicine, Marmara University, Istanbul, Turkiye.
Fatih ErenInstitute of Gastroenterology, Marmara University, Istanbul, Turkiye.
Adil MardinogluScience for Life Laboratory, KTH- Royal Institute of Technology, Stockholm, Sweden.
Yusuf YilmazDepartment of Gastroenterology and Hepatology, School of Medicine, Recep Tayyip Erdogan University, Rize, Turkiye.
Mujdat ZeybelDepartment of Gastroenterology and Hepatology, School of Medicine, Koc University, Istanbul, Turkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aim: While liver biopsy remains the reference standard for assessing hepatic fibrosis, the major prognostic factor in metabolic dysfunction-associated steatotic liver disease (MASLD), its inherent limitations have driven the search for innovative non-invasive diagnostic tests. In this study, we sought to evaluate the diagnostic accuracy of plasma Materials and Methods: Patients with biopsy-proven MASLD and healthy controls were recruited from the three institutions. Quantitative methylation of circulating cell-free DNA was assessed using bisulfite modification and pyrosequencing. The resulting data were used to develop linear discriminant analysis, random forest, and support vector machine algorithms to identify patients at different stages of fibrosis. Results: The study included 234 patients with histologically confirmed MASLD and 43 healthy controls. Each dataset was validated using an independent cohort. Advanced fibrosis was associated with elevated plasma Conclusion: Supervised machine learning algorithms incorporating plasma

Indexed as

Cell-free DNADNA methylationliver fibrosismachine learning algorithmsMASLDpredictive models

Identifiers

PMID42564411
PMCPMC13442723

What Socratic holds

Textmetadata
LicenceCC BY-NC
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.