Evidence mapPaperPMID 42516780Full record

ArticleJGH open : an open access journal of gastroenterology and hepatology2026

Bioimpedance Analysis to Predict Clinical Outcomes of Liver Cirrhosis in a Prospective Cohort Study.

Mohammed Kanan, Michelle Luster, Saira Khaderi, Fasiha Kanwal, Aaron P Thrift, Abeer Alsarraj, Emad Sorial, Emad Salem, Hao Duong, Hashem B El-Serag

Abstract read
In one paragraph

Article in JGH open : an open access journal of gastroenterology and hepatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

10 authors.

Mohammed KananSection of Gastroenterology and Hepatology, Department of Medicine Baylor College of Medicine Houston Texas USA.
Michelle LusterSection of Gastroenterology and Hepatology, Department of Medicine Baylor College of Medicine Houston Texas USA.
Saira KhaderiSection of Gastroenterology and Hepatology, Department of Medicine Baylor College of Medicine Houston Texas USA.
Fasiha KanwalSection of Gastroenterology and Hepatology, Department of Medicine Baylor College of Medicine Houston Texas USA.
Aaron P ThriftSection of Epidemiology and Population Sciences, Department of Medicine Baylor College of Medicine Houston Texas USA.ORCID https://orcid.org/0000-0002-0084-5308
Abeer AlsarrajSection of Gastroenterology and Hepatology, Department of Medicine Baylor College of Medicine Houston Texas USA.
Emad SorialSection of Gastroenterology and Hepatology, Department of Medicine Baylor College of Medicine Houston Texas USA.
Emad SalemSection of Gastroenterology and Hepatology, Department of Medicine Baylor College of Medicine Houston Texas USA.ORCID https://orcid.org/0009-0008-5160-7431
Hao DuongSection of Gastroenterology and Hepatology, Department of Medicine Baylor College of Medicine Houston Texas USA.ORCID https://orcid.org/0009-0007-2086-7209
Hashem B El-SeragSection of Gastroenterology and Hepatology, Department of Medicine Baylor College of Medicine Houston Texas USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: Bioimpedance analysis (BIA) is a non-invasive method for estimating body composition, which plays a role in the development of cirrhosis. We investigated if BIA measures were associated with cirrhosis complications. Methods: We analyzed data from 566 participants in a prospective cohort study of cirrhosis patients from tertiary care clinics who underwent BIA at enrollment and regular follow up (20.3% female; 47.0% non-Hispanic White, 23.1% Hispanic, 27.7% Black; 47.7% metabolic and alcohol-associated liver disease [MetALD], 30.4% metabolic dysfunction-associated steatotic liver disease [MASLD], 1.9% alcohol-associated liver disease [ALD], 9.0% active hepatitis C virus [HCV]). We performed multivariable logistic regression to assess the association of BIA measures with etiology and prevalent decompensation and Cox proportional hazards regression to assess incident decompensation and HCC. Results: After adjustment for sex and race, body fat mass was associated with 14-fold increased odds of MASLD (adjusted odds ratio [aOR] 14.10, 95% confidence interval [CI] 5.25-37.85) and decreased odds of ALD (aOR 0.73, 95% CI 0.60-0.88). Lower odds of prevalent decompensation were seen in the highest tertile of trunk lean mass (aOR 0.39, 95% CI 0.21-0.73) and left arm lean mass (aOR 0.40, 95% CI 0.21-0.75) compared with their lowest tertiles. The middle tertile of visceral fat surface area showed an inverse association with incident decompensation (adjusted hazard ratio 0.19, 95% CI 0.04-0.88). There were no significant associations between BIA measures and incident HCC. Conclusions: BIA could be used as a prognostic tool for patients with cirrhosis, supporting its incorporation into clinical workflows.

Indexed as

alcoholepidemiologyhepatitis Cnonalcoholic fatty liver diseaserisk stratification

Identifiers

PMID42516780
PMCPMC13403763

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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 Socratic graph.