Evidence map›Paper›PMID 39713167›Full record

ReviewWorld journal of gastroenterology2024

Inflammatory biomarkers as cost-effective predictive tools in metabolic dysfunction-associated fatty liver disease.

Davide Ramoni, Luca Liberale, Fabrizio Montecucco

Abstract readReview
In one paragraph

Review in World journal of gastroenterology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
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.

Davide RamoniDepartment of Internal Medicine, University of Genoa, Genoa 16132, Italy.
Luca LiberaleDepartment of Internal Medicine, University of Genoa, Genoa 16132, Italy.
Fabrizio MontecuccoDepartment of Internal Medicine, University of Genoa, Genoa 16132, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Qu and Li emphasize a fundamental aspect of metabolic dysfunction-associated fatty liver disease in their manuscript, focusing on the critical need for non-invasive diagnostic tools to improve risk stratification and predict the progression to severe liver complications. Affecting approximately 25% of the global population, metabolic dysfunction-associated fatty liver disease is the most common chronic liver condition, with higher prevalence among those with obesity. This letter stresses the importance of early diagnosis and intervention, especially given the rising incidence of obesity and metabolic syndrome. Research advancements provide insight into the potential of biomarkers (particularly inflammation-related) as predictive tools for disease progression and treatment response. This overview addresses pleiotropic biomarkers linked to chronic inflammation and cardiometabolic disorders, which may aid in risk stratification and treatment efficacy monitoring. Despite progress, significant knowledge gaps remain in the clinical application of these biomarkers, necessitating further research to establish standardized protocols and validate their utility in clinical practice. Understanding the complex interactions among these factors opens new avenues to enhance risk assessment, leading to better patient outcomes and addressing the public health burden of this worldwide condition.

Indexed as

BiomarkersMetabolic SyndromeNon-alcoholic Fatty Liver DiseaseCost-Benefit AnalysisDisease ProgressionEarly DiagnosisHumansInflammationLiverObesityPredictive Value of TestsRisk AssessmentBiomarkersAdipokinesCardiometabolic risk assessmentInflammatory biomarkersMetabolic dysfunction-associated fatty liver diseaseMetabolic syndromeOsteopontin

Identifiers

PMID39713167
PMCPMC11612858

What OpenQuestion holds

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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.