Evidence map›Paper›PMID 35509420›Full record

ArticleTherapeutic advances in gastroenterology2022

Prognostic utility of magnetic resonance elastography and MEFIB index in predicting liver-related outcomes and mortality in individuals at risk of and with nonalcoholic fatty liver disease.

Veeral Ajmera, Khang Nguyen, Nobuharu Tamaki, Suzanne Sharpton, Ricki Bettencourt, Rohit Loomba

Open access · goldAbstract read
In one paragraph

Article in Therapeutic advances in gastroenterology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 4 pooled it
4.5field-weighted citation impact, top 4% of its field
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

17 citing papers in PubMed, 4 syntheses or guidelines pooled it, 30 citations in OpenAlex.

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  14. [Liver fibrosis screening, evaluation pathway, and management in patients with fatty liver].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2023
    Review
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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

6 authors at 2 institutions in 2 countries.

Veeral AjmeraNAFLD Research Center, Division of Gastroenterology, University of California at San Diego, 9500 Gilman Drive, ACTRI Building, 1W507, La Jolla, CA 92093-0887, USA.
Khang NguyenNAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, CA, USA.
Nobuharu TamakiNAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, CA, USADepartment of Gastroenterology and Hepatology, Musashino Red Cross Hospital, Tokyo, Japan.
Suzanne SharptonNAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, CA, USA.ORCID https://orcid.org/0000-0001-7722-5716
Ricki BettencourtNAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, CA, USA.
Rohit LoombaNAFLD Research Center, Division of Gastroenterology, University of California at San Diego, 9500 Gilman Drive, ACTRI Building, 2W202, La Jolla, CA 92093-0887, USA.ORCID https://orcid.org/0000-0002-4845-9991
University of California San Diego · USMusashino Red Cross Hospital · JP

Funding

UC San Diego Clinical and Translational Research InstituteUL1TR001442 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI FIRESTEIN, GARY S, HOGARTH, MICHAEL · 2015 to 2024
$88.3M
Yeast Genetics and Stress Response Genes-BiomedicalP42ES010337 · NIEHS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI TUKEY, ROBERT H · 2000 to 2022
$69.8M
San Diego Digestive Diseases Research CenterP30DK120515 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Bernd G. Schnabl · 2019 to 2026
$10.8M
QUS Technology for Diagnosis and Grading of Hepatic Steatosis in NAFLDR01DK106419 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LOOMBA, ROHIT, SIRLIN, CLAUDE B · 2015 to 2019
$3.4M
A Novel Multimodal Approach to Characterize NAFLD Severity and PrognosisK23DK119460 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI AJMERA, VEERAL HARESH · 2019 to 2023
$1.1M
NCATS NIH HHS UL1 TR001442NIDDK NIH HHS K23 DK119460NIDDK NIH HHS P30 DK120515NIDDK NIH HHS R01 DK106419NIEHS NIH HHS P42 ES010337
6 · The paper itself

Abstract

Background: Magnetic resonance elastography (MRE) is an accurate biomarker of liver fibrosis; however, limited data characterize its association with outcomes. We aimed to evaluate the association between liver stiffness (LS) on MRE and liver-related outcomes. Methods: This is a longitudinal, retrospective analysis of subjects at risk of NAFLD who had MRE assessment. LS was estimated using MRE, and liver fat was assessed using magnetic resonance imaging proton density fat fraction. Univariable and multivariable survival and regression analyses were used to assess the association between LS on MRE and liver-related outcomes including a cumulative primary outcome of hepatic decompensation, hepatocellular carcinoma (HCC), or death. Results: In all, 265 patients (68% women) with a mean age of 50 (±18) years and 44% Hispanic ethnicity and 45.3% with NAFLD were included. A total of 76 liver-related events or death occurred, and there was 453 person-years of follow-up time in 97 patients with available follow-up. Each 1-kPa increase in LS was associated with 2.20-fold (95% CI: 1.70-2.84, Conclusion: LS assessed by MRE is associated with hepatic decompensation and death, and the MEFIB combination of MRE with FIB-4 may have high negative predictive value for liver-related events.

Indexed as

ascitesbiomarkercirrhosisnonalcoholic fatty liver diseasenoninvasiveportal hypertensionvarices

Identifiers

PMID35509420
PMCPMC9058353
OpenAlexW4226414225

What OpenQuestion 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 OpenQuestion graph.