Evidence map›Paper›PMID 35436625›Full record

ArticleClinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association2023

Admission Serum Metabolites and Thyroxine Predict Advanced Hepatic Encephalopathy in a Multicenter Inpatient Cirrhosis Cohort.

Jasmohan S Bajaj, Puneeta Tandon, Jacqueline G O'Leary, K Rajender Reddy, Guadalupe Garcia-Tsao, Paul Thuluvath, Jennifer C Lai, Ram M Subramanian, Hugo E Vargas, Florence Wong and 4 more

Open access · bronzeAbstract readMulticenter Study
In one paragraph

Article in Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
3.5field-weighted citation impact, top 6% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
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  8. Machine learning techniques in hepatic encephalopathy: a scoping review.BMC medical informatics and decision making · 2025
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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

14 authors at 10 institutions in 2 countries.

Jasmohan S BajajDepartment of Medicine, Virginia Commonwealth University, Richmond Veterans Affairs Medical Center, Richmond, Virginia. Electronic address: jasmohan.bajaj@vcuhealth.org.
Puneeta TandonDepartment of Medicine, University of Alberta, Edmonton, Canada.
Jacqueline G O'LearyDepartment of Medicine, Dallas Veterans Affairs Medical Center, Dallas, Texas.
K Rajender ReddyDepartment of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Guadalupe Garcia-TsaoDepartment of Medicine, Yale University Medical Center, New Haven, Connecticut.
Paul ThuluvathDepartment of Medicine, Mercy Medical Center, Baltimore, Maryland.
Jennifer C LaiDepartment of Medicine, University of California San Francisco, San Francisco, California.
Ram M SubramanianDepartment of Medicine, Emory University Medical Center, Atlanta, Georgia.
Hugo E VargasDepartment of Medicine, Mayo Clinic Arizona, Phoenix, Arizona.
Florence WongDepartment of Medicine, University of Toronto, Toronto, Canada.
Andrew FaganDepartment of Medicine, Virginia Commonwealth University, Richmond Veterans Affairs Medical Center, Richmond, Virginia.
Sara McGeorgeDepartment of Medicine, Virginia Commonwealth University, Richmond Veterans Affairs Medical Center, Richmond, Virginia.
Leroy R ThackerDepartment of Medicine, Virginia Commonwealth University, Richmond Veterans Affairs Medical Center, Richmond, Virginia.
Patrick S KamathDepartment of Medicine, Mayo Clinic Rochester, Rochester, Minnesota.
Virginia Commonwealth University Medical Center · USUniversity Medical Center · USMayo Clinic · USMayo Clinic in Florida · USMercy Medical Center · USUniversity of Alberta · CAUniversity of California, San Francisco · USUniversity of Pennsylvania · USUniversity of Toronto · CAVeterans Health Administration · US

Funding

Fecal microbiota transplant for Alcohol-Associated CirrhosisR01AA029398 · NIAAA · VIRGINIA COMMONWEALTH UNIVERSITY · PI Jasmohan S Bajaj, ALEXANDER KHORUTS · 2022 to 2026
$2.9M
Gut Microbiota in the Modulation of Outcomes after Liver TransplantR21TR003095 · NCATS · VIRGINIA COMMONWEALTH UNIVERSITY · PI BAJAJ, JASMOHAN S, VERNA, ELIZABETH CLARICE · 2020 to 2021
$448k
CSRD VA I01 CX000176CSRD VA I01 CX001076CSRD VA I01 CX002472NCATS NIH HHS R21 TR003095NIAAA NIH HHS R01 AA029398
6 · The paper itself

Abstract

BACKGROUND &

aimsGrades 3 to 4 hepatic encephalopathy (advanced HE), also termed brain failure, is an organ failure that defines acute-on-chronic liver failure. It is associated with poor outcomes in cirrhosis but cannot be predicted accurately. We aimed to determine the admission metabolomic biomarkers able to predict the development of advanced HE with subsequent validation.

methodsProspective inpatient cirrhosis cohorts (multicenter and 2-center validation) without brain failure underwent admission serum collection and inpatient follow-up evaluation. Serum metabolomics were analyzed to predict brain failure on random forest analysis and logistic regression. A separate validation cohort also was recruited.

resultsThe multicenter cohort included 602 patients, of whom 144 developed brain failure (105 only brain failure) 3 days after admission. Unadjusted random forest analysis showed that higher admission microbially derived metabolites and lower isoleucine, thyroxine, and lysophospholipids were associated with brain failure development (area under the curve, 0.87 all; 0.90 brain failure only). Logistic regression area under the curve with only clinical variables significantly improved with metabolites (95% CI 0.65-0.75; P = .005). Four metabolites that significantly added to brain failure prediction were low thyroxine and maltose and high methyl-4-hydroxybenzoate sulfate and 3-4 dihydroxy butyrate. Thyroxine alone also significantly added to the model (P = .05). The validation cohort including 81 prospectively enrolled patients, of whom 11 developed brain failure. Admission hospital laboratory thyroxine levels predicted brain failure development despite controlling for clinical variables with high specificity.

conclusionsIn a multicenter inpatient cohort, admission serum metabolites, including thyroxine, predicted advanced HE development independent of clinical factors. Admission low local laboratory thyroxine levels were validated as a predictor of advanced HE development in a separate cohort.

Indexed as

Hepatic EncephalopathyFibrosisHumansInpatientsLiver CirrhosisProspective StudiesThyroxineThyroxineAcute-on-Chronic Liver FailureBrain FailureMetabolomicsOutcomesThyroid

Identifiers

PMID35436625
PMCPMC11000256
OpenAlexW4224093093

What OpenQuestion holds

Textmetadata
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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.