Evidence map›Paper›PMID 42770295›Full record

ArticleJCI insight2026

Urine leukemia inhibitory factor predicts kidney function recovery in patients with acute interstitial nephritis.

Long Qian, Megan L Baker, Laura Aponte Becerra, Cathleen Liang, Emma Koval, Kyra Shelton, Daris Javed, Gilbert Moeckel, Deepika Kumar, Avi Z Rosenberg and 10 more

Abstract read
In one paragraph

Article in JCI insight, 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

20 authors.

Long QianSection of Nephrology and.
Megan L BakerSection of Nephrology and.
Laura Aponte BecerraSection of Nephrology and.
Cathleen LiangSection of Nephrology and.
Emma KovalSection of Nephrology and.
Kyra SheltonSection of Nephrology and.
Daris JavedSection of Nephrology and.
Gilbert MoeckelDepartment of Pathology, Yale University, New Haven, Connecticut, USA.
Deepika KumarDepartment of Pathology, Yale University, New Haven, Connecticut, USA.
Avi Z RosenbergDepartment of Pathology, Johns Hopkins University, Baltimore, Maryland, USA.
Michael KupermanDepartment of Pathology, Cleveland Clinic, Cleveland, Ohio, USA.
Tinyi ChuDepartment of Genome Sciences, University of Virginia, Charlottesville, Virginia, USA.
Wassim ObeidDivision of Nephrology, Johns Hopkins University, Baltimore, Maryland, USA.
Xuefei TianSection of Nephrology and.
Chirag R ParikhDivision of Nephrology, Johns Hopkins University, Baltimore, Maryland, USA.
Leyuan XuSection of Nephrology and.
Jonathan BaraschDivision of Nephrology, Columbia University, New York, New York, USA.
Shuta IshibeSection of Nephrology and.
Lloyd G CantleySection of Nephrology and.
Dennis G MoledinaSection of Nephrology and.

Funding

Biomarkers for acute interstitial nephritis in humansR01DK128087 · NIDDK · YALE UNIVERSITY · PI MOLEDINA, DENNIS G. · 2021 to 2025
$2.9M
Defining the Pathogenesis and Prognosis of Human Acute Interstitial NephritisR01DK126815 · NIDDK · YALE UNIVERSITY · PI CANTLEY, LLOYD G · 2020 to 2024
$2.6M
NIDDK NIH HHS R01 DK126815NIDDK NIH HHS R01 DK128087
6 · The paper itself

Abstract

A urine protein called LIF predicts kidney recovery after a common kidney injury called acute interstitial nephritis, potentially guiding treatment decisions and prognosis.

Indexed as

KidneyLeukemia Inhibitory FactorNephritis, InterstitialAcute DiseaseBiomarkersHumansPrognosisRecovery of FunctionBiomarkersLeukemia Inhibitory FactorBiomarkersClinical ResearchFibrosisNephrologyProteomics

Identifiers

PMID42770295
PMCPMC13596714

What OpenQuestion holds

Textmetadata
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.