Evidence map›Paper›PMID 31652022›Full record

Trial reportPediatric transplantation2020

The use of urinary biomarkers to predict acute kidney injury in children after liver transplant.

Dana Y Fuhrman, John A Kellum, Emily L Joyce, Yosuke Miyashita, George V Mazariegos, Armando Ganoza, James E Squires

Open access · greenAbstract readClinical Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Pediatric transplantation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 5 pooled it
1.1field-weighted citation impact, top 22% 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

13 citing papers in PubMed, 5 syntheses or guidelines pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
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

7 authors at 2 institutions in 1 country.

Dana Y FuhrmanDepartment of Critical Care Medicine, University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, PA, USA.ORCID 0000-0002-3672-7960
John A KellumDepartment of Critical Care Medicine, The Center for Critical Care Nephrology, Pittsburgh, PA, USA.
Emily L JoyceDepartment of Critical Care Medicine, The Center for Critical Care Nephrology, Pittsburgh, PA, USA.
Yosuke MiyashitaDivision of Pediatric Nephrology, Department of Pediatrics, University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, PA, USA.
George V MazariegosHillman Center for Pediatric Liver Transplantation, University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, PA, USA.ORCID 0000-0002-2624-8632
Armando GanozaHillman Center for Pediatric Liver Transplantation, University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, PA, USA.
James E SquiresDivision of Pediatric Gastroenterology, Hepatology and Nutrition, University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, PA, USA.
Children's Hospital of Pittsburgh · USSociety of Critical Care Medicine · US

Funding

Pittsburgh Liver Research CenterP30DK120531 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Kari N Nejak-Bowen · 2019 to 2026
$10.9M
Renal Fitness in Young Adults with Congenital Heart DiseaseK23DK116973 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI FUHRMAN, DANA YOUNG · 2019 to 2023
$1.2M
NIDDK NIH HHS K23 DK116973NIDDK NIH HHS P30 DK120531
6 · The paper itself

Abstract

backgroundAKI after pediatric liver transplantation is associated with increased morbidity and mortality. The role of urinary biomarkers for the prediction of AKI in pediatric patients after liver transplantation has not been previously reported. The primary objective of this prospective pilot study was to determine the predictive capabilities of urinary KIM-1, NGAL, TIMP-2, and IGFBP7 for diagnosing AKI.

methodsSixteen children undergoing liver transplantation were enrolled in the study over a 19-month time period. The Kidney Disease Improving Outcomes criteria for urine output and serum creatinine were used to define AKI. Predictive ability was evaluated using the area under the curve obtained by ROC analysis.

resultsAKI occurred in 6 (37.5%) of the patients between 2 and 4 days after transplant. There were no differences in any of the biomarkers prior to transplant. When obtained within 6 hours after transplant, the area under the ROC curve for predicting AKI was 0.758 (95% CI: 0.458-1.00) for KIM-1, 0.900 (95% CI: 0.724-1.00) for NGAL, and 0.933 (95% CI: 0.812-1.00) for the product of TIMP-2 and IGFBP7 ([TIMP-2]·[IGFBP7]).

conclusionsOur results show that both NGAL and [TIMP-2]·[IGFBP7] provide significant discrimination for AKI risk following liver transplant in children. Larger studies are needed to determine the optimal time point for measuring these biomarkers and to validate our findings.

Indexed as

Liver TransplantationAcute Kidney InjuryAdolescentBiomarkersChildChild, PreschoolClinical Decision RulesFeasibility StudiesFemaleHepatitis A Virus Cellular Receptor 1HumansInfantInfant, NewbornInsulin-Like Growth Factor Binding ProteinsLipocalin-2MaleBiomarkersHAVCR1 protein, humanHepatitis A Virus Cellular Receptor 1insulin-like growth factor binding protein-related protein 1Insulin-Like Growth Factor Binding ProteinsLCN2 protein, humanLipocalin-2TIMP2 protein, humanTissue Inhibitor of Metalloproteinase-2kidney diseaseliver transplantationpediatricstubular biomarkers

Identifiers

PMID31652022
PMCPMC7216780
OpenAlexW2981717066

What OpenQuestion holds

Textmetadata
LicenceTDM
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.