Evidence map›Paper›PMID 31013714›Full record

ArticleJournal of clinical medicine2019

A Novel Multi-Biomarker Assay for Non-Invasive Quantitative Monitoring of Kidney Injury.

Drew Watson, Joshua Y C Yang, Reuben D Sarwal, Tara K Sigdel, Juliane M Liberto, Izabella Damm, Victoria Louie, Shristi Sigdel, Devon Livingstone, Katherine Soh and 4 more

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04705766 (The KIDCOV Study), which is not on this map. Cited by 24 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 2 pooled it
4.5field-weighted citation impact, top 5% 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.

NCT04705766 recruitingnot on this mapstarted 2021, after this paper: background citation

The KIDCOV Study: ASSESSMENT of SARS-CoV-2 Without HOSPITALIZATION as a RISK FACTOR for ACUTE KIDNEY INJURY

Typeobservational_patient_registrySponsorUniversity of California, San FranciscoRan2021 to 2027Enrolled2,000ConditionsSARS-CoV Infection, Covid19, Corona Virus Infection, Acute Kidney InjuryArmsUrine Collection
3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 2 syntheses or guidelines pooled it, 44 citations in OpenAlex.

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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 2 institutions in 1 country.

Drew WatsonKIT Bio, 665 3rd Street, San Francisco, CA 94107, USA. drew@kit.bio.
Joshua Y C YangKIT Bio, 665 3rd Street, San Francisco, CA 94107, USA. joshua.yang@ucsf.edu.ORCID 0000-0003-2410-7817
Reuben D SarwalDepartment of Surgery, University of California San Francisco, San Francisco, CA 94143, USA. reuben.sarwal@ucsf.edu.
Tara K SigdelDepartment of Surgery, University of California San Francisco, San Francisco, CA 94143, USA. tara.sigdel@ucsf.edu.
Juliane M LibertoDepartment of Surgery, University of California San Francisco, San Francisco, CA 94143, USA. juliane.liberto@ucsf.edu.ORCID 0000-0003-1927-5058
Izabella DammDepartment of Surgery, University of California San Francisco, San Francisco, CA 94143, USA. izabella.damm@ucsfmedctr.org.
Victoria LouieDepartment of Surgery, University of California San Francisco, San Francisco, CA 94143, USA. victorialouie11@gmail.com.
Shristi SigdelDepartment of Surgery, University of California San Francisco, San Francisco, CA 94143, USA. shristisigdel@gmail.com.
Devon LivingstoneMasters in Translational Medicine Program, University of California Berkeley, Berkeley, CA 94720, USA. devonlivingstone@berkeley.edu.
Katherine SohMasters in Translational Medicine Program, University of California Berkeley, Berkeley, CA 94720, USA. katherine_soh@berkeley.edu.
Arjun ChakrabortyMasters in Translational Medicine Program, University of California Berkeley, Berkeley, CA 94720, USA. archakra@berkeley.edu.
Michael LiangMasters in Translational Medicine Program, University of California Berkeley, Berkeley, CA 94720, USA. liangmichael@berkeley.edu.
Pei-Chen LinDepartment of Surgery, University of California San Francisco, San Francisco, CA 94143, USA. peichen@berkeley.edu.
Minnie M SarwalKIT Bio, 665 3rd Street, San Francisco, CA 94107, USA. minnie.sarwal@ucsf.edu.
University of California, San Francisco · USUniversity of California, Berkeley · US

Funding

Novel Therapies to Modulate the Inflammatory Alloresponse in Renal GraftsU01AI113362 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI VINCENTI, FLAVIO · 2014 to 2023
$15.2M
The KIDCOV Study: Assessment of Kidney Injury and Associated Risk Factors for SARS-CoV-2R01DK109720 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI REISER, JOCHEN, SARWAL, MINNIE M · 2017 to 2021
$3.2M
NIAID NIH HHS U01 AI113362NIDDK NIH HHS R01 DK109720NIH HHS 1R21 AI-075256-01A2
6 · The paper itself

Abstract

The current standard of care measures for kidney function, proteinuria, and serum creatinine (SCr) are poor predictors of early-stage kidney disease. Measures that can detect chronic kidney disease in its earlier stages are needed to enable therapeutic intervention and reduce adverse outcomes of chronic kidney disease. We have developed the Kidney Injury Test (KIT) and a novel KIT Score based on the composite measurement and validation of multiple biomarkers across a unique set of 397 urine samples. The test is performed on urine samples that require no processing at the site of collection and without target sequencing or amplification. We sought to verify that the pre-defined KIT test, KIT Score, and clinical thresholds correlate with established chronic kidney disease (CKD) and may provide predictive information on early kidney injury status above and beyond proteinuria and renal function measurements alone. Statistical analyses across six DNA, protein, and metabolite markers were performed on a subset of residual spot urine samples with CKD that met assay performance quality controls from patients attending the clinical labs at the University of California, San Francisco (UCSF) as part of an ongoing IRB-approved prospective study. Inclusion criteria included selection of patients with confirmed CKD and normal healthy controls; exclusion criteria included incomplete or missing information for sample classification, logistical delays in transport/processing of urine samples or low sample volume, and acute kidney injury. Multivariate logistic regression of kidney injury status and likelihood ratio statistics were used to assess the contribution of the KIT Score for prediction of kidney injury status and stage of CKD as well as assess the potential contribution of the KIT Score for detection of early-stage CKD above and beyond traditional measures of renal function. Urine samples were processed by a proprietary immunoprobe for measuring cell-free DNA (cfDNA), methylated cfDNA, clusterin, CXCL10, total protein, and creatinine. The KIT Score and stratified KIT Score Risk Group (high versus low) had a sensitivity and specificity for detection of kidney injury status (healthy or CKD) of 97.3% (95% CI: 94.6-99.3%) and 94.1% (95% CI: 82.3-100%). In addition, in patients with normal renal function (estimated glomerular filtration rate (eGFR) ≥ 90), the KIT Score clearly identifies those with predisposing risk factors for CKD, which could not be detected by eGFR or proteinuria (

Indexed as

biomarkercfDNAchronic kidney diseaseeGFRKIT Assaynon-invasiveurine

Identifiers

PMID31013714
PMCPMC6517941
OpenAlexW2939879954

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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.