Evidence map›Paper›PMID 35708187›Full record

ReviewDiabetes/metabolism research and reviews2022

Review of potential biomarkers of inflammation and kidney injury in diabetic kidney disease.

Vuthi Khanijou, Neda Zafari, Melinda T Coughlan, Richard J MacIsaac, Elif I Ekinci

Open access · greenAbstract readReview
In one paragraph

Review in Diabetes/metabolism research and reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
5.9field-weighted citation impact, top 3% 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

22 citing papers in PubMed, 42 citations in OpenAlex.

  1. Article
  2. Multi-Omics Integration IdentifiesInternational journal of molecular sciences · 2025
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  19. The Molecular Mechanism of Renal Tubulointerstitial Inflammation Promoting Diabetic Nephropathy.International journal of nephrology and renovascular disease · 2023
    Review
  20. Article
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

5 authors at 2 institutions in 1 country.

Vuthi KhanijouMelbourne Medical School, University of Melbourne, Austin Health, Melbourne, Victoria, Australia.ORCID 0000-0001-7402-3190
Neda ZafariDepartment of Medicine, University of Melbourne, Austin Health, Melbourne, Victoria, Australia.
Melinda T CoughlanDepartment of Diabetes, Central Clinical School, Monash University, Alfred Medical Research Alliance, Melbourne, Victoria, Australia.
Richard J MacIsaacDepartment of Endocrinology & Diabetes, St. Vincent's Hospital Melbourne and University of Melbourne, Melbourne, Victoria, Australia.
Elif I EkinciMelbourne Medical School, University of Melbourne, Austin Health, Melbourne, Victoria, Australia.
The University of Melbourne · AUBaker Heart and Diabetes Institute · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic kidney disease is expected to increase rapidly over the coming decades with rising prevalence of diabetes worldwide. Current measures of kidney function based on albuminuria and estimated glomerular filtration rate do not accurately stratify and predict individuals at risk of declining kidney function in diabetes. As a result, recent attention has turned towards identifying and assessing the utility of biomarkers in diabetic kidney disease. This review explores the current literature on biomarkers of inflammation and kidney injury focussing on studies of single or multiple biomarkers between January 2014 and February 2020. Multiple serum and urine biomarkers of inflammation and kidney injury have demonstrated significant association with the development and progression of diabetic kidney disease. Of the inflammatory biomarkers, tumour necrosis factor receptor-1 and -2 were frequently studied and appear to hold most promise as markers of diabetic kidney disease. With regards to kidney injury biomarkers, studies have largely targeted markers of tubular injury of which kidney injury molecule-1, beta-2-microglobulin and neutrophil gelatinase-associated lipocalin emerged as potential candidates. Finally, the use of a small panel of selective biomarkers appears to perform just as well as a panel of multiple biomarkers for predicting kidney function decline.

Indexed as

Diabetes MellitusDiabetic NephropathiesAlbuminuriaBiomarkersGlomerular Filtration RateHepatitis A Virus Cellular Receptor 1HumansInflammationKidneyLipocalin-2BiomarkersHepatitis A Virus Cellular Receptor 1Lipocalin-2biomarkersdiabetic kidney diseaseinflammationkidney injurykidney injury Molecule-1 [KIM-1]tumour necrosis factor receptor [TNFR]

Identifiers

PMID35708187
PMCPMC9541229
OpenAlexW4283019646

What Socratic 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 Socratic graph.