Evidence map›Paper›PMID 41217780›Full record

Trial reportDiabetes care2026

Baseline Risk and Longitudinal Changes in kidneyintelX.dkd and Its Association With Kidney Outcomes in the CANVAS and CREDENCE Trials.

Erik Moedt, Steven G Coca, Katherine Edwards, Brendon L Neuen, Clare Arnott, Stephan J L Bakker, Fergus Fleming, Hiddo J L Heerspink

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Diabetes care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Erik MoedtDepartment of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands.ORCID 0009-0003-3983-5136
Steven G CocaBarbara T. Murphy Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, NY.
Katherine EdwardsRenalytix AI, PLC, New York, NY.
Brendon L NeuenThe George Institute for Global Health, University of South Wales, Sydney, New South Wales, Australia.
Clare ArnottThe George Institute for Global Health, University of South Wales, Sydney, New South Wales, Australia.ORCID 0000-0001-9370-9913
Stephan J L BakkerDepartment of Internal Medicine, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands.
Fergus FlemingRenalytix AI, PLC, New York, NY.
Hiddo J L HeerspinkDepartment of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands.ORCID 0000-0002-3126-3730

Funding

HORIZON EUROPE Health 101095146
6 · The paper itself

Abstract

objectiveWe evaluated the prognostic and clinical utility of kidneyintelX.dkd, a biomarker-based risk score, in patients with type 2 diabetes and a broad range of chronic kidney disease (CKD) by assessing its association with kidney outcomes at baseline and longitudinally, comparing it with the established Kidney Disease Improving Global Outcomes (KDIGO) risk classification, and examining its responsiveness to canagliflozin. RESEARCH DESIGN AND

methodsWe measured tumor necrosis factor receptor-1 (TNFR-1), TNFR-2, and kidney injury molecule-1 (KIM-1) in banked plasma samples at baseline and year 1 and calculated kidneyintelX.dkd scores of participants with CKD G1-G3b from two large randomized controlled trials (Canagliflozin Cardiovascular Assessment Study [CANVAS] and Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation [CREDENCE]). We assessed concordance between KDIGO and kidneyintelX.dkd risk levels, evaluated associations of baseline and 1-year changes in kidneyintelX.dkd with kidney outcomes, and examined treatment effects of canagliflozin versus placebo.

resultsMean kidneyintelX.dkd scores increased across higher KDIGO risk categories, but individual-level differences revealed improved risk reclassification. The kidneyintelX.dkd score was independently associated with kidney outcomes and more strongly predictive than KDIGO classification. At 1 year, canagliflozin significantly lowered kidneyintelX.dkd score versus placebo, and longitudinal reductions by 1 year were associated with lower subsequent risk of kidney outcomes, independent of changes in estimated glomerular filtration rate or urinary albumin-to-creatinine ratio. Absolute risk reductions with canagliflozin were largest among those at high kidneyintelX.dkd risk.

conclusionsThe kidneyintelX.dkd score adds prognostic value beyond clinical classification, reflects canagliflozin treatment response, and helps identify individuals most likely to benefit from therapy. These findings support a role for the kidneyintelX.dkd score in personalized risk assessment and monitoring in type 2 diabetes and CKD in prospective studies and clinical practice.

Indexed as

Diabetes Mellitus, Type 2Diabetic NephropathiesRenal Insufficiency, ChronicAgedBiomarkersCanagliflozinFemaleGlomerular Filtration RateHepatitis A Virus Cellular Receptor 1HumansLongitudinal StudiesMaleMiddle AgedSodium-Glucose Transporter 2 InhibitorsBiomarkersCanagliflozinHepatitis A Virus Cellular Receptor 1Sodium-Glucose Transporter 2 Inhibitors

Identifiers

PMID41217780
PMCPMC12719711

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Registered trials

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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.