Derivation and independent validation of kidneyintelX.dkd: A prognostic test for the assessment of diabetic kidney disease progression.

Girish N Nadkarni^1,2,3, Sharon Stapleton⁴, Dipti Takale⁵, Katherine Edwards⁴, Kara Moran⁴, Gohar Mosoyan¹, Michael K Hansen⁶, Michael J Donovan⁴, Hiddo J L Heerspink⁷, Fergus Fleming⁴, Steven G Coca¹

¹Barbara T Murphy Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

²Division of Digital and Data Driven Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

³The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

⁴Renalytix AI, PLC, New York, New York, USA.

⁵Persistent Systems, Pune, India.

⁶Janssen Research & Development, LLC, Spring House, Pennsylvania, USA.

⁷Department of Clinical Pharmacy and Pharmacology, University of Groningen, Groningen, The Netherlands.

PubMed DOI

Abstract

AIMS: To develop and validate an updated version of KidneyIntelX (kidneyintelX.dkd) to stratify patients for risk of progression of diabetic kidney disease (DKD) stages 1 to 3, to simplify the test for clinical adoption and support an application to the US Food and Drug Administration regulatory pathway. METHODS: We used plasma biomarkers and clinical data from the Penn Medicine Biobank (PMBB) fo…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free Account Sign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.