Evidence map›Paper›PMID 38185870›Full record

ArticleJournal of primary care & community health

A Real-World Precision Medicine Program Including the KidneyIntelX Test Effectively Changes Management Decisions and Outcomes for Patients With Early-Stage Diabetic Kidney Disease.

Joji Tokita, David Lam, Aida Vega, Stephanie Wang, Leonard Amoruso, Tamara Muller, Nidhi Naik, Shivani Rathi, Sharlene Martin, Azadeh Zabetian and 10 more

Erratum issued Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Journal of primary care & community health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT04802395 (Real World Evidence Clinical Utility Study of KidneyIntelX in Patients With Type 2 Diabetes and Chronic Kidney Disease), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.7field-weighted citation impact, top 9% 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.

NCT04802395 recruitingnot on this map

Real World Evidence Clinical Utility Study of KidneyIntelX in Patients With Type 2 Diabetes and Chronic Kidney Disease

TypeobservationalSponsorRenalytix AI, Inc.Ran2021 to 2026Enrolled10,000ConditionsChronic Kidney Diseases, Diabetic Kidney DiseaseArmsKidneyIntelX
3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. kidneyintelX.dkd: An Innovation in Precision Medicine for Diabetic Kidney Disease.Journal of the American Society of Nephrology : JASN · 2025
    Article
  5. Article
  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

20 authors at 2 institutions in 1 country.

Joji TokitaIcahn School of Medicine at Mount Sinai, New York, NY, USA.
David LamIcahn School of Medicine at Mount Sinai, New York, NY, USA.
Aida VegaIcahn School of Medicine at Mount Sinai, New York, NY, USA.
Stephanie WangIcahn School of Medicine at Mount Sinai, New York, NY, USA.
Leonard AmorusoIcahn School of Medicine at Mount Sinai, New York, NY, USA.
Tamara MullerIcahn School of Medicine at Mount Sinai, New York, NY, USA.
Nidhi NaikIcahn School of Medicine at Mount Sinai, New York, NY, USA.
Shivani RathiIcahn School of Medicine at Mount Sinai, New York, NY, USA.
Sharlene MartinIcahn School of Medicine at Mount Sinai, New York, NY, USA.
Azadeh ZabetianRenalytix AI, Inc., New York, NY, USA.
Catherine LiuIcahn School of Medicine at Mount Sinai, New York, NY, USA.
Catherine SinfieldIcahn School of Medicine at Mount Sinai, New York, NY, USA.
Tony McNicholasRenalytix AI, Inc., New York, NY, USA.
Fergus FlemingRenalytix AI, Inc., New York, NY, USA.
Steven G CocaIcahn School of Medicine at Mount Sinai, New York, NY, USA.
Girish N NadkarniIcahn School of Medicine at Mount Sinai, New York, NY, USA.
Roger TunRenalytix AI, Inc., New York, NY, USA.
Mike KattanCleveland Clinic, Cleveland, OH, USA.
Michael J DonovanIcahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID 0000-0003-0772-598X
Arshad K RahimIcahn School of Medicine at Mount Sinai, New York, NY, USA.
Icahn School of Medicine at Mount Sinai · USCleveland Clinic · US

Funding

COVID and Translational Science supercomputer (CATS)S10OD030463 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KOVATCH, PATRICIA · 2021 to 2021
$2.0M
Big Omics Data Engine 2 SupercomputerS10OD026880 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KOVATCH, PATRICIA · 2019 to 2019
$2.0M
NIH HHS S10 OD026880NIH HHS S10 OD030463
6 · The paper itself

Abstract

INTRODUCTION/

objectiveThe KidneyIntelX is a multiplex, bioprognostic, immunoassay consisting of 3 plasma biomarkers and clinical variables that uses machine learning to predict a patient's risk for a progressive decline in kidney function over 5 years. We report the 1-year pre- and post-test clinical impact on care management, eGFR slope, and A1C along with engagement of population health clinical pharmacists and patient coordinators to promote a program of sustainable kidney, metabolic, and cardiac health.

methodsThe KidneyIntelX in vitro prognostic test was previously validated for patients with type 2 diabetes and diabetic kidney disease (DKD) to predict kidney function decline within 5 years was introduced into the RWE study (NCT04802395) across the Health System as part of a population health chronic disease management program from [November 2020 to April 2023]. Pre- and post-test patients with a minimum of 12 months of follow-up post KidneyIntelX were assessed across all aspects of the program.

resultsA total of 5348 patients with DKD had a KidneyIntelX assay. The median age was 68 years old, 52% were female, 27% self-identified as Black, and 89% had hypertension. The median baseline eGFR was 62 ml/min/1.73 m

conclusionsDeployment and risk stratification by KidneyIntelX was associated with an escalation in action taken to optimize cardio-kidney-metabolic health including medications and specialist referrals. Glycemic control and kidney function trajectories improved post-KidneyIntelX testing, with the greatest improvements observed in those scored as high-risk.

Indexed as

Diabetes Mellitus, Type 2Diabetic NephropathiesAgedAlbuminuriaFemaleGlycated HemoglobinHumansMalePrecision MedicineGlycated Hemoglobindiabetic kidney diseaseearly-stageKidneyIntelXprecision medicineReal World Evidencetreatment management

Identifiers

PMID38185870
PMCPMC10773280
OpenAlexW4390665963

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.