Evidence mapPaperPMID 41002359Full record

ArticleBiosensors2025

Possible Use of the SUDOSCAN Nephropathy Risk Score in Chronic Kidney Disease Diagnosis: Application in Patients with Type 2 Diabetes.

Claudiu Cobuz, Mădălina Ungureanu-Iuga, Dana-Teodora Anton-Paduraru, Maricela Cobuz

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Article in Biosensors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Claudiu CobuzFaculty of Medicine and Biological Sciences, Stefan cel Mare University of Suceava, 13th Universitatii Street, 720229 Suceava, Romania.ORCID 0009-0005-2795-8491
Mădălina Ungureanu-IugaIntegrated Center for Research, Development and Innovation in Advanced Materials, Nanotechnologies, and Distributed Systems for Fabrication and Control (MANSiD), Stefan cel Mare University of Suceava, 13th Universitatii Street, 720229 Suceava, Romania.ORCID 0000-0003-1314-5957
Dana-Teodora Anton-PaduraruDepartment of Maternal and Child Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 16th Universitatii Street, 700115 Iaşi, Romania.ORCID 0000-0001-8657-378X
Maricela CobuzFaculty of Medicine and Biological Sciences, Stefan cel Mare University of Suceava, 13th Universitatii Street, 720229 Suceava, Romania.ORCID 0009-0003-8343-5025

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of quick and non-invasive techniques for detecting chronic kidney disease (CKD) in patients with type 2 diabetes mellitus is desirable and has recently garnered attention. One of these techniques is the evaluation of nephropathy risk based on electrochemical skin conductance (ESC) measured with a SUDOSCAN device. This paper aims to evaluate the possibility of using SUDOSCANs in chronic kidney disease prediction in diabetic patients and to investigate the relationships between clinical characteristics and SUDOSCAN parameters. The number of patients with type 2 diabetes included in this study was 254. Clinical metabolic characteristics like glycated hemoglobin, total and LDL cholesterol, triglyceride, blood pressure, and creatinine were determined along with body mass index, diabetes duration, and age. The estimated glomerular filtration rate (EGFR) was calculated and patients were grouped into three CKD stages based on EGFR values. Electrochemical skin conductance in hands and feet was determined with a SUDOSCAN device. The results showed that patients with symptomatic CKD (S2 and 3) presented lower ESC values, along with lower EFGRs and higher creatinine levels. A significant positive but weak correlation (

Indexed as

Diabetes Mellitus, Type 2Diabetic NephropathiesElectrochemical TechniquesRenal Insufficiency, ChronicAgedCreatinineFemaleGalvanic Skin ResponseGlomerular Filtration RateHumansMaleMiddle AgedRisk FactorsCreatininediabetes nephropathyEGFRkidney diseaseSUDOSCAN screeningtype 2 diabetes mellitus

Identifiers

PMID41002359
PMCPMC12467832

What Socratic holds

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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 Socratic graph.