Evidence map›Paper›PMID 41316697›Full record

ArticleJournal of diabetes investigation2026

Electrophysiological diagnosis using the coefficient of variation of R-R intervals and a point-of-care nerve conduction device is highly correlated to the diagnosis of diabetic polyneuropathy using conventional electromyographs.

Tatsuhito Himeno, Hideki Kamiya, Yuka Shibata, Masato Kase, Hiromi Nakai-Shimoda, Dai Yamagami, Masahiro Saito, Teruo Jojima, Aiko Arimura, Kenta Murotani and 5 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of diabetes investigation, 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

15 authors.

Tatsuhito HimenoDivision of Diabetes, Department of Internal Medicine, Aichi Medical University School of Medicine, Nagakute, Japan.
Hideki KamiyaDivision of Diabetes, Department of Internal Medicine, Aichi Medical University School of Medicine, Nagakute, Japan.
Yuka ShibataDivision of Diabetes, Department of Internal Medicine, Aichi Medical University School of Medicine, Nagakute, Japan.
Masato KaseDepartment of Endocrinology and Metabolism, Dokkyo Medical University, Mibu, Japan.
Hiromi Nakai-ShimodaDivision of Diabetes, Department of Internal Medicine, Aichi Medical University School of Medicine, Nagakute, Japan.
Dai YamagamiDepartment of Diabetology, Endocrinology and Metabolism, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan.ORCID https://orcid.org/0009-0000-2152-782X
Masahiro SaitoDepartment of Endocrinology and Metabolism, Dokkyo Medical University, Mibu, Japan.
Teruo JojimaDepartment of Endocrinology and Metabolism, Dokkyo Medical University, Mibu, Japan.
Aiko ArimuraDepartment of Diabetology, Endocrinology and Metabolism, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan.
Kenta MurotaniBiostatistics Center, Kurume University, Kurume, Japan.ORCID https://orcid.org/0000-0003-0623-9365
Chieko SuzukiDepartment of Neurology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan.
Hiroki MizukamiDepartment of Pathology and Molecular Medicine, Biomedical Research Center, Hirosaki University Graduate School of Medicine, Hirosaki, Japan.ORCID https://orcid.org/0000-0003-2920-582X
Takahisa DeguchiDepartment of Diabetology, Endocrinology and Metabolism, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan.ORCID https://orcid.org/0000-0002-4769-2193
Yoshimasa AsoDepartment of Endocrinology and Metabolism, Dokkyo Medical University, Mibu, Japan.ORCID https://orcid.org/0000-0003-0610-1999
Jiro NakamuraDivision of Diabetes, Department of Internal Medicine, Aichi Medical University School of Medicine, Nagakute, Japan.ORCID https://orcid.org/0000-0003-3385-6916

Funding

the Ministry of Health, Labour and Welfare JPMH20FA1701
6 · The paper itself

Abstract

AIMS/

introductionWhile treatment for diabetic polyneuropathy (DPN) is still developing, progress has stagnated. The alignment between pathological neurodegeneration in DPN and patients' subjective symptoms is often low, yet these symptoms are frequently used for diagnosis. This reliance has hindered the development of effective drugs to prevent neurodegeneration. This study aims to establish an objective electrophysiological diagnostic method that could support future treatment development and validate its accuracy. MATERIALS AND

methodsThis retrospective multicenter cohort study involved hospitalized diabetic patients. A total of 314 patients underwent nerve conduction studies using standard electromyography and a simplified nerve conduction testing device (NC-stat/DPNCheck™), along with electrocardiogram-based coefficient of variation of R-R intervals (CV

resultsSignificant factors included resting CV

conclusionsThe established diagnostic criteria of DPN demonstrate high performance and are expected to be applicable in clinical settings.

Indexed as

Diabetic NeuropathiesElectromyographyNeural ConductionPoint-of-Care SystemsAdultAgedElectrocardiographyFemaleHumansMaleMiddle AgedRetrospective StudiesDiabetic polyneuropathyHeart rate variabilityNerve conduction study

Identifiers

PMID41316697
PMCPMC12863008

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.