Evidence map›Paper›PMID 36769457›Full record

ArticleJournal of clinical medicine2023

Two Distinct Groups Are Shown to Be at Risk of Diabetes by Means of a Cluster Analysis of Four Variables.

Ryoma Ito, Satoru Mizushiri, Yuki Nishiya, Shoma Ono, Ayumi Tamura, Kiho Hamaura, Akihide Terada, Jutaro Tanabe, Miyuki Yanagimachi, Kyi Mar Wai and 4 more

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2023. 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.

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2 · The registry

The trial behind it

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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

14 authors.

Ryoma ItoDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.
Satoru MizushiriDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.
Yuki NishiyaDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.
Shoma OnoDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.
Ayumi TamuraDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.
Kiho HamauraDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.
Akihide TeradaDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.
Jutaro TanabeDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.
Miyuki YanagimachiDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.
Kyi Mar WaiDepartment of Social Medicine, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.ORCID 0000-0001-8755-277X
Yutaro KudoDepartment of Social Medicine, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.
Kazushige IharaDepartment of Social Medicine, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.
Yoshiko TakahashiCenter of Innovation Research Initiatives Organization, Hirosaki 036-8562, Japan.
Makoto DaimonDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.ORCID 0000-0002-3775-1719

Funding

the Japan Science and Technology Agency JPMJCE1302, JPMJCA2201
6 · The paper itself

Abstract

Recent attempts to classify adult-onset diabetes using only six diabetes-related variables (GAD antibody, age at diagnosis, BMI, HbA1c, and homeostatic model assessment 2 estimates of b-cell function and insulin resistance (HOMA2-B and HOMA2-IR)) showed that diabetes can be classified into five clusters, of which four correspond to type 2 diabetes (T2DM). Here, we classified nondiabetic individuals to identify risk clusters for incident T2DM to facilitate the refinement of prevention strategies. Of the 1167 participants in the population-based Iwaki Health Promotion Project in 2014 (baseline), 868 nondiabetic individuals who attended at least once during 2015-2019 were included in a prospective study. A hierarchical cluster analysis was performed using four variables (BMI, HbA1c, and HOMA2 indices). Of the four clusters identified, cluster 1 (n = 103), labeled as "obese insulin resistant with sufficient compensatory insulin secretion", and cluster 2 (n = 136), labeled as "low insulin secretion", were found to be at risk of diabetes during the 5-year follow-up period: the multiple factor-adjusted HRs for clusters 1 and 2 were 14.7 and 53.1, respectively. Further, individuals in clusters 1and 2 could be accurately identified: the area under the ROC curves for clusters 1and 2 were 0.997 and 0.983, respectively. The risk of diabetes could be better assessed on the basis of the cluster that an individual belongs to.

Indexed as

cluster analysisincident type 2 diabetesnondiabetic population

Identifiers

PMID36769457
PMCPMC9918294

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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.