Evidence mapPaperPMID 40490374Full record

ArticleBMJ open diabetes research & care2025

Identification of pre-diabetes subphenotypes for type 2 diabetes, related vascular complications and mortality.

Chaiwat Washirasaksiri, Nutsakol Borrisut, Varisara Lapinee, Tullaya Sitasuwan, Rungsima Tinmanee, Chayanis Kositamongkol, Pinyapat Ariyakunaphan, Watip Tangjittipokin, Nattachet Plengvidhya, Weerachai Srivanichakorn

Abstract read
In one paragraph

Article in BMJ open diabetes research & care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Biochemical and Molecular Markers Among Prediabetic and Type 2 Diabetes Mellitus Patients.International journal of endocrinology and metabolism · 2026
    Article
  2. Article
  3. Article
  4. Review
  5. Precision prevention in type 2 diabetes.BMJ open diabetes research & care · 2025
    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

10 authors.

Chaiwat WashirasaksiriDepartment of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Nutsakol BorrisutDepartment of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Varisara LapineeASEAN Institute for Health Development, Mahidol University, Salaya, Thailand.
Tullaya SitasuwanDepartment of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Rungsima TinmaneeDepartment of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Chayanis KositamongkolDepartment of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Pinyapat AriyakunaphanDepartment of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Watip TangjittipokinDepartment of Immunology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.ORCID http://orcid.org/0000-0002-7103-8466
Nattachet PlengvidhyaDivision of Endocrinology and Metabolism, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Weerachai SrivanichakornDepartment of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand weerachai.srv@mahidol.ac.th.ORCID http://orcid.org/0000-0001-9581-7117

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPre-diabetes comprises diverse subphenotypes linked to varying complications, type 2 diabetes, and mortality outcomes. This study aimed to explore these outcomes across different pre-diabetes subphenotypes. RESEARCH DESIGN AND

methodsThe dataset included adults without type 2 diabetes with baseline HbA1c and fasting plasma glucose (FPG) measurements from Siriraj Hospital, Bangkok, Thailand. The participants were classified into six subphenotypes via the

resultsAmong the 4915 participants (mean age 60.1±10.1 years; 54.6% female), six clusters emerged: cluster 1, low risk (n=650; 13.2%); cluster 2, mild dysglycemia elderly (n=791; 16.1%); cluster 3, severe dysglycemia obese (n=1127; 22.9%); cluster 4, mild dysglycemia obese (n=963; 19.7%); cluster 5, severe dysmetabolic obese (n=337; 6.9%); and cluster 6, severe dysglycemia elderly (n=1042; 21.2%). Clusters were classified into diabetes risk subgroups: low risk (clusters 1 and 4) and high risk (clusters 3 and 5). Cluster 6 exhibited the highest risk, with significantly increased incidences of macrovascular complications (adjusted HR 2.22, 1.51-3.27) and type 2 diabetes (1.73, 1.42-2.12). In contrast, cluster 4 demonstrated the lowest risk, with significantly decreased incidences of new chronic kidney disease (0.65, 0.44-0.96), microvascular complications (0.62, 0.43-0.89) and mortality (0.25, 0.10-0.63).

conclusionsOur pre-diabetes phenotyping approach effectively provides valuable insights into the risk of type 2 diabetes, vascular complications and mortality in individuals with pre-diabetes. Those with high-risk phenotypes should be prioritized for type 2 diabetes and cardiovascular interventions to mitigate risks.

Indexed as

BiomarkersDiabetes Mellitus, Type 2Diabetic AngiopathiesPrediabetic StateAgedBlood GlucoseBody Mass IndexFemaleFollow-Up StudiesGlycated HemoglobinHumansIncidenceMaleMiddle AgedPhenotypePrognosisBiomarkersBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, humanDiabetes ComplicationsMortalityPrediabetic StatePreventive Medicine

Identifiers

PMID40490374
PMCPMC12161346

What Socratic holds

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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 Socratic graph.