Evidence map›Paper›PMID 40444231›Full record

Observational studyFrontiers in endocrinology2025

Predicting incident type 2 diabetes in a Japanese cohort: an 8-year analysis of the NAGALA database.

Yangchun Wang, Fei Liu, Ruixiang Tong, Zhonghua He, Qin Fang, Jie Feng, Hongliang An, Junjun Liu

Abstract readObservational Study
In one paragraph

Observational study in Frontiers in endocrinology, 2025. 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. Review
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

8 authors.

Yangchun Wang *Department of Endocrinology, Nanjing Meishan Hospital, Nanjing, China.
Fei Liu *Department of General Surgery, Nanjing Meishan Hospital, Nanjing, China.
Ruixiang Tong *Department of Endocrinology, Nanjing Meishan Hospital, Nanjing, China.
Zhonghua HeDepartment of Endocrinology, Nanjing Meishan Hospital, Nanjing, China.
Qin FangDepartment of Endocrinology, Nanjing Meishan Hospital, Nanjing, China.
Jie FengDepartment of Pharmacy, Nanjing Meishan Hospital, Nanjing, China.
Hongliang AnDepartment of Pharmacy, Nanjing Meishan Hospital, Nanjing, China.
Junjun LiuDepartment of Psychiatry, Nanjing Meishan Hospital, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Using data from the NAGALA database, this retrospective cohort study set out to identify the predictive markers for incident Type 2 Diabetes Mellitus (T2DM), with a particular focus on the non-diabetic Japanese population. Methods: We examined the data from a cohort of 15,464 individuals (with a male representation of 54.5% and an average age of (43.71 ± 8.90 years) sourced from the NAGALA (NAfld in the Gifu Area Longitudinal Analysis) research which was a longitudinal study at Medical Health Checkup Center of Murakami Memorial Hospital. The analysis focused on the incidence of T2DM from 2004 to 2012. Baseline demographic, anthropometric, biochemical, and lifestyle data were collected. All participants were not type 2 diabetic at baseline. The diagnosis of T2DM was confirmed by HbA1c >= 48mmol/mol, fasting plasma glucose >= 126mg/dL, or diabetes reported by oneself. Multivariate analysis was performed after univariate Cox regression analysis was used to find early determinants of T2DM incidence. The ability of individual components and a composite risk score to discriminate was assessed using Receiver Operating Characteristic (ROC) curves. Results: Over an average follow-up duration of 2207.82 ± 1379.73 days, 262 patients (1.7%) had the onset of T2DM. Following the removal of confounding variables we found that age ( Conclusion: Current research has underscored the significance of a multifaceted approach to the prevention of T2DM, which includes early intervention targeting modifiable risk factors such as obesity, unhealthy alcohol use, and smoking, in conjunction with the monitoring of key metabolic markers like HbA1c and liver enzymes.

Indexed as

Diabetes Mellitus, Type 2AdultBiomarkersBlood GlucoseCohort StudiesDatabases, FactualFemaleFollow-Up StudiesGlycated HemoglobinHumansIncidenceJapanLongitudinal StudiesMaleMiddle AgedPrognosisBiomarkersBlood GlucoseGlycated Hemoglobincohort studyincidenceJapanese populationpredictive markerstype 2 diabetes mellitus

Identifiers

PMID40444231
PMCPMC12119281

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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.