Evidence mapPaperPMID 41813261Full record

ReviewDiabetes & metabolism journal2026

Redefining β-Cell Function in Type 2 Diabetes Mellitus: From Comprehensive Assessment to Precision Medicine.

YongKyung Kim, Joon Ha, Jun Sung Moon

Abstract readReview
In one paragraph

Review in Diabetes & metabolism journal, 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

3 authors.

YongKyung KimInstitute of Medical Science, Yeungnam University College of Medicine, Daegu, Korea.
Joon HaDepartment of Mathematics, Howard University, Washington, DC, USA.
Jun Sung MoonInstitute of Medical Science, Yeungnam University College of Medicine, Daegu, Korea.

Funding

Ministry of Science and ICT RS-2023-00219725National Research Foundation of KoreaNational Science Foundation DMS 2401921NIDDK NIH HHS
6 · The paper itself

Abstract

The global surge in type 2 diabetes mellitus (T2DM) requires a thorough understanding of pancreatic β-cell dysfunction, which remains a central determinant of the disease. However, the evaluation of β-cell insulin secretory capacity is often challenging in clinical practice due to its inherent complexity. This review presents a comprehensive technical overview of diverse assessment methodologies, ranging from conventional fasting-based indices and glucose tolerance tests to advanced mathematical modeling and artificial intelligence-driven approaches. A detailed examination of the methodological strengths and limitations of these various tools is provided to guide their appropriate clinical application. Furthermore, we explore the clinical implications of these assessments in enhancing diagnostic accuracy and tailoring therapeutic strategies. Particular emphasis is placed on the pivotal role of β-cell function evaluation in predicting and achieving diabetes remission-an emerging clinical priority. By integrating the technical landscape of β-cell assessment with practical applications, this review provide a structured framework for optimizing T2DM management and improving long-term patient outcomes.

Indexed as

Diabetes Mellitus, Type 2Insulin-Secreting CellsPrecision MedicineGlucose Tolerance TestHumansInsulinInsulin SecretionInsulinDiabetes mellitus, type 2Diagnostic techniques and proceduresGlucose tolerance testInsulin-secreting cellsPrecision medicine

Identifiers

PMID41813261
PMCPMC12996962

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.