Evidence map›Paper›PMID 42137346›Full record

ReviewFrontiers in endocrinology2026

Sentinel factors for mild cognitive impairment in type 2 diabetes mellitus and their interaction mechanisms: a narrative review with network analysis perspective.

Qiongqiong Sun, LingYan Zhang, Jianwen Zhao, Shanshan Wang

Abstract readReview
In one paragraph

Review in Frontiers in endocrinology, 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

4 authors.

Qiongqiong SunYangzhou Hospital of Traditional Chinese Medicine (TCM), Yangzhou, China.
LingYan ZhangYangzhou Hospital of Traditional Chinese Medicine (TCM), Yangzhou, China.
Jianwen ZhaoYangzhou Hospital of Traditional Chinese Medicine (TCM), Yangzhou, China.
Shanshan WangYangzhou Hospital of Traditional Chinese Medicine (TCM), Yangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type 2 diabetes mellitus (T2DM) is a global chronic metabolic epidemic, and affected patients face a 1.5-fold higher risk of mild cognitive impairment (MCI) - a reversible pre-dementia stage - than non-diabetic populations. Early identification of modifiable sentinel factors is the cornerstone of delaying cognitive decline in T2DM patients, yet traditional statistical methods cannot fully elucidate the synergistic interactions between multi-dimensional risk factors. Network analysis, a graph theory-based statistical approach, enables visualization of complex variable associations and identification of core regulatory nodes in disease networks, providing a novel perspective for MCI research. Based on our team's clinical data and comprehensive evidence synthesis, this review systematically summarizes the pathophysiological mechanisms linking T2DM and MCI, establishes an operational definition and classification framework of MCI sentinel factors in T2DM patients, elaborates the application value of network analysis in this field, and proposes concrete research paradigms for future investigation. This review aims to provide a theoretical and practical framework for the early screening, targeted intervention, and precise prevention of MCI in T2DM patients, aligning with the scope of clinical diabetes and geriatric endocrinology research.

Indexed as

Cognitive DysfunctionDiabetes Mellitus, Type 2HumansRisk Factorscognitive protectionmild cognitive impairmentnetwork analysisrisk factorssentinel factorstype 2 diabetes mellitus

Identifiers

PMID42137346
PMCPMC13167409

What Socratic holds

Textmetadata
LicenceCC BY
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.