Evidence map›Paper›PMID 41080000›Full record

ArticleFrontiers in aging neuroscience2025

Risk factor analysis of cognitive frailty in older adults with type 2 diabetes mellitus: a cross-sectional study.

Qingjuan Ren, Shu Niu, Lei Zhi, Hongfang Liu

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

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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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Qingjuan Ren *Department of Geriatrics, Shijiazhuang People's Hospital, Shijiazhuang, Hebei, China.
Shu Niu *Department of Endocrinology, Shijiazhuang People's Hospital, Shijiazhuang, Hebei, China.
Lei ZhiDepartment of Geriatrics, Shijiazhuang People's Hospital, Shijiazhuang, Hebei, China.
Hongfang LiuDepartment of Geriatrics, Shijiazhuang People's Hospital, Shijiazhuang, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cognitive Frailty (CF), characterized by the co-occurrence of physical frailty and cognitive impairment without dementia, is a significant concern in older adults with Type 2 Diabetes Mellitus (T2DM). This study investigates the prevalence and risk factors of CF in this population, addressing the urgent need for early detection and intervention strategies. Methods: A cross-sectional study was conducted among 713 T2DM patients aged ≥65 years. Participants were assessed using the Clinical Dementia Rating (CDR) for cognitive function and Fried Frailty Phenotype (FP) criteria for physical frailty. CF was defined as CDR = 0.5 and FP score ≥ 3. Multivariable logistic regression identified independent risk factors, adjusting for demographic and clinical variables. Results: The prevalence of CF was 24.3%. Cerebrovascular disease (OR: 2.39, 95% CI: 1.44-3.97) and peripheral arterial disease (OR: 1.74, 95% CI: 1.03-2.95) were significant risk factors, while higher education (OR 0.85, 95% CI 0.76-0.94) and later diabetes onset (OR: 0.93, 95% CI: 0.88-0.98) were protective. Early-onset diabetes significantly increased CF risk regardless of education level. Conclusion: This study highlights a markedly increased risk of CF in older adults with T2DM, especially in individuals with CVD, PAD, low education levels, or early-onset diabetes. Notably, early diabetes onset may override the protective effects of cognitive reserve, emphasizing the critical need for early metabolic and vascular risk management in this high-risk population. These findings support integrated screening for cognitive and physical frailty in diabetes care to enable timely interventions.

Indexed as

cognitive frailtycross-sectional studyfrailtyolder adultstype 2 diabetes

Identifiers

PMID41080000
PMCPMC12507847

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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.