Evidence map›Paper›PMID 37057310›Full record

ArticleJournal of diabetes2023

The use of nomogram for detecting mild cognitive impairment in patients with type 2 diabetes mellitus.

Rehanguli Maimaitituerxun, Wenhang Chen, Jingsha Xiang, Yu Xie, Atipatsa C Kaminga, Xin Yin Wu, Letao Chen, Jianzhou Yang, Aizhong Liu, Wenjie Dai

Open access · goldAbstract read
In one paragraph

Article in Journal of diabetes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.8field-weighted citation impact, top 6% of its field
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

13 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
  2. Review
  3. Development and multi-center validation of a high-performance predictive model for early detection of cognitive impairment in older adults: data-based on communities in Northern China.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
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  4. Article
  5. Observational
  6. Prediction model for mild cognitive impairment in patients with type 2 diabetes using the autonomic function test.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024
    Article
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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

10 authors at 4 institutions in 2 countries.

Rehanguli MaimaitituerxunDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China.ORCID https://orcid.org/0000-0002-3388-3861
Wenhang ChenDepartment of Nephrology, Xiangya Hospital, Central South University, Changsha, China.
Jingsha XiangHuman Resources Department, Central Hospital Affiliated to Shandong First Medical University, Jinan, China.
Yu XieDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China.
Atipatsa C KamingaDepartment of Mathematics and Statistics, Mzuzu University, Mzuzu, Malawi.
Xin Yin WuDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China.
Letao ChenInfection Control Center, Xiangya Hospital, Central South University, Changsha, China.
Jianzhou YangDepartment of Preventive Medicine, Changzhi Medical College, Changzhi, China.
Aizhong LiuDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China.
Wenjie DaiDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China.
Central South University · CNChangzhi Medical College · CNJinan Central Hospital · CNMzuzu University · MW

Funding

National Key R&D Program of China 2020YFC2008600National Natural Science Foundation of China 82103939National Natural Science Foundation of Hunan Province 2021JJ40805start-up research fund of Central South University 202044003
6 · The paper itself

Abstract

backgroundType 2 diabetes mellitus (T2DM) is highly prevalent worldwide and may lead to a higher rate of cognitive dysfunction. This study aimed to develop and validate a nomogram-based model to detect mild cognitive impairment (MCI) in T2DM patients.

methodsInpatients with T2DM in the endocrinology department of Xiangya Hospital were consecutively enrolled between March and December 2021. Well-qualified investigators conducted face-to-face interviews with participants to retrospectively collect sociodemographic characteristics, lifestyle factors, T2DM-related information, and history of depression and anxiety. Cognitive function was assessed using the Mini-Mental State Examination scale. A nomogram was developed to detect MCI based on the results of the multivariable logistic regression analysis. Calibration, discrimination, and clinical utility of the nomogram were subsequently evaluated by calibration plot, receiver operating characteristic curve, and decision curve analysis, respectively.

resultsA total of 496 patients were included in this study. The prevalence of MCI in T2DM patients was 34.1% (95% confidence interval [CI]: 29.9%-38.3%). Age, marital status, household income, diabetes duration, diabetic retinopathy, anxiety, and depression were independently associated with MCI. Nomogram based on these factors had an area under the curve of 0.849 (95% CI: 0.815-0.883), and the threshold probability ranged from 35.0% to 85.0%.

conclusionsAlmost one in three T2DM patients suffered from MCI. The nomogram, based on age, marital status, household income, duration of diabetes, diabetic retinopathy, anxiety, and depression, achieved an optimal diagnosis of MCI. Therefore, it could provide a clinical basis for detecting MCI in T2DM patients.

Indexed as

Cognitive DysfunctionDiabetes Mellitus, Type 2Diabetic RetinopathyHumansNomogramsRetrospective StudiesRisk Factors2型糖尿病diagnosismild cognitive impairmentmodelnomogramtype 2 diabetes mellitus列线图模型诊断轻度认知障碍

Identifiers

PMID37057310
PMCPMC10172024
OpenAlexW4365483391

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.