Evidence map›Paper›PMID 41384016›Full record

ArticleFrontiers in endocrinology2025

Prediction model for cognitive impairment in maintenance hemodialysis patients: the role of diabetes.

Jia Xu, Hao Li, Hualin Qi, Xinhui Zhao

Abstract read
In one paragraph

Article 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. 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.

Jia Xu *Department of Nephrology, The People's Hospital of Pudong New District in Shanghai, Shanghai, China.
Hao Li *Department of Internal Medicine, The People's Hospital of Pudong New District in Shanghai, Shanghai, China.
Hualin QiDepartment of Nephrology, The People's Hospital of Pudong New District in Shanghai, Shanghai, China.
Xinhui ZhaoDepartment of Nephrology, The People's Hospital of Pudong New District in Shanghai, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The aim of this study was to identify risk factors for cognitive impairment (CI) in maintenance hemodialysis (MHD) patients and to develop a predictive model. Methods: A total of 151 MHD patients from our hospital were recruited between July 2020 and April 2021. Sociodemographic, clinical, and laboratory data were collected. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), whereas physical performance was evaluated using handgrip strength, the Timed Up and Go Test (TUGT), and 4-m gait speed. Univariate and multivariate logistic regression analyses identified risk factors, which were used to develop original and simplified predictive models. Results: CI was present in 43 patients (28.5%). The simplified model demonstrated discriminatory ability comparable to that of the original model (AUC: 0.737; 95% CI: 0.648-0.818) and was easier to use. A robust nomogram was developed on the basis of the simplified model. Decision curve analysis (DCA) confirmed the clinical utility of both models. Diabetes was identified as an independent risk factor, whereas dialysis duration was not associated with CI. Conclusions: This study provides a simple predictive model for CI in MHD patients, which could aid in clinical decision-making.

Indexed as

Cognitive DysfunctionDiabetes MellitusDiabetic NephropathiesPredictive Learning ModelsRenal DialysisAgedArea Under CurveClinical Decision-MakingCross-Sectional StudiesDecision Support TechniquesExercise TestFemaleHand StrengthHumansLogistic ModelsMalecognitive impairmentdiabetesgait speedhandgrip strengthhemodialysisTUGT

Identifiers

PMID41384016
PMCPMC12689383

What OpenQuestion holds

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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.