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ORIGINAL RESEARCH article

Front. Endocrinol.

Sec. Clinical Diabetes

This article is part of the Research TopicAssociation of Diabetes Mellitus with Cognitive Impairment and Neurological Disorders Vol. 2View all 12 articles

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

Provisionally accepted
  • 1Department of Nephrology, Shanghai Pudong New Area People's Hospital, Pudong, Shanghai Municipality, China
  • 2Shanghai Pudong New Area People's Hospital, Pudong, China

The final, formatted version of the article will be published soon.

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.

Keywords: cognitive impairment, hemodialysis, diabetes, handgrip strength, TUGT, gait speed

Received: 16 Mar 2025; Accepted: 11 Nov 2025.

Copyright: © 2025 Xu, Li, Qi and Zhao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Xinhui Zhao, zxh80114@163.com

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