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ORIGINAL RESEARCH article

Front. Aging Neurosci.

Sec. Alzheimer's Disease and Related Dementias

Volume 17 - 2025 | doi: 10.3389/fnagi.2025.1492804

This article is part of the Research Topic A comprehensive look at biomarkers in neurodegenerative diseases: from early diagnosis to treatment response assessment View all 23 articles

Early Identification of Mild Cognitive Impairment: An Innovative Model Using Ocular Biomarkers

Provisionally accepted
  • 1 Nankai University, Tianjin, China
  • 2 Department of General Surgery, The 926th Hospital, Joint Logistics Support Force of PLA, Kaiyuan, China
  • 3 People's Liberation Army General Hospital, Beijing, China
  • 4 Department of Ophthalmology, People's Liberation Army General Hospital, Haidian, Beijing, China
  • 5 Department of Ophthalmology, The General Hospital of the People's Liberation Army, Beijing, China

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

    Background: Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive, irreversible brain damage. Current diagnostic procedures for AD are both costly and highly invasive for patients. Age-related cataract (ARC), a common ocular condition in elderly populations, correlates with a 1.43-fold increased risk of developing AD. This study sought to establish a novel model for early detection of mild cognitive impairment (MCI) in patients with ARC.The study prospectively collected 170 monocular data as training dataset and 65 monocular data from another independent medical center as test dataset.Demographic data and comprehensive ophthalmic examination results were collected.The least absolute shrinkage and selection operator (LASSO) method and multivariate logistic regression analysis were performed using R software for dimensionality reduction and variable selection. A nomogram was constructed, and its discriminative ability was evaluated using receiver operating characteristic (ROC) curve, area under the ROC curve (AUC) with 95% confidence interval (CI), as well as sensitivity and specificity. Internal validation was performed using 1000-resample bootstrap analysis, while model calibration was assessed through calibration curves and Brier scores.Decision curve analysis (DCA) was performed to evaluate clinical utility. A baseline model incorporating demographic variables was developed for comparison with the nomogram. Additionally, an external dataset from an independent medical center was employed as a test set to further validate the nomogram's predictive performance. An online calculator was created using the "DynNom" and "rsconnect" functions.Results: Through LASSO regression and multivariate logistic regression analyses, six variables were identified and incorporated into the nomogram: age (OR: 1.097; 95%CI:1.041-1.161; p < 0.001), years of education (OR: 0.333; 95%CI: 0.

    Keywords: Mild Cognitive Impairment, Ocular biomarkers, Alzheimer's disease, Prediction model, web-based calculator

    Received: 08 Sep 2024; Accepted: 26 Mar 2025.

    Copyright: © 2025 Lingjing, Wang, Liu, Ye and Li. 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:
    Zi Ye, Department of Ophthalmology, People's Liberation Army General Hospital, Haidian, Beijing, China
    Zhaohui Li, Department of Ophthalmology, The General Hospital of the People's Liberation Army, Beijing, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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