Visual Deficits in Type 2 Diabetes Mellitus Without Retinopathy: From Retinal Structure to Higher-Level Visual Functions.

IF 2.6 3区医学 Q2 OPHTHALMOLOGY

Translational Vision Science & Technology Pub Date : 2025-03-03 DOI:10.1167/tvst.14.3.10

Sha Luo, Lin Xia, Yue Wang, Yong Tang, Jiong Dong, Rong Liu, Lixia Feng

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引用次数: 0

Abstract

Purpose: The purpose of this study was to evaluate deficits at varying levels of visual system in diabetes without clinical retinopathy (NoDR) and to explore the optimal method for detecting early diabetic visual disorders among functional and retinal structural assessments included.

Methods: This cross-sectional study examined eyes by the Early Treatment of Diabetic Retinopathy Study (ETDRS) charts, visual psychophysical tests, optical coherence tomography (OCT), and OCT angiography (OCTA). Visual psychophysical metrics included grating acuity (GA), and contrast sensitivity to first-order motion stimuli (1stM), second-order contrast-modulated stationary stimuli (2ndS), and second-order motion stimuli (2ndM). Generalized linear mixed effect (GLME) models were applied to assess group effects and linear relationships between measurements. The receiver operating characteristic (ROC) analysis was utilized to identify the optimal classifier for detecting NoDR.

Results: Fifty-three eyes of 33 patients with NoDR and 40 eyes of 27 healthy controls were included. The NoDR group showed significant reductions in various visual functions, including ETDRS acuity, GA, 2ndS, and 2ndM (P values < 0.001), and microvascular changes in foveal vascular density (FD-300), the acircularity index (AI) of the foveal avascular zone, and the parafoveal superficial capillary plexus density (P values < 0.05). GLME models revealed these retinal variations were not significantly correlated with early diabetic visual function abnormalities. ROC analysis demonstrated the integration of GA and FD-300 (area under the curve [AUC] = 0.911) is the most effective classifier for detecting early diabetic visual dysfunctions.

Conclusions: In addition to retinal defects, both low- and higher-order visual function disorders along the visual pathway exist in patients with NoDR. Combining functional and structural measurements may provide more accurate assessments for detecting early diabetic visual disorders.

Translational relevance: Sophisticated visual psychophysical measurements, including grating acuity and second-order function, could be applied for detecting early diabetic visual disorders.

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来源期刊

Translational Vision Science & Technology Engineering-Biomedical Engineering

CiteScore

5.70

自引率

3.30%

发文量

346

审稿时长

25 weeks

期刊介绍： Translational Vision Science & Technology (TVST), an official journal of the Association for Research in Vision and Ophthalmology (ARVO), an international organization whose purpose is to advance research worldwide into understanding the visual system and preventing, treating and curing its disorders, is an online, open access, peer-reviewed journal emphasizing multidisciplinary research that bridges the gap between basic research and clinical care. A highly qualified and diverse group of Associate Editors and Editorial Board Members is led by Editor-in-Chief Marco Zarbin, MD, PhD, FARVO. The journal covers a broad spectrum of work, including but not limited to: Applications of stem cell technology for regenerative medicine, Development of new animal models of human diseases, Tissue bioengineering, Chemical engineering to improve virus-based gene delivery, Nanotechnology for drug delivery, Design and synthesis of artificial extracellular matrices, Development of a true microsurgical operating environment, Refining data analysis algorithms to improve in vivo imaging technology, Results of Phase 1 clinical trials, Reverse translational ("bedside to bench") research. TVST seeks manuscripts from scientists and clinicians with diverse backgrounds ranging from basic chemistry to ophthalmic surgery that will advance or change the way we understand and/or treat vision-threatening diseases. TVST encourages the use of color, multimedia, hyperlinks, program code and other digital enhancements.