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Introduction: Diabetic retinopathy grading plays a vital role in the diagnosis and treatment of patients. In practice, this task mainly relies on manual inspection using human visual system. However, the human visual system-based screening process is labor-intensive, time-consuming, and error-prone.

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Purpose: To report a case of a diabetic patient undergoing rapid glycemic improvement characterized by the development and resolution of cotton wool spot (CWS), with detailed structural and vascular assessment using wide-field multimodal imaging, including wide-field color fundus photography and wide-field optical coherence tomography angiography (OCTA).

Observations: A 47-year-old man with poorly controlled Type 2 diabetes mellitus developed CWS in his right eye 3 months after initiating insulin therapy, which coincided with a significant reduction in HbA1c levels. Wide-field color fundus photography and wide-field OCTA were performed before, during, and after CWS appeared.

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Association of socioeconomic status with diabetic microvascular complications: a UK Biobank prospective cohort study.

Diabetol Metab Syndr

January 2025

Department of Ophthalmology, Shengli Clinical College of Fujian Medical University; Fuzhou University Affiliated Provincial Hospital, School of Medicine, Fuzhou University, Fuzhou, Fujian, China.

Background: Prior studies on the link between socioeconomic status (SES) and diabetic microvascular complications have been inconclusive. This study aimed to explore whether SES is associated with the risk of diabetic retinopathy (DR), nephropathy (DN) and diabetic peripheral neuropathy (DPN) using large prospective cohort.

Methods: SES was evaluated using education attainment (individual level), household income (household level), and Townsend deprivation index (TDI, neighborhood level).

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Background: Age is the principal risk factor for neurodegeneration in both the retina and brain. The retina and brain share many biological properties; thus, insights into retinal aging and degeneration may shed light onto similar processes in the brain. Genetic makeup strongly influences susceptibility to age-related retinal disease.

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Diabetic retinopathy (DR) presents a significant concern among diabetic patients, often leading to vision impairment or blindness if left untreated. Traditional diagnosis methods are prone to human error, necessitating accurate alternatives. While various computer-aided systems have been developed to assist in DR detection, there remains a need for accurate and efficient methods to classify its stages.

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