Retinal microvascular changes in diabetic patients with diabetic nephropathy

A semantic segmentation method to analyze retinal vascular parameters of diabetic nephropathy

Introduction

By using spectral domain optical coherence tomography (SD-OCT) to measure retinal blood vessels. The correlation between the changes of retinal vascular structure and the degree of diabetic nephropathy is analyzed with a full-pixel Semantic segmentation method.

Methods

A total of 120 patients with diabetic nephropathy who were treated in the nephrology department of Quzhou People's Hospital from March 2023 to March 2024 were selected and divided into three groups according to the urinary albumin creatinine ratio (UACR). The groups included simple diabetes group (UACR < 30 mg/g), microalbuminuria group (30 mg/g ≤ UACR <300 mg/g) and macroalbuminuria group (UACR ≥300 mg/g). SD-OCT was used to scan the arteries and veins in the superior temporal area B of the retina. The semantic segmentation method built into the SD-eye software was used to automatically identify the morphology and structure of the vessels and calculate the parameters of arteriovenous vessels. The parameters of arteriovenous vessels are as follows: outer diameter of the retinal artery (RAOD); inner diameter of the retinal artery (RALD); arterial wall thickness (AWT); arterial wall to lumen ratio (AWLR); cross sectional area of arterial wall (AWCSA); retinal vein outer diameter (RVOD); retinal vein inner diameter (RVLD); vein wall thickness (VWT); vein wall to lumen ratio (VWLR); cross sectional area of vein wall (VWCSA). Statistical analysis software was used to compare and analyze the parameters of retinal arteriovenous vessels of the three groups.

Results

The study revealed statistically significant differences in RAOD and RALD among the three groups (p < 0.05) with the RAOD and RALD of the macroalbuminuria group and microalbuminuria group being lower than those of the simple diabetes group. Conversely, there were no significant differences in AWT, AWLR and AWCSA among the three groups (p > 0.05). Additionally, the differences in RVOD and RVLD among the three groups were found to be statistically significant (p < 0.05) with the RVOD and RVLD of the simple diabetes group being lower than those of the microalbuminuria group and macroalbuminuria group. No significant differences were observed in VWT and VWL among the groups. Additionally, RVOD and RVLD were weakly associated with UACR (R = 0.247, p = 0.007; R = 0.210, p = 0.021). Full-pixel semantic segmentation method combined with OCT images is a new retinal vascular scanning technology, which can be used as a new method for early diagnosis of diabetic nephropathy. The structural changes of retinal vessels can be used to predict the severity of diabetic nephropathy during the development of diabetic nephropathy.

Evaluating the potential of retinal photography in chronic kidney disease detection: a review

Background

Chronic kidney disease (CKD) is a significant global health concern, emphasizing the necessity of early detection to facilitate prompt clinical intervention. Leveraging the unique ability of the retina to offer insights into systemic vascular health, it emerges as an interesting, non-invasive option for early CKD detection. Integrating this approach with existing invasive methods could provide a comprehensive understanding of patient health, enhancing diagnostic accuracy and treatment effectiveness.

Objectives

The purpose of this review is to critically assess the potential of retinal imaging to serve as a diagnostic tool for CKD detection based on retinal vascular changes. The review tracks the evolution from conventional manual evaluations to the latest state-of-the-art in deep learning.

Survey Methodology

A comprehensive examination of the literature was carried out, using targeted database searches and a three-step methodology for article evaluation: identification, screening, and inclusion based on Prisma guidelines. Priority was given to unique and new research concerning the detection of CKD with retinal imaging. A total of 70 publications from 457 that were initially discovered satisfied our inclusion criteria and were thus subjected to analysis. Out of the 70 studies included, 35 investigated the correlation between diabetic retinopathy and CKD, 23 centered on the detection of CKD via retinal imaging, and four attempted to automate the detection through the combination of artificial intelligence and retinal imaging.

Results

Significant retinal features such as arteriolar narrowing, venular widening, specific retinopathy markers (like microaneurysms, hemorrhages, and exudates), and changes in arteriovenous ratio (AVR) have shown strong correlations with CKD progression. We also found that the combination of deep learning with retinal imaging for CKD detection could provide a very promising pathway. Accordingly, leveraging retinal imaging through this technique is expected to enhance the precision and prognostic capacity of the CKD detection system, offering a non-invasive diagnostic alternative that could transform patient care practices.

Conclusion

In summary, retinal imaging holds high potential as a diagnostic tool for CKD because it is non-invasive, facilitates early detection through observable microvascular changes, offers predictive insights into renal health, and, when paired with deep learning algorithms, enhances the accuracy and effectiveness of CKD screening.

Association between controlling nutritional status score and chronic kidney disease in diabetic patients: a cross-sectional study based on the National Health and Nutrition Examination Survey

PURPOSE

This study aimed to explore the association between controlling nutritional status (CONUT) score and chronic kidney disease (CKD) in type-2 diabetes mellitus (T2DM) patients.

METHODS

This was a cross-sectional study based on the National Health and Nutrition Examination Survey (NHANES). The data on demographic characteristics, physical examination, lifestyle behaviors, comorbidities, medicine use, laboratory values, and energy were extracted. Nutritional status was assessed using CONUT score, and patients were divided into normal nutrition group and malnutrition group. Association between CONUT score and CKD in T2DM patients was assessed using logistic regression analysis, and odds ratio (OR) and 95% confidence intervals (CIs) were reported. Subgroup analysis based on age, body mass index (BMI), cardiovascular disease (CVD), diabetic retinopathy, and hyperlipidemia was performed.

RESULTS

A total of 4581 patients were finally included for analysis. In the adjusted model, high CONUT score was found to be associated with the high odds of CKD (OR = 1.28, 95% CI 1.05-1.56). Also, high CONUT score was associated with the high odds of CKD in T2DM patients with age ≥ 65 years, with BMI < 25 kg/m2, with BMI ≥ 25 kg/m2, without CVD, without diabetic retinopathy, with hyperlipidemia, or without hyperlipidemia (all P < 0.05).

CONCLUSIONS

Malnutrition was associated with the high odds of CKD in T2DM patients, indicating that actively monitoring the nutritional status is important for the management of CKD in T2DM patients.

Relationship between Biochemical Pathways and Non-Coding RNAs Involved in the Progression of Diabetic Retinopathy

Diabetic retinopathy (DR) is a progressive blinding disease, which affects the vision and quality of life of patients, and it severely impacts the society. This complication, caused by abnormal glucose metabolism, leads to structural, functional, molecular, and biochemical abnormalities in the retina. Oxidative stress and inflammation also play pivotal roles in the pathogenic process of DR, leading to mitochondrial damage and a decrease in mitochondrial function. DR causes retinal degeneration in glial and neural cells, while the disappearance of pericytes in retinal blood vessels leads to alterations in vascular regulation and stability. Clinical changes include dilatation and blood flow changes in response to the decrease in retinal perfusion in retinal blood vessels, leading to vascular leakage, neovascularization, and neurodegeneration. The loss of vascular cells in the retina results in capillary occlusion and ischemia. Thus, DR is a highly complex disease with various biological factors, which contribute to its pathogenesis. The interplay between biochemical pathways and non-coding RNAs (ncRNAs) is essential for understanding the development and progression of DR. Abnormal expression of ncRNAs has been confirmed to promote the development of DR, suggesting that ncRNAs such as miRNAs, lncRNAs, and circRNAs have potential as diagnostic biomarkers and theranostic targets in DR. This review provides an overview of the interactions between abnormal biochemical pathways and dysregulated expression of ncRNAs under the influence of hyperglycemic environment in DR.