Retinal Microcirculation Alterations in Microalbuminuric Diabetic Patients With and Without Retinopathy

The automatic detection of diabetic kidney disease from retinal vascular parameters combined with clinical variables using artificial intelligence in type-2 diabetes patients

BACKGROUND

Diabetic kidney disease (DKD) has become the largest cause of end-stage kidney disease. Early and accurate detection of DKD is beneficial for patients. The present detection depends on the measurement of albuminuria or the estimated glomerular filtration rate, which is invasive and not optimal; therefore, new detection tools are urgently needed. Meanwhile, a close relationship between diabetic retinopathy and DKD has been reported; thus, we aimed to develop a novel detection algorithm for DKD using artificial intelligence technology based on retinal vascular parameters combined with several easily available clinical parameters in patients with type-2 diabetes.

METHODS

A total of 515 consecutive patients with type-2 diabetes mellitus from Xiangyang Central Hospital were included. Patients were stratified by DKD diagnosis and split randomly into either the training set (70%, N = 360) or the testing set (30%, N = 155) (random seed = 1). Data from the training set were used to develop the machine learning algorithm (MLA), while those from the testing set were used to validate the MLA. Model performances were evaluated.

RESULTS

The MLA using the random forest classifier presented optimal performance compared with other classifiers. When validated, the accuracy, sensitivity, specificity, F1 score, and AUC for the optimal model were 84.5%(95% CI 83.3-85.7), 84.5%(82.3-86.7), 84.5%(82.7-86.3), 0.845(0.831-0.859), and 0.914(0.903-0.925), respectively.

CONCLUSIONS

A new machine learning algorithm for DKD diagnosis based on fundus images and 8 easily available clinical parameters was developed, which indicated that retinal vascular changes can assist in DKD screening and detection.

Is preclinical diabetic retinopathy in diabetic nephropathy individuals more severe?

Purpose

To analyse the retinal vessel density and thickness characteristics of diabetic nephropathy (DN) individuals with preclinical diabetic retinopathy (DR) using optical coherence tomography angiography (OCTA).

Methods

This retrospective case-control study included 88 eyes of 88 type 2 DM patients with preclinical DR [44 non-DN (NDN) and 44 DN]. OCTA images and data were acquired using AngioVue 2.0 of the spectral domain OCT device. The foveal avascular zone (FAZ) area, superficial capillary plexus (SCP) and deep capillary plexus vessel densities, ganglion cell complex (GCC) and full retinal thicknesses, peripapillary capillary density and nerve fibre layer (RNFL) thickness were compared between the NDN and DN groups. The relationship between each renal function parameter and each OCTA parameter was analysed.

Results

SCP vessel density, GCC thickness and full retinal thickness were significantly reduced in DN individuals compared to NDN individuals [(NDN versus DN) SCP vessel density: 46.65 ± 3.84% versus 44.35 ± 5.25%, p=0.030; GCC thickness: 100.79 ± 5.92 μm versus 93.28 ± 8.66 μm, p<0.001; full retinal thickness: whole area: 287.04 ± 13.62 μm versus 277.71 ± 15.10 μm, p=0.005). Within the peripapillary area, capillary density was also significantly reduced in the whole area (50.19 ± 3.10% versus 47.46 ± 5.93%, p=0.016) and some sectors in the DN group, though RNFL thickness was only decreased in some sectors. For all individuals, estimated glomerular filtration rate (eGFR) correlated significantly with most OCTA parameters and then showed a significantly negative correlation with FAZ area (β=-16.43, p=0.039) in multivariate linear regression analysis. In the NDN group, eGFR showed a significantly negative correlation with FAZ area (β=-18.746, p=0.048) and a significantly positive correlation with SCP vessel density (β=0.580, p=0.036).

Conclusion

Preclinical DR may be more severe in DN individuals than in NDN individuals with regard to microvascular and microstructural impairment. Moreover, eGFR may be a good indicator for retinal microvascular impairment.

Association of Obesity Indices with Diabetic Kidney Disease and Diabetic Retinopathy in Type 2 Diabetes: A Real-World Study

Background

Diabetic microvascular complications mainly include diabetic kidney disease (DKD) and diabetic retinopathy (DR). Obesity was recognized as a risk factor for DKD, while the reported relationship between obesity and DR was inconsistent. Moreover, whether the associations can be attributed to C-peptide levels is unknown.

Methods

Data from 1142 sequential inpatients with T2DM at Xiangyang Central Hospital between June 2019 and March 2022 were extracted retrospectively from the electronic medical record system. The associations between four obesity indices (body mass index (BMI), waist-hip circumference ratio (WHR), visceral fat tissue area (VFA), and subcutaneous fat tissue area (SFA)) and DKD and DR were evaluated. Whether the associations can be attributed to C-peptide levels was also explored.

Results

Obesity was a risk factor for DKD after adjusting for sex, HbA1c, TG, TC, HDL, LDL, smoking history, education, duration of diabetes, and insulin use (obesity indices: BMI (OR 1.050: 95% CI: 1.008-1.094; P = 0.020); WHR (OR 10.97; 95% CI: 1.250-92.267; P = 0.031); VFA (OR 1.005; 95% CI: 1.001-1.008; P = 0.008)), but it became insignificant after further adjusting for fasting C-peptide. The associations between BMI, WHR, VFA, and DKD might be U-shaped. Obesity and FCP tended to protect against DR; however, they became insignificant after adjusting for multiple potential confounders. C2/C0 (the ratio of the postprandial serum C-peptide to fasting C-peptide) was a protective factor for both DKD (OR 0.894, 95% CI: 0.833-0.959, P < 0.05) and DR (OR 0.851, 95% CI: 0.787-0.919; P < 0.05).

Conclusions

Obesity was a risk factor for DKD, and the effect may be attributable to C-peptide, which represents insulin resistance. The protective effect of obesity or C-peptide on DR was not independent and could be confounded by multiple factors. Higher C2/C0 was associated with both decreased DKD and DR.

Status and Trends of the Association Between Diabetic Nephropathy and Diabetic Retinopathy From 2000 to 2021: Bibliometric and Visual Analysis

Background: Diabetic nephropathy (DN) and diabetic retinopathy (DR) are microvascular complications of diabetes that share a similar pathogenesis and clinical relevance. The study aimed to visually analyze the research status and development trend of the relationship between DN and DR by means of bibliometrics and knowledge mapping.

Methods: Publications were collected from the Science Citation Index-Expanded of the Web of Science Core Collection between 2000 and 2021. CiteSpace, Alluvial Generator, and Microsoft Excel were used to analyze and present the data.

Results: A total of 3,348 publications were retrieved and 3,285 were included in the analysis after deduplication. The publications demonstrated an annually increasing trend. The results of the collaborative network analysis showed that the United States, Steno Diabetes Center, and Tien Y. Wong were the most influential country, institution and author, in this field of research, respectively. The analysis of references and keywords showed that the pathogenesis of DN and DR and their relationship with cardiovascular disease are research hotspots. The clinical relevance and drug therapy for DN and DR will become frontiers of future research in this field.

Conclusion: This study is the first to visualize the correlation between DN and DR using a bibliometric approach. This study provides a reference of research trends for scholars.

Optical Coherence Tomography Angiography in Type 1 Diabetes Mellitus-Report 2: Diabetic Kidney Disease

The purpose of this study is to investigate potential associations between optical coherence tomography angiography (OCTA) parameters and diabetic kidney disease (DKD) categories in type 1 diabetes mellitus (T1DM) patients and controls. A complete ocular and systemic examination, including OCTA imaging tests and bloods, was performed. OCTA parameters included vessel density (VD), perfusion density (PD), foveal avascular zone area (FAZa), perimeter (FAZp) and circularity (FAZc) in the superficial vascular plexus, and DKD categories were defined according to glomerular filtration rate (GFR), albumin-creatinine ratio (ACR) and KDIGO prognosis risk classifications. A total of 425 individuals (1 eye/1 patient) were included. Reduced VD and FAZc were associated with greater categories of GFR (p = 0.002, p = 0.04), ACR (p = 0.003, p = 0.005) and KDIGO risk prognosis classifications (p = 0.002, p = 0.005). FAZc was significantly reduced in greater KDIGO prognosis risk categories (low risk vs. moderate risk, 0.65 ± 0.09 vs. 0.60 ± 0.07, p < 0.05). VD and FAZc presented the best diagnostic performance in ROCs. In conclusion, OCTA parameters, such as VD and FAZc, are able to detect different GFR, ACR, and KDIGO categories in T1DM patients and controls in a non-invasive, objective quantitative way. FAZc is able to discriminate within T1DM patients those with greater DKD categories and greater risk of DKD progression.