Progression of retinopathy and incidence of cardiovascular disease: findings from the Chronic Renal Insufficiency Cohort Study

Association of retinal age gap with chronic kidney disease and subsequent cardiovascular disease sequelae: a cross-sectional and longitudinal study from the UK Biobank

Background

Chronic kidney disease (CKD) increases the risk of cardiovascular disease (CVD) and is more prevalent in older adults. Retinal age gap, a biomarker of aging based on fundus images, has been previously developed and validated. This study aimed to investigate the association of retinal age gap with CKD and subsequent CVD complications.

Methods

A deep learning model was trained to predict the retinal age using 19 200 fundus images of 11 052 participants without any medical history at baseline. Retinal age gap, calculated as retinal age predicted minus chronological age, was calculated for the remaining 35 906 participants. Logistic regression models and Cox proportional hazards regression models were used for the association analysis.

Results

A total of 35 906 participants (56.75 ± 8.04 years, 55.68% female) were included in this study. In the cross-sectional analysis, each 1-year increase in retinal age gap was associated with a 2% increase in the risk of CKD prevalence [odds ratio 1.02, 95% confidence interval (CI) 1.01-1.04, P = .012]. A longitudinal analysis of 35 039 participants demonstrated that 2.87% of them developed CKD in follow-up, and each 1-year increase in retinal age gap was associated with a 3% increase in the risk of CKD incidence (hazard ratio 1.03, 95% CI 1.01-1.05, P = .004). In addition, a total of 111 CKD patients (15.81%) developed CVD in follow-up, and each 1-year increase in retinal age gap was associated with a 10% increase in the risk of incident CVD (hazard ratio 1.10, 95% CI 1.03-1.17, P = .005).

Conclusions

We found that retinal age gap was independently associated with the prevalence and incidence of CKD, and also associated with CVD complications in CKD patients. This supports the use of this novel biomarker in identifying individuals at high risk of CKD and CKD patients with increased risk of CVD.

Long-term prediction models for vision-threatening diabetic retinopathy using medical features from data warehouse

We sought to evaluate the performance of machine learning prediction models for identifying vision-threatening diabetic retinopathy (VTDR) in patients with type 2 diabetes mellitus using only medical data from data warehouse. This is a multicenter electronic medical records review study. Patients with type 2 diabetes screened for diabetic retinopathy and followed-up for 10 years were included from six referral hospitals sharing same electronic medical record system (n = 9,102). Patient demographics, laboratory results, visual acuities (VAs), and occurrence of VTDR were collected. Prediction models for VTDR were developed using machine learning models. F1 score, accuracy, specificity, and area under the receiver operating characteristic curve (AUC) were analyzed. Machine learning models revealed F1 score, accuracy, specificity, and AUC values of up 0.89, 0.89.0.95, and 0.96 during training. The trained models predicted the occurrence of VTDR at 10-year with F1 score, accuracy, and specificity up to 0.81, 0.70, and 0.66, respectively, on test set. Important predictors included baseline VA, duration of diabetes treatment, serum level of glycated hemoglobin and creatinine, estimated glomerular filtration rate and blood pressure. The models could predict the long-term occurrence of VTDR with fair performance. Although there might be limitation due to lack of funduscopic findings, prediction models trained using medical data can facilitate proper referral of subjects at high risk for VTDR to an ophthalmologist from primary care.

[Features of structural and microvascular changes of the choroid in angioretinopathy of various etiologies]

PURPOSE

To study structural and microvascular changes in the choroid in patients with chronic kidney disease (CKD), diabetic retinopathy (DR) and arterial hypertension (AH), and their relationship with the level of renal function, carbohydrate metabolism and blood pressure.

MATERIAL AND METHODS

The study involved 172 patients (325 eyes): 56 patients with CKD (109 eyes); 66 patients with DR (121 eyes); 50 patients with AH (95 eyes). All patients underwent comprehensive ophthalmological examination including visometry, biomicroscopy, ophthalmoscopy, optical coherence tomography (OCT) and OCT angiography.

RESULTS

In patients with DR and CKD, a decrease in the thickness of the ganglion cell complex and the inner plexiform layer (GCL+IPL) was noted: in proliferative DR (PDR) - 62.45±4.25 µm, in stage 4-5 CKD - 75.23±6.43 µm; a decrease in choroidal thickness (CT) of minimal values in stage 4-5 CKD (179.9±37.72 µm) and PDR (211.0±40.7 µm). The decrease in choroidal vascularity index (CVI) depended on the stage of CKD and PDR (in PDR - 63.47±1.37, in stage 4-5 CKD - 65.93±2.01). Maximum decrease in perfusion density and vascular density was found in patients with DR (37.22±9.00% and 15.11±3.39 mm, respectively). An increase in the area, perimeter of the foveolar avascular zone (FAZ), and a decrease in the circularity index were noted in all groups, with most pronounced changes in PDR and stage 4-5 CKD. Patients with CKD were found to have strong correlations of CT and CVI with creatinine, urea, proteinuria and glomerular filtration rate (GFR). Patients with diabetes mellitus and PDR were revealed to have strong relations of CT, CVI, GCL+IPL, the area and perimeter of FAZ with creatinine levels and the duration of diabetes mellitus.

CONCLUSION

Choroidal thickness and choroidal vascularity index are important diagnostic markers of disorders of chorioretinal microcirculation that allow stratifying individual assessment of risk factors for progression of both chronic kidney disease and diabetic retinopathy.

Development and validation of a predictive risk model based on retinal geometry for an early assessment of diabetic retinopathy

AIMS

This study aimed to develop and validate a risk nomogram prediction model based on the retinal geometry of diabetic retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM) and to investigate its clinical application value.

METHODS

In this study, we collected the clinical data of 410 patients with T2DM in the Second Affiliated Hospital of Chongqing Medical University between October 2020 and March 2022. Firstly, the patients were randomly divided into a development cohort and a validation cohort in a ratio of 7:3. Then, the modeling factors were selected using the least absolute shrinkage and selection operator (LASSO). Subsequently, a nomogram prediction model was built with these identified risk factors. Two other models were constructed with only retinal vascular traits or only clinical traits to confirm the performance advantage of this nomogram model. Finally, the model performances were assessed using the area under the receiver operating characteristic curve (AUC), calibration plot, and decision curve analysis (DCA).

RESULTS

Five predictive variables for DR among patients with T2DM were selected by LASSO regression from 33 variables, including fractal dimension, arterial tortuosity, venular caliber, duration of diabetes mellitus (DM), and insulin dosage (P< 0.05). A predictive nomogram model based on these selected clinical and retinal vascular factors presented good discrimination with an AUC of 0.909 in the training cohort and 0.876 in the validation cohort. By comparing the models, the retinal vascular parameters were proven to have a predictive value and could improve diagnostic sensitivity and specificity when combined with clinical characteristics. The calibration curve displayed high consistency between predicted and actual probability in both training and validation cohorts. The DCA demonstrated that this nomogram model led to net benefits in a wide range of threshold probability and could be adapted for clinical decision-making.

CONCLUSION

This study presented a predictive nomogram that might facilitate the risk stratification and early detection of DR among patients with T2DM.

Novel biomarkers and therapeutic approaches for diabetic retinopathy and nephropathy: Recent progress and future perspectives

The global burden due to microvascular complications in patients with diabetes mellitus persists and even increases alarmingly, the intervention and management are now encountering many difficulties and challenges. This paper reviews the recent advancement and progress in novel biomarkers, artificial intelligence technology, therapeutic agents and approaches of diabetic retinopathy and nephropathy, providing more insights into the management of microvascular complications.

[Development, clinical manifestations and diagnosis of retinal changes in chronic kidney disease]

Chronic kidney disease (CKD) is a significant public health problem with a high risk of developing age-dependent eye diseases. Renal glomeruli and the choroid have similar structures and vascular networks; the internal hematoretinal barrier and the glomerular filtration barrier have similar developmental path; the renin-angiotensin-aldosterone hormonal system is found in both the eye and the kidneys. All this determines the similarity of physiological and pathogenetic features of the development of diseases associated with these organs. The article discusses general risk factors and pathophysiological mechanisms of development of retinal and renal lesions in CKD, the influence of various factors of pathogenesis on their development and progression. The anatomical similarity of vascularization, accompanied by microvascular changes in the retina and kidneys, leads to similar complications in both organs. Optical coherence tomography (OCT) and optical coherence tomography angiography (OCT-A) are accurate, well reproducible and non-invasive methods for diagnosing and assessing changes in the retinal microvascular bed, which make it possible to assess microvasculature changes in the kidneys. In CKD, the retina shows signs of impaired capillary perfusion, a decrease in their density, expansion of intercapillary spaces, a rarefaction of the density of the parafoveolar capillary network, which may indicate a decrease in peritubular capillary blood flow, blood circulation of the kidneys in general and their ischemia. Significant thinning of the retina and choroid, along with a decrease in macular volume, even in the initial stages of CKD, is accompanied by impaired renal function (changes in the estimated glomerular filtration rate and urinary albumin excretion), which is a sign of systemic microvascular lesion and pathological process in the kidneys. Therefore, monitoring of retinal vessels using OCT and OCT-A can become a reliable indicator of the progression of renal microvascular changes at any stage of the disease.