Renal Function Markers Predict Risk of Specific Fundus Lesions in CKD: A Cross- Sectional Risk-Stratification Study

Renal Function Markers Predict Risk of Specific Fundus Lesions in CKD: A Cross- Sectional Risk-Stratification Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Renal Function Markers Predict Risk of Specific Fundus Lesions in CKD: A Cross- Sectional Risk-Stratification Study Yuran Chen, Min Hu, Weiwei Dai, Chaokui Huo, Wai Cheng Iao, Huayin Chen, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9190108/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objectives To investigate the association between renal function markers and fundus damage in patients with chronic kidney disease(CKD). Methods Basic demographic information, renal function parameters, and data related to fundus lesions were collected. The correlations between kidney disease and ocular disease, as well as the associations between renal function markers and various ocular pathologies, were analyzed. Results Analysis of odds ratios (OR) between ocular and renal variables revealed a significantly increased risk of ocular diseases in patients with kidney disease, with particularly elevated risks for retinal hemorrhage and macular edema. Boxplot analyses further demonstrated that specific fundus phenotypes, such as retinal exudates, retinal hemorrhage, and macular edema, were significantly associated with markers of renal impairment, including estimated glomerular filtration rate (eGFR), serum creatinine, blood urea nitrogen, urinary protein, and urinary microalbumin. Further analysis of eGFR data indicated that for every 10 ml/(min·1.73 m²) decrease in eGFR, the risks of retinal hemorrhage, diabetic retinopathy, macular edema, hypertensive retinopathy, and retinal exudates increased by 27%, 25%, 20%, 20%, and 12%, respectively. Conclusions Patients with kidney disease have a significantly increased risk of developing ocular diseases, particularly retinal hemorrhage and macular edema. There are significant differences in specific fundus phenotypes according to markers of renal impairment, suggesting that renal dysfunction may indirectly elevate the risk of retinal lesions and macular edema by affecting systemic vascular health. Moreover, a decline in eGFR is closely associated with increased risks of various ocular diseases. Kidney disease Ocular disease Glomerular filtration rate Correlation Clinical data Microangiopathy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The interplay between chronic kidney disease (CKD) and ocular diseases has increasingly become a focus of interdisciplinary research. Globally, CKD affects approximately 850 million individuals suffering from the disease. Notably, over 40% of patients are already in the middle or late stages of CKD at the time of initial diagnosis, partly due to the suboptimal sensitivity of traditional renal function markers (such as serum creatinine) for early disease detection 1 , 2 . This limitation underscores the urgent need for more effective early diagnostic approaches. Recent studies have highlighted the retina as a window into the systemic microcirculation 3 , 4 , 5 , suggesting that retinal lesions (such as exudates and hemorrhages) may offer novel avenues for early CKD screening. Anatomically, the retinal and glomerular microvasculature share similar vascular networks and certain pathological regulatory pathways (e.g., involving vascular endothelial growth factor and inflammation) 6 . Clinical research has also provided compelling evidence for this association: patients with diabetic retinopathy (DR) have a 2.4-fold increased risk of developing diabetic nephropathy compared to the general population 7 , while the incidence of retinal arteriolosclerosis in patients with hypertensive nephropathy is significantly higher than in the general population 8 . However, current research on the relationship between CKD and ocular diseases remains limited. Most studies focus on single ocular indicators or specific types of eye diseases, lacking comprehensive investigations into the phenotypic differences of ocular diseases among CKD patients with varying etiologies and disease stages. Systematic analyses of the relationships between multidimensional renal function markers and a broad spectrum of fundus phenotypes are yet to be conducted. This study adopts a cross-sectional design to systematically explore the strength of associations between renal impairment and various ocular diseases. The findings are expected to provide a scientific basis for establishing an eye-kidney comorbidity warning system in clinical practice and to inform the development of individualized and precise treatment strategies. Methods 2.1 Study Population This is a retrospective, single-center, cross-sectional study. A total of 641 patients who underwent nephrology-ophthalmology consultations at the First Affiliated Hospital of Guangzhou Medical University from January 2020 to April 2023 were enrolled. Inclusion criteria were a diagnosis of kidney disease (including chronic kidney disease, diabetic nephropathy, glomerulonephritis, etc.) and completion of fundus examinations. Patients with other severe systemic diseases (such as malignancies, autoimmune diseases) or ocular lesions due to other causes (such as trauma or surgical history) were excluded. 2.2 Data Collection Collected data included basic demographic information (such as sex and age), visual acuity, refraction, intraocular pressure, slit-lamp anterior segment examination, Scanning Laser Ophthalmoscope(SLO) and macular optical coherence tomography (OCT). Laboratory tests included serum creatinine, blood urea nitrogen, urinary protein, urinary N-acetyl-β-D-glucosaminidase (NAG), and urinary microalbumin. All ocular symptoms were evaluated and diagnosed by attending or senior ophthalmologists, while the type of kidney disease was diagnosed by attending or senior nephrologists. The estimated glomerular filtration rate (eGFR) was calculated using the 2021 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) Eq. 9. 2.3 Statistical Analysis Statistical analyses were performed using IBM SPSS Statistics 25.0. A p-value < 0.05 was considered statistically significant. All quantitative data are presented as mean ± standard deviation. Pearson correlation analysis was used to assess the relationships between ocular and renal symptoms. Ocular parameters included lens opacity, anterior segment findings, vitreous liquefaction and opacities, arteriovenous crossing changes, macular foveal reflex, retinal hemorrhage, and retinal exudates. Renal parameters included diabetic retinopathy, kidney disease, chronic renal failure, acute renal failure, chronic glomerulonephritis, uremia, and chronic kidney disease. Boxplot analysis (Mann-Whitney U test) was used to compare differences in renal function markers among different ocular disease groups. Furthermore, multivariate logistic regression was performed to assess the association between eGFR levels and DR, categorizing eGFR into three clinically relevant groups: ≥90, 60–89, and < 60 ml / (min·1.73 m²), with eGFR ≥ 90 ml/(min·1.73 m²) as the reference. To control for confounding factors, age, hypertension, and hyperlipidemia were included as covariates in the regression model. Results are presented as odds ratios (OR) with 95% confidence intervals (CI), and a p-value < 0.05 was considered statistically significant. Results 3.1 Dataset Summary A total of 641 patients were included in this study, with a mean age of 54.75 ± 16.16 years. Among them, 56.3% (n = 361) were male and 43.7% (n = 280) were female. The types of kidney disease among the patients were classified according to disease course as chronic kidney disease (CKD, stages 1–5) and acute kidney disease; and according to etiology as diabetic nephropathy, hypertensive nephropathy, obstructive nephropathy, membranous nephropathy, and chronic glomerulonephritis. The main types of fundus lesions included diabetic retinopathy, hypertensive retinopathy, retinal hemorrhage, macular edema, and retinal exudates. The general demographic and clinical characteristics of the patients are summarized in Table_1, Figure_1. 3.2 Odds Ratios for Kidney–Ocular Disease Associations In this study, we explored the associations between different types of kidney disease and ocular diseases, and quantified the strength of these associations by calculating odds ratio (OR). Significant correlations were observed between various ocular diseases and kidney diseases. Diabetic nephropathy was significantly associated with multiple ocular manifestations, including lens opacity, retinal hemorrhage, and macular edema. Chronic kidney disease was mainly associated with retinal hemorrhage, retinal exudates, and macular edema. The associations between different types of kidney disease and ocular manifestations varied: hypertensive nephropathy was primarily associated with retinal hemorrhage, while chronic glomerulonephritis was significantly associated with lens opacity, among others (Figure_2). 1. Diabetic Nephropathy: Patients with diabetic nephropathy had significantly higher risks of developing lens opacity (OR = 1.74, p < 0.05), retinal hemorrhage (OR = 5.87, p < 0.01), retinal exudates (OR = 4.22, p < 0.01), macular edema (OR = 2.63, p < 0.01), and vitreous opacity (OR = 1.64, p < 0.05) compared to those without diabetic nephropathy. 2. Chronic Kidney Disease: Patients with chronic kidney disease had significantly higher risks of retinal hemorrhage (OR = 5.20, p < 0.01), retinal exudates (OR = 2.25, p < 0.01), and macular edema (OR = 4.93, p < 0.01) compared to those without chronic kidney disease. 3. Hypertensive Nephropathy: Patients with hypertensive nephropathy had a significantly lower risk of retinal hemorrhage (OR = 0.49, p < 0.01) compared to those without hypertensive nephropathy. 4. Chronic Glomerulonephritis: Patients with chronic glomerulonephritis had significantly lower risks of lens opacity (OR = 0.53, p < 0.05), retinal hemorrhage (OR = 0.46, p < 0.05), and retinal exudates (OR = 0.47, p < 0.05) compared to those without chronic glomerulonephritis. 3.3 Renal Markers and Fundus Lesions Boxplot analyses revealed significant differences in renal function markers among patients with different ocular disease statuses: 1. eGFR Distribution: The eGFR values in the hypertensive retinopathy group (p < 0.01), retinal exudate group (p < 0.01), retinal hemorrhage group (p < 0.01), diabetic retinopathy group (p < 0.01), and macular edema group (p < 0.01) were all significantly lower than those in their respective control groups without these lesions, suggesting an association between ocular disease and renal dysfunction (Figure_3A). 2. Urinary Microalbumin: Urinary microalbumin levels were significantly higher in the retinal hemorrhage group compared to the non-hemorrhage group (p < 0.01), with the most pronounced difference observed in the retinal hemorrhage group. This suggests that combined assessment of urinary microalbumin and retinal hemorrhage may serve as an early warning indicator (Figure_3B). 3. Serum Creatinine: Serum creatinine levels were significantly higher in patients with hypertensive retinopathy (p < 0.01), retinal exudates (p < 0.01), and macular edema (p < 0.01) compared to those without retinal lesions, indicating a close relationship between renal impairment and these ocular diseases. 4. Urinary Protein: Urinary protein levels were significantly higher in patients with diabetic retinopathy (p < 0.05) and retinal exudates (p < 0.01) compared to control groups without these lesions, suggesting that glomerular permeability may be affected by ocular disease. 5. Blood Urea Nitrogen: Blood urea nitrogen levels were significantly higher in patients with retinal hemorrhage compared to those without hemorrhage (p < 0.05), indicating possible impairment of glomerular filtration function. 3.4 Ocular Signs Linked to eGFR Decline Multivariate logistic regression analysis demonstrated that eGFR is a significant risk factor for the development of various ocular diseases. The relationship between declining eGFR and the odds ratios for ocular symptoms is shown in Table_2 and Figure_4. 1. Declining eGFR independently increases the risk of multiple ocular diseases. For every 10 ml/(min·1.73 m²) decrease in eGFR, the risks of retinal hemorrhage, diabetic retinopathy (DR), macular edema, hypertensive retinopathy, and retinal exudates increased by 27%, 20%, 20%, 14%, and 12%, respectively, all of which were statistically significant (p < 0.05). This indicates that renal dysfunction significantly exacerbates the risk of ocular complications. 2. The extent of risk increase differs among ocular disease. The risk increase was most pronounced for retinal hemorrhage (OR = 1.27), followed by DR (OR = 1.25) and macular edema (OR = 1.25), while the risk increases for retinal exudates and hypertensive retinopathy were relatively lower (OR = 1.12 and 1.20, respectively), suggesting that declining eGFR has a more pronounced impact on certain ocular diseases. 3. A dose-dependent relationship exists between eGFR decline and ocular disease risk. As also shown in the Appendix Table 2, with each fixed unit decrease in eGFR, the risks of multiple ocular diseases showed a consistent upward trend, and the 95% confidence intervals did not include 1 (p < 0.05), further supporting the clinical value of eGFR as a predictive marker for ocular complications. 3.5 Diagnostic Performance of Renal Markers and Age for Ocular Signs Receiver Operating Characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of eGFR, urinary microalbumin, and age in predicting the presence of various ocular signs (Figure 5). For predicting retinal hemorrhage, eGFR demonstrated the highest discriminatory ability (Area Under the Curve [AUC] = 0.67), followed by urinary microalbumin (AUC = 0.65). Similar analyses for macular edema revealed AUCs of 0.62 for both eGFR and urinary microalbumin. When predicting retinal exudates, the AUCs were 0.67 (eGFR), 0.65 (urinary microalbumin), and 0.45 (age). Discussion Based on a cohort of 641 CKD patients, this study is the first to comprehensively evaluate the association strength between serum creatinine, blood urea nitrogen, urinary protein, urinary microalbumin, and eGFR with retinal hemorrhage, exudates, macular edema, diabetic retinopathy, and hypertensive retinopathy. The results indicate that greater renal impairment increases the risk of fundus lesions, suggesting shared pathogenic mechanisms involving systemic microvascular disease, oxidative stress, and inflammatory pathways. 4.1 Kidney–Eye Disease Associations This study systematically elucidates the clinical association strength between different types of kidney disease and specific ocular diseases. Notably, diabetic nephropathy (DN) showed a particularly strong association with retinal hemorrhage (OR = 5.87), retinal exudates (OR = 4.22), and macular edema (OR = 2.63), while CKD was strongly associated with retinal exudates (OR = 2.25) and macular edema (OR = 4.93). These findings not only confirm the shared pathological basis of the renal and ocular microvascular systems but also reveal the heterogeneity in the mechanisms by which different types of kidney disease drive ocular pathology. From a pathophysiological perspective, diabetic nephropathy and retinal disease share hyperglycemia-induced endothelial injury pathways. Advanced glycation end products (AGEs) activate oxidative stress and inflammatory responses, disrupting both the glomerular filtration and blood-retinal barriers 10 , 11 , 12 , which may explain the strong association between DN and retinal hemorrhage. Recent mechanistic studies provide further biological explanations: uremic toxins (such as indoxyl sulfate) accumulated in CKD patients can activate the ROS-NFκB pathway, damaging the blood-retinal barrier and directly leading to vascular leakage and hemorrhage 13 , which mechanistically aligns with the high risk of retinal hemorrhage and macular edema observed in this study. Our findings indicated a significantly lower risk of retinal hemorrhage in patients with hypertensive nephropathy (OR = 0.49, p < 0.01) compared to the reference group. This unexpected protective association warrants further exploration. While systemic hypertension is a risk factor for retinal hemorrhage, it is plausible that patients specifically identified with hypertensive nephropathy in our cohort are subject to distinct management strategies (e.g., more intensive blood pressure control or specific antihypertensive classes) that could mitigate hemorrhagic risk. Alternatively, The relatively weaker association between hypertensive nephropathy and retinal hemorrhage (OR = 0.49, p < 0.01) may suggest its pathology may focus more on arteriolosclerosis than microvascular leakage. This is consistent with the longitudinal findings of Sabanayagam et al., who reported that retinal arteriolar narrowing independently predicts renal function decline 14 , but its impact on hemorrhagic lesions may be buffered by hemodynamic compensatory mechanisms. In contrast, the negative associations observed between chronic glomerulonephritis (CGN) and lens opacity (OR = 0.53, p < 0.05), retinal hemorrhage (OR = 0.46, p < 0.05), and retinal exudates (OR = 0.47, p < 0.05) may suggest that immune-mediated renal injury (such as complement activation or antibody deposition) affects the ocular microenvironment through unique pathways 15 , 16 , indicating that immune regulation may counteract exudative processes. Clinical studies have shown that patients with diabetic retinopathy (DR) have an increased risk of developing diabetic nephropathy, and the incidence of retinal arteriolosclerosis is higher in patients with hypertensive nephropathy 17 , 18 , 19 . These findings suggest that kidney and ocular diseases may share common pathophysiological mechanisms, such as microvascular disease, oxidative stress, and inflammatory responses 20 , which may play a role in the development and progression of both conditions. 4.2 eGFR Decline and Ocular Risk Systemic vascular endothelial dysfunction resulting from renal impairment may be an important underlying mechanism linking kidney and ocular diseases. Our results demonstrate a significant association between declining eGFR and the risk of various fundus lesions in CKD patients. Specifically, for every 10 ml/(min·1.73 m²) decrease in eGFR, the risks of retinal hemorrhage, diabetic retinopathy, macular edema, hypertensive retinopathy, and retinal exudates increased by 27%, 25%, 20%, 20%, and 12%, respectively. This finding is highly consistent with large-scale epidemiological studies, such as the CRIC Study by Juan E. Grunwald et al. (n = 1904), which found that patients with GFR < 30 ml/min/1.73 m² had a threefold increased risk of retinopathy 21 . As renal function declines, the kidneys are less able to clear metabolic waste and toxins, leading to their accumulation, which in turn induces oxidative stress and inflammation, damaging systemic vascular endothelial cells 22 , 23 . As part of the systemic microvascular system, retinal vessels are similarly affected 24 , resulting in retinal microvascular disease. Thus, a decrease in eGFR not only reflects the degree of renal impairment but may also indirectly indicate the extent of systemic vascular endothelial dysfunction 25 , closely linking it to the risk of fundus lesions. Our forest plot analysis further showed that specific fundus phenotypes, such as retinal exudates, retinal hemorrhage, and macular edema, were significantly different in relation to eGFR, serum creatinine, blood urea nitrogen, urinary protein, and urinary microalbumin (Figure_5). This suggests that renal dysfunction may increase the risk of retinal lesions and macular edema by affecting systemic vascular health. As a key indicator of renal function, eGFR decline is closely associated with increased risk of multiple ocular diseases. Our quantitative analysis found that for every 10 ml/(min·1.73 m²) decrease in eGFR, the risks of retinal hemorrhage, macular edema, hypertensive retinopathy, and retinal exudates increased by 27%, 20%, 14%, and 12%, respectively. This provides important quantitative evidence for clinicians, highlighting that monitoring renal function is crucial for managing kidney disease and for early screening and intervention of ocular diseases. In particular, patients with declining renal function should undergo more frequent fundus examinations to facilitate early detection and intervention of ocular disease. 4.3 Ocular Signs as Early Renal Indicators By analyzing the distribution differences of various renal function markers in the presence of different fundus lesions, this study reveals the potential early warning value of five ocular manifestations—retinal exudates, retinal hemorrhage, macular edema, lens opacity, and vitreous opacity—for different renal function markers. Our results suggest that the presence of retinal exudates, retinal hemorrhage, or macular edema is associated with significantly lower eGFR compared to patients without these ocular symptoms, indicating a strong correlation between multiple types of retinal microvascular injury and renal function decline, whereas lens opacity and vitreous opacity do not reflect renal function status. This finding is consistent with the results of the multicenter cohort study by Juan E. Grunwald et al. 26 . Anatomically, since the kidney and retina develop during the same embryonic stage, the retinal and glomerular microvasculature share significant similarities in structure, function, and pathological mechanisms 27 , 28 , 29 , 30 , including common regulatory pathways and the renin-angiotensin-aldosterone system (RAAS) 31 , 32 . These lines of evidence suggest that the eye-kidney association is largely based on their shared microvascular architecture, and our study further demonstrates that retinal lesions can serve as indicators of eGFR decline, providing a foundation for future research on eye-kidney comorbidity. Our findings indicate that different retinal signs may reflect abnormalities in different renal function markers. For example, patients with retinal hemorrhage had significantly higher blood urea nitrogen and urinary microalbumin levels. Urinary microalbumin is an early marker of glomerular filtration membrane damage and systemic microvascular endothelial injury; its elevation indicates glomerular microvascular disease 33 , 34 . In this study, the difference in urinary microalbumin was most pronounced in the retinal hemorrhage group. As a severe manifestation of retinal microvascular disease, retinal hemorrhage may share a common pathophysiological basis with elevated urinary microalbumin. Therefore, combined assessment of urinary microalbumin and retinal hemorrhage may facilitate early identification of eye-kidney comorbidity. In patients with kidney disease, non-invasive and convenient retinal examination may indirectly reflect the type of renal impairment, thereby enhancing the comprehensive management of kidney disease in clinical practice. 4. 4 Limitations This study provides new evidence for the association between kidney disease and ocular disease, particularly in quantifying the relationship between renal function markers and fundus lesions. However, several limitations should be noted. First, as a cross-sectional study, causality between renal function decline and ocular disease cannot be established. Second, being a single-center study, the generalizability of the results may be limited. Additionally, the study did not include dynamic data on changes in renal function markers, precluding further exploration of the impact of renal function changes on the progression of ocular disease. Future research should employ longitudinal designs and include data from multiple centers to further investigate the pathophysiological mechanisms linking kidney and ocular diseases. Conclusion This study reveals the multi-layered pathological nature of the association between declining renal function and ocular disease, analyzes the associations between different types of kidney disease and ocular symptoms, and quantifies the specific risks of various ocular lesions associated with renal function decline. These findings provide new insights for the clinical management of patients with kidney disease, may enhance clinical awareness of eye-kidney comorbidity, and offer further clinical evidence for future research on the eye-kidney connection. Declarations Ethics approval and consent to participate The study was approved by the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University (Approval No. : ES-2024-157-01), and all procedures adhered to the principles of the Declaration of Helsinki. Disclosure of interest The authors report no conflict of interest. Clinical trial number Not applicable. Consent to participate This retrospective case analysis has obtained ethical approval from the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University (Approval No.: ES-2024-157-01). In accordance with the approval decision of this ethics committee, informed consent for this study has been waived. Funding: 1. Medical Science and Technology Research Foundation of Guangdong Province(A2024147); 2. Guangzhou Science and Technology Bureau Basic Research Program Municipal School (Institute) Enterprise joint funding Project (SL2024A03J01543) Author Contribution Yuran Chen: Writing-Original Draft, Investigation, Data Curation, Project administration. Min Hu: Writing-Review & Editing, Methodology, Formal analysis, Data Curation, Visualization. Weiwei Dai: Writing-Review& Editing, Conceptualization, Methodology. Chaokui Huo: Writing- Review & Editing, Conceptualization, Methodology. Wai Cheng Iao: Writing-Review & Editing, Conceptualization, Methodology. Huayin Chen: Writing-Review & Editing, Investigation. Jianmei Lu: Writing-Review & Editing, Investigation Hao Cheng: Writing-Review & Editing, Conceptualization, Methodology, Supervision, Resources. Danmin Cao: Writing-Review & Editing, Conceptualization, Methodology, Supervision, Resources, Funding acquisition. 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Microvascular changes at different stages of chronic kidney disease. J Clin Hypertens (Greenwich). 2021;23(2):309–16. 10.1111/jch.14138 . Grunwald JE, Alexander J, Ying GS, et al. Retinopathy and chronic kidney disease in the Chronic Renal Insufficiency Cohort (CRIC) study. Arch Ophthalmol. 2012;130(9):1136–44. 10.1001/archophthalmol.2012.1800 . Goyal JL, Gupta A, Gandhi P. Ocular manifestations in renal diseases. Indian J Ophthalmol. 2023;71(8):2938–43. 10.4103/IJO.IJO_3234_22 . Bodaghi B, Massamba N, Izzedine H. The eye: a window on kidney diseases. Clin Kidney J. 2014;7(4):337–8. 10.1093/ckj/sfu073 . Wilkinson-Berka JL, Agrotis A, Deliyanti D. The retinal renin-angiotensin system: roles of angiotensin II and aldosterone. Peptides. 2012;36(1):142–50. 10.1016/j.peptides.2012.04.008 . Farrah TE, Dhillon B, Keane PA, Webb DJ, Dhaun N. The eye, the kidney, and cardiovascular disease: old concepts, better tools, and new horizons. Kidney Int. 2020;98(2):323–42. 10.1016/j.kint.2020.01.039 . Singh A, Satchell SC. Microalbuminuria: causes and implications. Pediatr Nephrol. 2011;26(11):1957–65. 10.1007/s00467-011-1777-1 . Epub 2011 Feb 8. PMID: 21301888; PMCID: PMC3178015. Prasad RM, Bali A, Tikaria R. Microalbuminuria. StatPearls. Volume 30. Treasure Island (FL): StatPearls Publishing; 2023. Tables Table_1. Demographic and Clinical Characteristics of the Study Population Characteristics n (%) Demographics Female 280 (43.7%) Renal observations Diabetic Nephropathy 122 (19.3%) Hypertensive Nephropathy 103 (16.3%) Obstructive Nephropathy 2 (0.3%) Membranous Nephropathy 3 (0.5%) Chronic Glomerulonephritis 74 (11.7%) Ophthalmic observations Lens Opacities 379 (60.1%) Vitreous Opacities 430 (68.1%) Macular Edema 35 (5.5%) Retinal Hemorrhage 201 (31.9%) Retinal Exudates 175 (27.7%) Mean±SD Demographics Age 55.03 ± 16.05 Biometrics Urinary Microalbumin 1334.16 ± 1487.94 Urinary Protein 2.68 ± 3.17 Urinary NAG 13.16 ± 21.42 Urinary Beta2-Microglobulin 3.23 ± 6.56 Blood Urea Nitrogen 16.51 ± 23.48 eGFR 35.20 ± 33.73 Table_2.Association Between Declining eGFR and Odds Ratios for Ocular Symptoms Lens Opacity (n=380) Vitreous Opacities (n=434) Macular Edema (n=35) Retinal Hemorrhage (n=203) Retinal Exudates (n=175) eGFR ml/(min・1.73 m²) Count OR (95%CI) p OR (95%CI) p OR (95%CI) p OR (95%CI) p OR (95%CI) p >90 58 Ref. - Ref. - Ref. - Ref. - Ref. - 60~90 84 1.34 (0.61, 2.97) 0.469 1.17 (0.57, 2.41) 0.666 inf* - 3.24 (1.01, 10.40) 0.048 1.92 (0.74, 4.98) 0.179 <60 496 0.91 (0.48, 1.72) 0.768 1.31 (0.73, 2.33) 0.365 inf* - 8.78 (3.11, 24.80) <0.001 3.06 (1.35, 6.94) <0.05 35.1 ± 32.2 638 0.91 (0.76, 1.09) 0.317 1.02 (0.87, 1.21) 0.779 1.84 (1.15, 2.94) <0.05 2.16 (1.73, 2.70) <0.001 1.44 (1.18, 1.76) <0.001 *Odds ratios could not be estimated (denoted by inf) due to zero events observed in a comparison group Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9190108","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":619878475,"identity":"a320f595-17ea-4f1e-b2f3-e8ac33dce52a","order_by":0,"name":"Yuran Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuran","middleName":"","lastName":"Chen","suffix":""},{"id":619878480,"identity":"9af9a424-23e7-4a4a-968c-fbcb5ca59a86","order_by":1,"name":"Min Hu","email":"","orcid":"","institution":"Changsha Aier Eye Hospital","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Hu","suffix":""},{"id":619878485,"identity":"e01faf9f-0d18-489f-9b68-5d65c5c1d037","order_by":2,"name":"Weiwei Dai","email":"","orcid":"","institution":"Changsha Aier Eye Hospital","correspondingAuthor":false,"prefix":"","firstName":"Weiwei","middleName":"","lastName":"Dai","suffix":""},{"id":619878487,"identity":"c93fc322-1261-467b-bde3-252faedf4819","order_by":3,"name":"Chaokui Huo","email":"","orcid":"","institution":"The Fourth People's Hospital of Shenzhen","correspondingAuthor":false,"prefix":"","firstName":"Chaokui","middleName":"","lastName":"Huo","suffix":""},{"id":619878488,"identity":"eacd1822-e61c-49dd-8f58-6c2af487f4fb","order_by":4,"name":"Wai Cheng Iao","email":"","orcid":"","institution":"The First Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wai","middleName":"Cheng","lastName":"Iao","suffix":""},{"id":619878490,"identity":"ea8caa5c-9246-4ab3-869e-58ede809417b","order_by":5,"name":"Huayin Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Huayin","middleName":"","lastName":"Chen","suffix":""},{"id":619878492,"identity":"2d54d40c-fb9a-423a-8603-c7c6ecfb3eab","order_by":6,"name":"Jianmei Lu","email":"","orcid":"","institution":"The First Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jianmei","middleName":"","lastName":"Lu","suffix":""},{"id":619878493,"identity":"e27c0618-6ac2-446b-8472-5ee766db1bf6","order_by":7,"name":"Hao Cheng","email":"","orcid":"","institution":"The First Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"Cheng","suffix":""},{"id":619878494,"identity":"4ed845cd-528e-41d0-9f6c-be6c2afedd9a","order_by":8,"name":"##Danmin Cao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAt0lEQVRIiWNgGAWjYFCCBIbDf37YyLGxNx8gWgvjAd6eNGM+nmMJRGthPsDDdjhxnkSOAnEa+NuzEw5I8DCntzHkMDD8qNhGWIvEmbcbDhhYsOW2MZw9wNhz5jZhLQYSuRsOJPDw5LYx9iUwM7YRq+UAm0Q6GzOPAfFaDjawGSSwsRGrBeSXw4w9CYZtPGwJB4nyC3977ubPDD/+y8vPf3zwwY8KIrSggAMkqh8Fo2AUjIJRgAsAAH2JPVXZKPDdAAAAAElFTkSuQmCC","orcid":"","institution":"The First Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":true,"prefix":"","firstName":"##Danmin","middleName":"","lastName":"Cao","suffix":""}],"badges":[],"createdAt":"2026-03-22 09:08:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9190108/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9190108/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106579905,"identity":"6799238d-96ad-488b-825d-3599be348a1b","added_by":"auto","created_at":"2026-04-10 06:34:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":247004,"visible":true,"origin":"","legend":"\u003cp\u003eSigns of fundus damage: A: SLO shows retinal hemorrhage; B: SLO shows retinal exudation; C: OCT shows macular edema.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9190108/v1/faacab3c73a7d93d308e082c.png"},{"id":106579906,"identity":"03ff723f-4516-4270-9106-1c6fb2636a83","added_by":"auto","created_at":"2026-04-10 06:34:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":255130,"visible":true,"origin":"","legend":"\u003cp\u003eOdds ratios for associations between different types of kidney disease and ocular manifestations.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9190108/v1/a96160e38b2648894c0ee758.png"},{"id":106579907,"identity":"8a497372-9763-48e4-84fe-70e7ad0a3e79","added_by":"auto","created_at":"2026-04-10 06:34:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":413038,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots of eGFR (A) and urinary microalbumin (B) distribution in various ocular diseases.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9190108/v1/806b41e920083d89331d41fc.png"},{"id":106579908,"identity":"7ff0d750-d959-4acf-bc88-4cf4acc5c2d5","added_by":"auto","created_at":"2026-04-10 06:34:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":151213,"visible":true,"origin":"","legend":"\u003cp\u003eOdds ratios for ocular symptoms associated with declining eGFR.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9190108/v1/1c75b0ed37f87bf5fe3930b1.png"},{"id":106725355,"identity":"5095171a-3652-4450-9bd8-c388b40bb166","added_by":"auto","created_at":"2026-04-12 18:32:34","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":311021,"visible":true,"origin":"","legend":"\u003cp\u003eDiagnostic performance (ROC Curve) of urinary microalbumin, eGFR, and age in predicting ocular signs.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-9190108/v1/67d766057ecf5633a3690630.png"},{"id":107970115,"identity":"a0d739ba-9010-4be7-a2ec-c73c751322ac","added_by":"auto","created_at":"2026-04-28 06:40:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1666239,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9190108/v1/664a2f66-f851-42f5-b3c9-06846051ef6c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Renal Function Markers Predict Risk of Specific Fundus Lesions in CKD: A Cross- Sectional Risk-Stratification Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe interplay between chronic kidney disease (CKD) and ocular diseases has increasingly become a focus of interdisciplinary research. Globally, CKD affects approximately 850\u0026nbsp;million individuals suffering from the disease. Notably, over 40% of patients are already in the middle or late stages of CKD at the time of initial diagnosis, partly due to the suboptimal sensitivity of traditional renal function markers (such as serum creatinine) for early disease detection \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. This limitation underscores the urgent need for more effective early diagnostic approaches.\u003c/p\u003e \u003cp\u003eRecent studies have highlighted the retina as a window into the systemic microcirculation \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, suggesting that retinal lesions (such as exudates and hemorrhages) may offer novel avenues for early CKD screening. Anatomically, the retinal and glomerular microvasculature share similar vascular networks and certain pathological regulatory pathways (e.g., involving vascular endothelial growth factor and inflammation) \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Clinical research has also provided compelling evidence for this association: patients with diabetic retinopathy (DR) have a 2.4-fold increased risk of developing diabetic nephropathy compared to the general population \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, while the incidence of retinal arteriolosclerosis in patients with hypertensive nephropathy is significantly higher than in the general population \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHowever, current research on the relationship between CKD and ocular diseases remains limited. Most studies focus on single ocular indicators or specific types of eye diseases, lacking comprehensive investigations into the phenotypic differences of ocular diseases among CKD patients with varying etiologies and disease stages. Systematic analyses of the relationships between multidimensional renal function markers and a broad spectrum of fundus phenotypes are yet to be conducted. This study adopts a cross-sectional design to systematically explore the strength of associations between renal impairment and various ocular diseases. The findings are expected to provide a scientific basis for establishing an eye-kidney comorbidity warning system in clinical practice and to inform the development of individualized and precise treatment strategies.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cb\u003e2.1 Study Population\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis is a retrospective, single-center, cross-sectional study. A total of 641 patients who underwent nephrology-ophthalmology consultations at the First Affiliated Hospital of Guangzhou Medical University from January 2020 to April 2023 were enrolled. Inclusion criteria were a diagnosis of kidney disease (including chronic kidney disease, diabetic nephropathy, glomerulonephritis, etc.) and completion of fundus examinations. Patients with other severe systemic diseases (such as malignancies, autoimmune diseases) or ocular lesions due to other causes (such as trauma or surgical history) were excluded.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.2 Data Collection\u003c/b\u003e \u003c/p\u003e \u003cp\u003eCollected data included basic demographic information (such as sex and age), visual acuity, refraction, intraocular pressure, slit-lamp anterior segment examination, Scanning Laser Ophthalmoscope(SLO) and macular optical coherence tomography (OCT). Laboratory tests included serum creatinine, blood urea nitrogen, urinary protein, urinary N-acetyl-β-D-glucosaminidase (NAG), and urinary microalbumin. All ocular symptoms were evaluated and diagnosed by attending or senior ophthalmologists, while the type of kidney disease was diagnosed by attending or senior nephrologists. The estimated glomerular filtration rate (eGFR) was calculated using the 2021 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) Eq.\u0026nbsp;9.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.3 Statistical Analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eStatistical analyses were performed using IBM SPSS Statistics 25.0. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All quantitative data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Pearson correlation analysis was used to assess the relationships between ocular and renal symptoms. Ocular parameters included lens opacity, anterior segment findings, vitreous liquefaction and opacities, arteriovenous crossing changes, macular foveal reflex, retinal hemorrhage, and retinal exudates. Renal parameters included diabetic retinopathy, kidney disease, chronic renal failure, acute renal failure, chronic glomerulonephritis, uremia, and chronic kidney disease. Boxplot analysis (Mann-Whitney U test) was used to compare differences in renal function markers among different ocular disease groups. Furthermore, multivariate logistic regression was performed to assess the association between eGFR levels and DR, categorizing eGFR into three clinically relevant groups: \u0026ge;90, 60\u0026ndash;89, and \u0026lt;\u0026thinsp;60 ml / (min\u0026middot;1.73 m\u0026sup2;), with eGFR\u0026thinsp;\u0026ge;\u0026thinsp;90 ml/(min\u0026middot;1.73 m\u0026sup2;) as the reference. To control for confounding factors, age, hypertension, and hyperlipidemia were included as covariates in the regression model. Results are presented as odds ratios (OR) with 95% confidence intervals (CI), and a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Dataset Summary\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 641 patients were included in this study, with a mean age of 54.75 ± 16.16 years. Among them, 56.3% (n = 361) were male and 43.7% (n = 280) were female. The types of kidney disease among the patients were classified according to disease course as chronic kidney disease (CKD, stages 1–5) and acute kidney disease; and according to etiology as diabetic nephropathy, hypertensive nephropathy, obstructive nephropathy, membranous nephropathy, and chronic glomerulonephritis. The main types of fundus lesions included diabetic retinopathy, hypertensive retinopathy, retinal hemorrhage, macular edema, and retinal exudates. The general demographic and clinical characteristics of the patients are summarized in Table_1,\u0026nbsp;Figure_1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Odds Ratios for Kidney–Ocular Disease Associations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, we explored the associations between different types of kidney disease and ocular diseases, and quantified the strength of these associations by calculating odds ratio (OR). Significant correlations were observed between various ocular diseases and kidney diseases. Diabetic nephropathy was significantly associated with multiple ocular manifestations, including lens opacity, retinal hemorrhage, and macular edema. Chronic kidney disease was mainly associated with retinal hemorrhage, retinal exudates, and macular edema. The associations between different types of kidney disease and ocular manifestations varied: hypertensive nephropathy was primarily associated with retinal hemorrhage, while chronic glomerulonephritis was significantly associated with lens opacity, among others (Figure_2).\u003c/p\u003e\n\u003cp\u003e1. \u003cstrong\u003eDiabetic Nephropathy:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Patients with diabetic nephropathy had significantly higher risks of developing lens opacity (OR = 1.74, p \u0026lt; 0.05), retinal hemorrhage (OR = 5.87, p \u0026lt; 0.01), retinal exudates (OR = 4.22, p \u0026lt; 0.01), macular edema (OR = 2.63, p \u0026lt; 0.01), and vitreous opacity (OR = 1.64, p \u0026lt; 0.05) compared to those without diabetic nephropathy.\u003c/p\u003e\n\u003cp\u003e2. \u003cstrong\u003eChronic Kidney Disease:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Patients with chronic kidney disease had significantly higher risks of retinal hemorrhage (OR = 5.20, p \u0026lt; 0.01), retinal exudates (OR = 2.25, p \u0026lt; 0.01), and macular edema (OR = 4.93, p \u0026lt; 0.01) compared to those without chronic kidney disease.\u003c/p\u003e\n\u003cp\u003e3. \u003cstrong\u003eHypertensive Nephropathy:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Patients with hypertensive nephropathy had a significantly lower risk of retinal hemorrhage (OR = 0.49, p \u0026lt; 0.01) compared to those without hypertensive nephropathy.\u003c/p\u003e\n\u003cp\u003e4. \u003cstrong\u003eChronic Glomerulonephritis:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Patients with chronic glomerulonephritis had significantly lower risks of lens opacity (OR = 0.53, p \u0026lt; 0.05), retinal hemorrhage (OR = 0.46, p \u0026lt; 0.05), and retinal exudates (OR = 0.47, p \u0026lt; 0.05) compared to those without chronic glomerulonephritis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Renal Markers and Fundus Lesions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBoxplot analyses revealed significant differences in renal function markers among patients with different ocular disease statuses:\u003c/p\u003e\n\u003cp\u003e1. \u003cstrong\u003eeGFR Distribution:\u003c/strong\u003e\u003cbr\u003eThe eGFR values in the hypertensive retinopathy group (p \u0026lt; 0.01), retinal exudate group (p \u0026lt; 0.01), retinal hemorrhage group (p \u0026lt; 0.01), diabetic retinopathy group (p \u0026lt; 0.01), and macular edema group (p \u0026lt; 0.01) were all significantly lower than those in their respective control groups without these lesions, suggesting an association between ocular disease and renal dysfunction (Figure_3A).\u003c/p\u003e\n\u003cp\u003e2. \u003cstrong\u003eUrinary Microalbumin:\u003c/strong\u003e\u003cbr\u003eUrinary microalbumin levels were significantly higher in the retinal hemorrhage group compared to the non-hemorrhage group (p \u0026lt; 0.01), with the most pronounced difference observed in the retinal hemorrhage group. This suggests that combined assessment of urinary microalbumin and retinal hemorrhage may serve as an early warning indicator (Figure_3B).\u003c/p\u003e\n\u003cp\u003e3. \u003cstrong\u003eSerum Creatinine:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Serum creatinine levels were significantly higher in patients with hypertensive retinopathy (p \u0026lt; 0.01), retinal exudates (p \u0026lt; 0.01), and macular edema (p \u0026lt; 0.01) compared to those without retinal lesions, indicating a close relationship between renal impairment and these ocular diseases.\u003c/p\u003e\n\u003cp\u003e4. \u003cstrong\u003eUrinary Protein:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Urinary protein levels were significantly higher in patients with diabetic retinopathy (p \u0026lt; 0.05) and retinal exudates (p \u0026lt; 0.01) compared to control groups without these lesions, suggesting that glomerular permeability may be affected by ocular disease.\u003c/p\u003e\n\u003cp\u003e5. \u003cstrong\u003eBlood Urea Nitrogen:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Blood urea nitrogen levels were significantly higher in patients with retinal hemorrhage compared to those without hemorrhage (p \u0026lt; 0.05), indicating possible impairment of glomerular filtration function.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Ocular Signs Linked to eGFR Decline\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultivariate logistic regression analysis demonstrated that eGFR is a significant risk factor for the development of various ocular diseases. The relationship between declining eGFR and the odds ratios for ocular symptoms is shown in\u0026nbsp;Table_2\u0026nbsp;and\u0026nbsp;Figure_4.\u003c/p\u003e\n\u003cp\u003e1. \u003cstrong\u003eDeclining eGFR independently increases the risk of multiple ocular diseases.\u003c/strong\u003e For every 10 ml/(min·1.73 m²) decrease in eGFR, the risks of retinal hemorrhage, diabetic retinopathy (DR), macular edema, hypertensive retinopathy, and retinal exudates increased by 27%, 20%, 20%, 14%, and 12%, respectively, all of which were statistically significant (p \u0026lt; 0.05). This indicates that renal dysfunction significantly exacerbates the risk of ocular complications.\u003c/p\u003e\n\u003cp\u003e2. \u003cstrong\u003eThe extent of risk increase differs among ocular disease.\u003c/strong\u003e The risk increase was most pronounced for retinal hemorrhage (OR = 1.27), followed by DR (OR = 1.25) and macular edema (OR = 1.25), while the risk increases for retinal exudates and hypertensive retinopathy were relatively lower (OR = 1.12 and 1.20, respectively), suggesting that declining eGFR has a more pronounced impact on certain ocular diseases.\u003c/p\u003e\n\u003cp\u003e3. \u003cstrong\u003eA dose-dependent relationship exists between eGFR decline and ocular disease risk.\u003c/strong\u003e As also shown in the Appendix Table 2, with each fixed unit decrease in eGFR, the risks of multiple ocular diseases showed a consistent upward trend, and the 95% confidence intervals did not include 1 (p \u0026lt; 0.05), further supporting the clinical value of eGFR as a predictive marker for ocular complications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5\u0026nbsp;Diagnostic Performance of Renal Markers and Age for Ocular Signs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReceiver Operating Characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of eGFR, urinary microalbumin, and age in predicting the presence of various ocular signs (Figure 5). For predicting retinal hemorrhage, eGFR demonstrated the highest discriminatory ability (Area Under the Curve [AUC] = 0.67), followed by urinary microalbumin (AUC = 0.65). Similar analyses for macular edema revealed AUCs of 0.62 for both eGFR and urinary microalbumin. When predicting retinal exudates, the AUCs were 0.67 (eGFR), 0.65 (urinary microalbumin), and 0.45 (age).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eBased on a cohort of 641 CKD patients, this study is the first to comprehensively evaluate the association strength between serum creatinine, blood urea nitrogen, urinary protein, urinary microalbumin, and eGFR with retinal hemorrhage, exudates, macular edema, diabetic retinopathy, and hypertensive retinopathy. The results indicate that greater renal impairment increases the risk of fundus lesions, suggesting shared pathogenic mechanisms involving systemic microvascular disease, oxidative stress, and inflammatory pathways.\u003c/p\u003e \u003cp\u003e \u003cb\u003e4.1 Kidney\u0026ndash;Eye Disease Associations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study systematically elucidates the clinical association strength between different types of kidney disease and specific ocular diseases. Notably, diabetic nephropathy (DN) showed a particularly strong association with retinal hemorrhage (OR\u0026thinsp;=\u0026thinsp;5.87), retinal exudates (OR\u0026thinsp;=\u0026thinsp;4.22), and macular edema (OR\u0026thinsp;=\u0026thinsp;2.63), while CKD was strongly associated with retinal exudates (OR\u0026thinsp;=\u0026thinsp;2.25) and macular edema (OR\u0026thinsp;=\u0026thinsp;4.93).\u003c/p\u003e \u003cp\u003eThese findings not only confirm the shared pathological basis of the renal and ocular microvascular systems but also reveal the heterogeneity in the mechanisms by which different types of kidney disease drive ocular pathology. From a pathophysiological perspective, diabetic nephropathy and retinal disease share hyperglycemia-induced endothelial injury pathways. Advanced glycation end products (AGEs) activate oxidative stress and inflammatory responses, disrupting both the glomerular filtration and blood-retinal barriers \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, which may explain the strong association between DN and retinal hemorrhage.\u003c/p\u003e \u003cp\u003eRecent mechanistic studies provide further biological explanations: uremic toxins (such as indoxyl sulfate) accumulated in CKD patients can activate the ROS-NFκB pathway, damaging the blood-retinal barrier and directly leading to vascular leakage and hemorrhage \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, which mechanistically aligns with the high risk of retinal hemorrhage and macular edema observed in this study. Our findings indicated a significantly lower risk of retinal hemorrhage in patients with hypertensive nephropathy (OR\u0026thinsp;=\u0026thinsp;0.49, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) compared to the reference group. This unexpected protective association warrants further exploration. While systemic hypertension is a risk factor for retinal hemorrhage, it is plausible that patients specifically identified with hypertensive nephropathy in our cohort are subject to distinct management strategies (e.g., more intensive blood pressure control or specific antihypertensive classes) that could mitigate hemorrhagic risk. Alternatively, The relatively weaker association between hypertensive nephropathy and retinal hemorrhage (OR\u0026thinsp;=\u0026thinsp;0.49, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) may suggest its pathology may focus more on arteriolosclerosis than microvascular leakage. This is consistent with the longitudinal findings of Sabanayagam et al., who reported that retinal arteriolar narrowing independently predicts renal function decline \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, but its impact on hemorrhagic lesions may be buffered by hemodynamic compensatory mechanisms. In contrast, the negative associations observed between chronic glomerulonephritis (CGN) and lens opacity (OR\u0026thinsp;=\u0026thinsp;0.53, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), retinal hemorrhage (OR\u0026thinsp;=\u0026thinsp;0.46, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and retinal exudates (OR\u0026thinsp;=\u0026thinsp;0.47, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) may suggest that immune-mediated renal injury (such as complement activation or antibody deposition) affects the ocular microenvironment through unique pathways \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, indicating that immune regulation may counteract exudative processes.\u003c/p\u003e \u003cp\u003eClinical studies have shown that patients with diabetic retinopathy (DR) have an increased risk of developing diabetic nephropathy, and the incidence of retinal arteriolosclerosis is higher in patients with hypertensive nephropathy \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. These findings suggest that kidney and ocular diseases may share common pathophysiological mechanisms, such as microvascular disease, oxidative stress, and inflammatory responses \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, which may play a role in the development and progression of both conditions.\u003c/p\u003e \u003cp\u003e \u003cb\u003e4.2 eGFR Decline and Ocular Risk\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSystemic vascular endothelial dysfunction resulting from renal impairment may be an important underlying mechanism linking kidney and ocular diseases. Our results demonstrate a significant association between declining eGFR and the risk of various fundus lesions in CKD patients. Specifically, for every 10 ml/(min\u0026middot;1.73 m\u0026sup2;) decrease in eGFR, the risks of retinal hemorrhage, diabetic retinopathy, macular edema, hypertensive retinopathy, and retinal exudates increased by 27%, 25%, 20%, 20%, and 12%, respectively. This finding is highly consistent with large-scale epidemiological studies, such as the CRIC Study by Juan E. Grunwald et al. (n\u0026thinsp;=\u0026thinsp;1904), which found that patients with GFR\u0026thinsp;\u0026lt;\u0026thinsp;30 ml/min/1.73 m\u0026sup2; had a threefold increased risk of retinopathy \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAs renal function declines, the kidneys are less able to clear metabolic waste and toxins, leading to their accumulation, which in turn induces oxidative stress and inflammation, damaging systemic vascular endothelial cells \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. As part of the systemic microvascular system, retinal vessels are similarly affected \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, resulting in retinal microvascular disease. Thus, a decrease in eGFR not only reflects the degree of renal impairment but may also indirectly indicate the extent of systemic vascular endothelial dysfunction \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, closely linking it to the risk of fundus lesions.\u003c/p\u003e \u003cp\u003eOur forest plot analysis further showed that specific fundus phenotypes, such as retinal exudates, retinal hemorrhage, and macular edema, were significantly different in relation to eGFR, serum creatinine, blood urea nitrogen, urinary protein, and urinary microalbumin (Figure_5). This suggests that renal dysfunction may increase the risk of retinal lesions and macular edema by affecting systemic vascular health. As a key indicator of renal function, eGFR decline is closely associated with increased risk of multiple ocular diseases. Our quantitative analysis found that for every 10 ml/(min\u0026middot;1.73 m\u0026sup2;) decrease in eGFR, the risks of retinal hemorrhage, macular edema, hypertensive retinopathy, and retinal exudates increased by 27%, 20%, 14%, and 12%, respectively. This provides important quantitative evidence for clinicians, highlighting that monitoring renal function is crucial for managing kidney disease and for early screening and intervention of ocular diseases. In particular, patients with declining renal function should undergo more frequent fundus examinations to facilitate early detection and intervention of ocular disease.\u003c/p\u003e \u003cp\u003e \u003cb\u003e4.3 Ocular Signs as Early Renal Indicators\u003c/b\u003e \u003c/p\u003e \u003cp\u003eBy analyzing the distribution differences of various renal function markers in the presence of different fundus lesions, this study reveals the potential early warning value of five ocular manifestations\u0026mdash;retinal exudates, retinal hemorrhage, macular edema, lens opacity, and vitreous opacity\u0026mdash;for different renal function markers. Our results suggest that the presence of retinal exudates, retinal hemorrhage, or macular edema is associated with significantly lower eGFR compared to patients without these ocular symptoms, indicating a strong correlation between multiple types of retinal microvascular injury and renal function decline, whereas lens opacity and vitreous opacity do not reflect renal function status. This finding is consistent with the results of the multicenter cohort study by Juan E. Grunwald et al. \u003csup\u003e26\u003c/sup\u003e. Anatomically, since the kidney and retina develop during the same embryonic stage, the retinal and glomerular microvasculature share significant similarities in structure, function, and pathological mechanisms \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, including common regulatory pathways and the renin-angiotensin-aldosterone system (RAAS) \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. These lines of evidence suggest that the eye-kidney association is largely based on their shared microvascular architecture, and our study further demonstrates that retinal lesions can serve as indicators of eGFR decline, providing a foundation for future research on eye-kidney comorbidity.\u003c/p\u003e \u003cp\u003eOur findings indicate that different retinal signs may reflect abnormalities in different renal function markers. For example, patients with retinal hemorrhage had significantly higher blood urea nitrogen and urinary microalbumin levels. Urinary microalbumin is an early marker of glomerular filtration membrane damage and systemic microvascular endothelial injury; its elevation indicates glomerular microvascular disease \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. In this study, the difference in urinary microalbumin was most pronounced in the retinal hemorrhage group. As a severe manifestation of retinal microvascular disease, retinal hemorrhage may share a common pathophysiological basis with elevated urinary microalbumin. Therefore, combined assessment of urinary microalbumin and retinal hemorrhage may facilitate early identification of eye-kidney comorbidity. In patients with kidney disease, non-invasive and convenient retinal examination may indirectly reflect the type of renal impairment, thereby enhancing the comprehensive management of kidney disease in clinical practice.\u003c/p\u003e \u003cp\u003e \u003cb\u003e4. 4 Limitations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study provides new evidence for the association between kidney disease and ocular disease, particularly in quantifying the relationship between renal function markers and fundus lesions. However, several limitations should be noted. First, as a cross-sectional study, causality between renal function decline and ocular disease cannot be established. Second, being a single-center study, the generalizability of the results may be limited. Additionally, the study did not include dynamic data on changes in renal function markers, precluding further exploration of the impact of renal function changes on the progression of ocular disease. Future research should employ longitudinal designs and include data from multiple centers to further investigate the pathophysiological mechanisms linking kidney and ocular diseases.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study reveals the multi-layered pathological nature of the association between declining renal function and ocular disease, analyzes the associations between different types of kidney disease and ocular symptoms, and quantifies the specific risks of various ocular lesions associated with renal function decline. These findings provide new insights for the clinical management of patients with kidney disease, may enhance clinical awareness of eye-kidney comorbidity, and offer further clinical evidence for future research on the eye-kidney connection.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e \u003cp\u003e The study was approved by the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University (Approval No. : ES-2024-157-01), and all procedures adhered to the principles of the Declaration of Helsinki.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eDisclosure of interest\u003c/h2\u003e \u003cp\u003eThe authors report no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eClinical trial number\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConsent to participate\u003c/h2\u003e \u003cp\u003e This retrospective case analysis has obtained ethical approval from the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University (Approval No.: ES-2024-157-01). In accordance with the approval decision of this ethics committee, informed consent for this study has been waived.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003e1. Medical Science and Technology Research Foundation of Guangdong Province(A2024147);\u003c/p\u003e \u003cp\u003e2. Guangzhou Science and Technology Bureau Basic Research Program Municipal School (Institute) Enterprise joint funding Project (SL2024A03J01543)\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eYuran Chen: Writing-Original Draft, Investigation, Data Curation, Project administration. Min Hu: Writing-Review \u0026amp; Editing, Methodology, Formal analysis, Data Curation, Visualization. Weiwei Dai: Writing-Review\u0026amp; Editing, Conceptualization, Methodology. Chaokui Huo: Writing- Review \u0026amp; Editing, Conceptualization, Methodology. Wai Cheng Iao: Writing-Review \u0026amp; Editing, Conceptualization, Methodology. Huayin Chen: Writing-Review \u0026amp; Editing, Investigation. Jianmei Lu: Writing-Review \u0026amp; Editing, Investigation Hao Cheng: Writing-Review \u0026amp; Editing, Conceptualization, Methodology, Supervision, Resources. Danmin Cao: Writing-Review \u0026amp; Editing, Conceptualization, Methodology, Supervision, Resources, Funding acquisition.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from the corresponding author, Cao DM, upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJager KJ, Kovesdy C, Langham R, Rosenberg M, Jha V, Zoccali C. A single number for advocacy and communication-worldwide more than 850 million individuals have kidney diseases. 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Understanding the Clinical Relationship Between Diabetic Retinopathy, Nephropathy, and Neuropathy: A Comprehensive Review. Cureus. 2024;16(3):e56674. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7759/cureus.56674\u003c/span\u003e\u003cspan address=\"10.7759/cureus.56674\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Published 2024 Mar 21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaini DC, Kochar A, Poonia R. Clinical correlation of diabetic retinopathy with nephropathy and neuropathy. Indian J Ophthalmol. 2021;69(11):3364\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/ijo.IJO_1237_21\u003c/span\u003e\u003cspan address=\"10.4103/ijo.IJO_1237_21\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang L, Wang JY, Chen C, et al. 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Clin J Am Soc Nephrol. 2010;5(5):867\u0026ndash;73. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2215/CJN.08271109\u003c/span\u003e\u003cspan address=\"10.2215/CJN.08271109\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKannenkeril D, Frost S, Nolde JM, et al. Microvascular changes at different stages of chronic kidney disease. J Clin Hypertens (Greenwich). 2021;23(2):309\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/jch.14138\u003c/span\u003e\u003cspan address=\"10.1111/jch.14138\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrunwald JE, Alexander J, Ying GS, et al. Retinopathy and chronic kidney disease in the Chronic Renal Insufficiency Cohort (CRIC) study. Arch Ophthalmol. 2012;130(9):1136\u0026ndash;44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/archophthalmol.2012.1800\u003c/span\u003e\u003cspan address=\"10.1001/archophthalmol.2012.1800\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoyal JL, Gupta A, Gandhi P. Ocular manifestations in renal diseases. Indian J Ophthalmol. 2023;71(8):2938\u0026ndash;43. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/IJO.IJO_3234_22\u003c/span\u003e\u003cspan address=\"10.4103/IJO.IJO_3234_22\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBodaghi B, Massamba N, Izzedine H. The eye: a window on kidney diseases. Clin Kidney J. 2014;7(4):337\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ckj/sfu073\u003c/span\u003e\u003cspan address=\"10.1093/ckj/sfu073\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilkinson-Berka JL, Agrotis A, Deliyanti D. The retinal renin-angiotensin system: roles of angiotensin II and aldosterone. Peptides. 2012;36(1):142\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.peptides.2012.04.008\u003c/span\u003e\u003cspan address=\"10.1016/j.peptides.2012.04.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarrah TE, Dhillon B, Keane PA, Webb DJ, Dhaun N. The eye, the kidney, and cardiovascular disease: old concepts, better tools, and new horizons. Kidney Int. 2020;98(2):323\u0026ndash;42. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.kint.2020.01.039\u003c/span\u003e\u003cspan address=\"10.1016/j.kint.2020.01.039\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh A, Satchell SC. Microalbuminuria: causes and implications. Pediatr Nephrol. 2011;26(11):1957\u0026ndash;65. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00467-011-1777-1\u003c/span\u003e\u003cspan address=\"10.1007/s00467-011-1777-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2011 Feb 8. PMID: 21301888; PMCID: PMC3178015.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrasad RM, Bali A, Tikaria R. Microalbuminuria. StatPearls. Volume 30. Treasure Island (FL): StatPearls Publishing; 2023.\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable_1. Demographic and Clinical Characteristics of the Study Population\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"105%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 23px;\"\u003e\n \u003cp\u003eDemographics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e280 (43.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 23px;\"\u003e\n \u003cp\u003eRenal observations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eDiabetic Nephropathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e122 (19.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eHypertensive Nephropathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e103 (16.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eObstructive Nephropathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e2 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eMembranous Nephropathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e3 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eChronic Glomerulonephritis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e74 (11.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 23px;\"\u003e\n \u003cp\u003eOphthalmic observations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eLens Opacities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e379 (60.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eVitreous Opacities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e430 (68.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eMacular Edema\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e35 (5.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eRetinal Hemorrhage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e201 (31.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eRetinal Exudates\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e175 (27.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 23px;\"\u003e\n \u003cp\u003eDemographics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e55.03 \u0026plusmn; 16.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" rowspan=\"6\" style=\"width: 23px;\"\u003e\n \u003cp\u003eBiometrics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eUrinary Microalbumin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e1334.16 \u0026plusmn; 1487.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eUrinary Protein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e2.68 \u0026plusmn; 3.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eUrinary NAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e13.16 \u0026plusmn; 21.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eUrinary Beta2-Microglobulin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e3.23 \u0026plusmn; 6.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eBlood Urea Nitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e16.51 \u0026plusmn; 23.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 36px;\"\u003e\n \u003cp\u003eeGFR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 40px;\"\u003e\n \u003cp\u003e35.20 \u0026plusmn; 33.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable_2.Association Between Declining eGFR and Odds Ratios for Ocular Symptoms\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"634\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 102px;\"\u003e\n \u003cp\u003eLens Opacity\u0026nbsp;\u003cbr\u003e\u0026nbsp;(n=380)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 100px;\"\u003e\n \u003cp\u003eVitreous Opacities\u0026nbsp;\u003cbr\u003e\u0026nbsp;(n=434)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 102px;\"\u003e\n \u003cp\u003eMacular Edema\u003cbr\u003e\u0026nbsp; (n=35)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 109px;\"\u003e\n \u003cp\u003eRetinal Hemorrhage\u003cbr\u003e\u0026nbsp; (n=203)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 102px;\"\u003e\n \u003cp\u003eRetinal Exudates\u003cbr\u003e\u0026nbsp; (n=175)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eeGFR\u003cbr\u003e\u0026nbsp;ml/(min・1.73 m\u0026sup2;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eCount\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eOR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eOR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eOR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eOR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eOR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026gt;90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e60~90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.34 (0.61, 2.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.469\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1.17 (0.57, 2.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003e0.666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003einf*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e3.24 (1.01, 10.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1.92 (0.74, 4.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e0.179\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026lt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.91 (0.48, 1.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1.31 (0.73, 2.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003e0.365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003einf*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e8.78 (3.11, 24.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e3.06 (1.35, 6.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e35.1 \u0026plusmn; 32.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.91 (0.76, 1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1.02 (0.87, 1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003e0.779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.84 (1.15, 2.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e2.16 (1.73, 2.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1.44 (1.18, 1.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Odds ratios could not be estimated (denoted by inf) due to zero events observed in a comparison group\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Kidney disease, Ocular disease, Glomerular filtration rate, Correlation, Clinical data, Microangiopathy","lastPublishedDoi":"10.21203/rs.3.rs-9190108/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9190108/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eTo investigate the association between renal function markers and fundus damage in patients with chronic kidney disease(CKD).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eBasic demographic information, renal function parameters, and data related to fundus lesions were collected. The correlations between kidney disease and ocular disease, as well as the associations between renal function markers and various ocular pathologies, were analyzed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAnalysis of odds ratios (OR) between ocular and renal variables revealed a significantly increased risk of ocular diseases in patients with kidney disease, with particularly elevated risks for retinal hemorrhage and macular edema. Boxplot analyses further demonstrated that specific fundus phenotypes, such as retinal exudates, retinal hemorrhage, and macular edema, were significantly associated with markers of renal impairment, including estimated glomerular filtration rate (eGFR), serum creatinine, blood urea nitrogen, urinary protein, and urinary microalbumin. Further analysis of eGFR data indicated that for every 10 ml/(min\u0026middot;1.73 m\u0026sup2;) decrease in eGFR, the risks of retinal hemorrhage, diabetic retinopathy, macular edema, hypertensive retinopathy, and retinal exudates increased by 27%, 25%, 20%, 20%, and 12%, respectively.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003ePatients with kidney disease have a significantly increased risk of developing ocular diseases, particularly retinal hemorrhage and macular edema. There are significant differences in specific fundus phenotypes according to markers of renal impairment, suggesting that renal dysfunction may indirectly elevate the risk of retinal lesions and macular edema by affecting systemic vascular health. Moreover, a decline in eGFR is closely associated with increased risks of various ocular diseases.\u003c/p\u003e","manuscriptTitle":"Renal Function Markers Predict Risk of Specific Fundus Lesions in CKD: A Cross- Sectional Risk-Stratification Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-10 06:34:44","doi":"10.21203/rs.3.rs-9190108/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"068b7851-0dae-4012-a912-a7e565bf2ebd","owner":[],"postedDate":"April 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T06:38:37+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-10 06:34:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9190108","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9190108","identity":"rs-9190108","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}