High Levels of Serum Uric Acid are Associated with Microvascular Complications in Patients with Long-term Diabetes

High Levels of Serum Uric Acid are Associated with Microvascular Complications in Patients with Long-term Diabetes | 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 High Levels of Serum Uric Acid are Associated with Microvascular Complications in Patients with Long-term Diabetes Hanying Wang, Liping Gu, Yuhang Ma, Xindan Xing, Yuan Qu, Xin Shi, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4757783/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Mar, 2025 Read the published version in Diabetology & Metabolic Syndrome → Version 1 posted 10 You are reading this latest preprint version Abstract Aims To assess the association between serum uric acid (SUA) level and the prevalence of diabetic retinopathy (DR) and chronic kidney disease (CKD) in patients with long-term diabetes. Methods A cross-sectional analysis was conducted involving diabetic patients from Shanghai General hospital during October 2018 and October 2021. Participants underwent measurements of SUA, renal function test and DR assessments via fundus photography. Multivariable ordinal logistic regression models assessed odd ratios (ORs) and 95% confidence intervals (95% CIs) for the progression of DR and CKD. Receiver operating characteristics (ROC) curves identified SUA thresholds, categorizing participants into low and high SUA groups. Results Among the 1015 patients with diabetes, SUA levels were higher in individuals with more sever CKD (p < 0.001, compared with CKD1) and those with vision-threatening diabetic retinopathy (VTDR) (p = 0.019, compared with no diabetic retinopathy (NDR)). Adjustments for potential confounders revealed that each 1 µmol/L increase in SUA was associated with an OR of 1.002 (95% CI: 1.001–1.004) for DR and 1.008 (95% CI: 1.006–1.011) for CKD. The risk of DR and CKD was elevated when SUA levels surpassed 354.0 µmol/L (95% CI: 318.9–393.2) and 361.0 µmol/L (95% CI: 339.2–386.3), respectively, with ORs of 1.571 (95% CI: 1.136–2.099, P = 0.006) for DR and 1.395 (95% CI: 1.033–1.885, P = 0.030) for CKD. Gender-specific analyses also demonstrated a positive correlation between higher SUA levels and the incidence of DR and CKD in both males and females. Conclusions Elevated SUA levels are independently associated with increased risks of DR and CKD, highlighting the importance of managing SUA levels in the patients with diabetes. serum uric acid diabetic retinopathy chronic kidney disease diabetes mellitus Figures Figure 1 Figure 2 Introduction Diabetes mellitus (DM), a chronic metabolic disorder characterized by elevated blood glucose levels, has seen a notable increase in prevalence, making it a considerable public health concern. Recent data from the World Health Organization (WHO) suggest that an estimated 462 million individuals globally are living with type 2 diabetes.[ 1 ] Both type 1 and type 2 diabetes are associated with cardiovascular, renal, ocular and neurological complications.[ 2 ] Diabetic retinopathy (DR) and diabetic nephropathy (DN) are common complications in patients with diabetes and the most frequent causes of blindness and death.[ 3 ] Both of them are microvascular injuries caused by hyperglycemia, thus share some common metabolic alterations that contribute to the pathogenesis of diabetic complications. Several research suggested the development and progression of DN and retinopathy are influenced not just by hyperglycemia but also by factors including age, smoking, obesity, hypertension, dyslipidemia, and inflammation.[ 4 ] Therefore, identifying additional contributors to the pathophysiological mechanisms underlying diabetic complications is crucial. Uric acid (UA) is the degradation product of purines, and hyperuricemia is highly prevalent in patients with diabetes,[ 5 ] due to impaired renal function resulting in decreased renal excretion of UA .[ 6 ] Serum uric acid (SUA) has been recently recognized as a risk factor for both macrovascular and microvascular diseases. On the one hand, previous studies[ 7 , 8 ] have suggested a potential link between elevated UA levels and the development and progression of diabetes. On the other hand, high levels of UA can also contribute to inflammation, oxidative stress, and apoptosis,[ 9 ] potentially playing a significant role in the development of diabetic complications. Several clinical studies have shown an association between elevated UA levels and DN.[ 10 , 11 ] However, clinical trials have yielded inconsistent findings regarding the link between UA and diabetic retinopathy (DR).[ 12 – 14 ] Our previous clinical study,[ 15 ] a metabolomics-based investigation, showed a significant increase of uric acid levels in vitreous samples from patients with proliferative diabetic retinopathy (PDR) compared to non-diabetic controls (UA intensity, 694.2 vs 475.8, p < 0.01). This result suggests a potential involvement of UA in the development of DR. The elevated levels of UA in the vitreous may be due to both local metabolic changes within the retina and a potential increase in systemic UA levels. Although alterations in vitreous uric acid levels exhibit more relevant to disease mechanisms, the assessment of SUA remains more suitable for disease prevention and management. Therefore, we conducted a cross-sectional study in patients with diabetes for at least 5 years to better understand the relationship between SUA and the occurrence of diabetic microvascular complications. Method Patients The cross-sectional study recruited patients with diabetes (including both Type 1 and Type 2 diabetes mellitus), who were from the Department of Endocrinology at Shanghai General Hospital, China between October 2018 and October 2021. Diabetes was determined through the assessment of plasma glucose levels, specifically with criteria such as fasting blood glucose (FBG) ≥ 7.0 mmol/L or 2-hour plasma glucose (2h PG) exceeding 11.1 mmol/L during a 75 g oral glucose tolerance test.[ 16 ] Patients were included if diagnosed with diabetes for > 5 years, with available SUA data and fundus photography. We excluded patients with gestational diabetes or diabetes induced by medication use or other endocrine diseases. Finally, a total of 1015 subjects were included in this study. Written informed consent was obtained from each participant before the study began, and the study was approved by the Ethics Committee of Shanghai General Hospital. Diagnose of Diabetic retinopathy (DR) For each eye of each subject, one standard color fundus image was obtained with 45° field of view, non-stereoscopic and macula-centered. A modified grading scale reported previously was used for the classification of DR and diabetic macular edema (DME).[ 17 ] Patients are grouped according to the degree of the eye with the worse grade when the grades of both eyes were inconsistent. Then the patients were grouped into non-DR (NDR), non-vision threatened diabetic retinopathy (non-VTDR) which including mild and moderate non proliferative diabetic retinopathy (NPDR), and VTDR which including severe NPDR, PDR and DME. All fundus images were assessed by the Ophthalmology Center of the Shanghai General Hospital (National Clinical Research Center for Eye Diseases). Demographic data and laboratory measurements In the survey, patients were subjected to a standard inquiry regarding their medical history, physical examination, and laboratory tests. Various demographic information including age, sex, height, weight, blood pressure, smoking or alcohol consumption habits were recorded. Additionally, their medical history encompassing both microvascular and macrovascular complications along with treatment approaches including medications for hypertension and diabetes were documented. In this study, demographic information of the patients including age, sex, height, weight, blood pressure, history of smoking and alcohol consumption, medical history and treatment were obtained. Blood samples were obtained from the patients’ antecubital vein at overnight fasting for biochemical measurement, including lipid profile (total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C)), blood urea nitrogen (BUN), serum creatinine, SUA, fasting blood glucose and postprandial blood glucose. Urine samples were collected to test the levels of urinary albumin–creatinine ratio (UACR). The estimated glomerular filtration rate (eGFR) is used to estimate kidney function and determine chronic kidney disease (CKD) staging, using the following formula: eGFR [mL/ (min × 1.73 m 2 )] = 194 × Cr − 1.094 × age − 0.287 (×0.739 for female patients).[ 18 ] Statistical analysis Multiple imputation was conducted in this study to impute missing values using the MI procedure in SPSS software (version 26.0.0.2; SPSS, Chicago, IL, USA). UA levels ≥ 7.0 mg/dL in men and ≥ 6 mg/dL in women were defined as hyperuricemia. All continuous variables were non-normally distributed and expressed as median plus interquartile range (IQR). Differences between groups were evaluated using nonparametric tests. Categorical variables were presented as numbers (proportions) and comparisons between groups were made using the chi-square test. Correlations between UA levels and other measures were evaluated by Pearson's correlation analysis and linear regression analysis. To identify independent risk factors associated with the prevalence of DR and CKD, orderly logistic regression analyses were performed. Variables known or thought to be associated with DR or CKD were selected as covariates in statistical models. Results were presented as odds ratios (ORs) and 95% confidence intervals (95% CIs), considering P values less than 0.05 as statistically significant. Receiver operating characteristics (ROC) curves and SUA cutoff points were derived to obtain UA groupings (low SUA group and high SUA group). Statistical analyses were performed using SPSS software and GraphPad Prism (version 9.5.0; GraphPad Software Inc., San Diego, CA, USA). The 95% CIs of SUA cutoff points were computed in Python (version 3.12). Results Baseline characteristics Baseline characteristics of the study participants are depicted in Table 1. A total of 1015 participants were included, comprising 721 patients with NDR (71.03%), 241 with non-VTDR (23.7%), and 53 diagnosed with VTDR (5.2%). The mean baseline SUA was 315.1, 322.5 and 356.0 µmol/L, respectively. Comparing individuals without DR, those with VTDR exhibited higher baseline SUA levels (315.1 µmol/L vs. 356.0 µmol/L; P = 0.019) (Fig. 1 ). Observations also indicate an increased prevalence of hyperuricemia among individuals at DR (14% vs. 19%, P < 0.05). The duration of diabetes (P = 0.002), sex distribution (P = 0.049) and the level of HbA1c (P < 0.001) differ between the groups. The indicators that also present inter-group differences include glycated albumin, BUN, HDL- C and ALB. There was no statistically significant difference in BMI between the two groups (P = 0.306). Table 1 Characteristics of the population grouped by diabetic retinopathy NDR (n=721) Non-VTDR (n=241) VTDR (n=53) p-value Age (year) 60.0 (13.0) 57.0 (14.0) 56.0 (18.0) <0.001 Eye (right, %) 343 (47.6) 111 (46.1) 22 (41.5) 0.664 Sex (Male, %) 401 (55.6) 155 (64.3) 33 (62.3) 0.049 duration(months) 122.0 (97.0) 131.0 (88) 157.0 (136) 0.002 BMI (kg/m2) 24.60 (4.25) 24.90 (4.20) 24.90 (4.45) 0.306 SBP (mmHg) 127.0 (21.0) 126.0 (20.0) 126.0 (26.0) 0.766 DBP (mmHg) 76.0 (12.0) 78.0 (16.0) 78.0 (13.0) 0.441 BUN (mmol/L) 5.52 (2.01) 5.52 (2.35) 6.43 (3.20) 0.003 SUA (umol/L) 315.1 (121.0) 322.5 (120.0) 356.0 (129.9) 0.047 Normal (n, %) 620 (86.0) 200 (83.0) 38 (71.7) 0.016 High (n, %) 101 (14.0) 41 (17.0) 15 (28.3) Scr (μmol/L) 59.0 (20.7) 58.8 (23.2) 65.4 (27.4) 0.055 eGFR (mL/min/1.73m2) 100.64 (15.87) 104.27 (20.89) 101.99 (24.02) 0.006 >120 86 (11.9) 42 (17.4) 9 (17.0) 0.016 90-120 517 (71.7) 165 (68.5) 29 (54.7) <89 119 (16.5) 34 (14.1) 15 (28.3) TC (mmol/L) 4.78 (1.63) 4.89 (1.77) 4.76 (2.30) 0.332 TG (mmol/L) 1.40 (1.00) 1.58 (1.10) 1.63 (1.10) 0.271 HDL-c(mmol/L) 1.06 (0.39) 1.01 (0.35) 1.00 (0.34) 0.018 LDL-c(mmol/L) 2.73 (1.33) 2.83 (1.26) 2.89 (1.61) 0.410 ALB (g/L) 44.80 (5.85) 44.40 (6.10) 42.30 (8.65) <0.001 HbA1c (%) 7.80 (2.20) 8.70 (2.85) 8.90 (2.90) <0.001 <7 (n, %) 221 (30.7) 51 (21.2) 10 (18.9) <0.001 7-9 (n, %) 314 (43.6) 89 (36.9) 17 (32.1) (n, %) 186 (25.8) 101 (41.9) 26 (49.1) Glycated albumin 19.47 (7.65) 22.50 (8.46) 24.22 (10.27) <0.001 0h-PG (mmol/L) 7.79 (3.13) 8.43 (3.18) 7.89 (4.32) 0.022 1h-PG (mmol/L) 13.26 (5.31) 12.84 (6.31) 11.05 (7.93) 0.056 2h-PG (mmol/L) 13.89 (6.71) 13.48 (7.39) 11.73 (9.36) 0.189 UACR 14.23 (29.87) 18.14 (54.52) 74.86 (365.21) <0.001 Normal (n, %) 517 (71.7) 155 (64.3) 21 (39.6) 300 (n, %) 41 (5.7) 26 (10.8) 16 (30.2) CKD (n, %) 194 (26.9) 85 (35.3) 33 (62.3) <0.001 CKD1 (n, %) 143 (19.8) 66 (27.4) 22 (41.5) <0.001 CKD2 (n, %) 38 (5.3) 10 (4.1) 8 (15.1) CKD3 (n, %) 13 (1.8) 9 (3.7) 3 (5.7) Previous history Hypertension 354 (49.1) 114 (47.3) 29 (54.7) 0.786 smoking 271 (37.6) 116 (48.1) 21 (39.6) 0.015 Drinking 325 (45.1) 120 (49.8) 24 (45.3) 0.441 Dyslipidemia 190 (26.4) 62 (25.7) 18 (34.0) 0.668 Coronary Heart Disease 63 (8.7) 18 (7.5) 6 (11.3) 0.790 Stroke 35 (4.9) 11 (4.6) 4 (7.5) 0.799 SUA: Serum Uric Acid; BMI: Body Mass Index; SBP: Systolic Blood Pressure; DBP: Diastolic Blood Pressure; BUN: Blood Urea Nitrogen; Scr: Serum Creatinine; eGFR: Estimated Glomerular Filtration Rate; TC: Total Cholesterol; TG: Triglycerides; HDL-c: High-Density Lipoprotein Cholesterol; LDL-c: Low-Density Lipoprotein Cholesterol; ALB: Albumin; HbA1c: Hemoglobin A1c; PG: Plasma Glucose; DR: Diabetic Retinopathy; NDR: Non-Diabetic Retinopathy; VTDR: Vision-Threatening Diabetic Retinopathy; CKD: Chronic Kidney Disease; CKD1: Stage 1 CKD; CKD2: Stage 2 CKD; CKD3: Stage 3 CKD Subsequently, we categorized all patients into three groups based on CKD staging (Table S1 ). Compared to the CKD 1 group, patients with CKD 2&3 exhibited significantly higher SUA levels (314.2 ± 134.3 µmol/L vs 362.9 ± 144.5 µmol/L, p < 0.001; 314.2 ± 134.3µmol/L vs 359.1 ± 173.2 µmol/L, p < 0.001, respectively). An analysis of diagnosed hyperuricemia proportions within each group revealed a higher prevalence of hyperuricemia among individuals in advanced CKD stages (12.6% vs 30.0%, p < 0.001; 12.6% vs 30.0%, p < 0.001, respectively). Several parameters exhibit significant differences between patients at different stages of CKD, including age, the duration of diabetes, DBP, ALB, BUN, Scr, eGFR, 0h-PG and the prevalence of hypertension. SUA levels are independent risk factors for both DR and CKD Upon examination of SUA as a continuous variable, an orderly logistic regression analysis revealed that SUA was an independent risk factor for the progression of both DR and CKD (Fig. 2 ). After adjusting for sex, age, diabetic duration, smoking history, HDL-C, ALB, and HbA1c, the risk factors for DR progression were high SUA (OR: 1.002, 95% CI: 1.001–1.004), longer duration of DM (OR, 1.005; 95% CI = 1.125–1.310; p < 0.001), younger age (OR, 0.959; 95% CI = 0.945–0.972; p < 0.001), low ALB (OR, 0.951; 95% CI = 0.921–0.981; p = 0.02), and high HbA1c (OR, 1.214; 95% CI = 1.125–1.310; p < 0.001). The study found that independent risk factors for CKD, after multivariate adjustments, included high SUA levels (OR: 1.008, 95% CI: 1.006–1.011), low Hb (OR, 0.977; 95% CI = 0.965–0.989; p < 0.001), and older age (OR, 1.155; 95% CI = 1.121–1.188; p < 0.001). ROC curves and ideal SUA cutoff for prediction of DR and CKD In order to determine clinically meaningful SUA thresholds for predicting the occurrence of DR and CKD, we utilized ROC curves to obtain cutoffs to optimize both sensitivity and specificity (Table 3 ). To discriminate DR or CKD from patients with diabetes, the average cutoff values for SUA in general population were 354.0 umol/L (95% CI: 318.9-393.2) and 361.0 umol/L (95% CI: 339.2-386.3), respectively. Table 2 Results of receiver operating characteristic curve identifying the threshold of serum uric acid for DR and CKD Outcomes Population Cut off points, umol/L 95% CIs AUC Sensitivity Specificity DR Entire 354.0 318.9–393.2 0.53 0.42 0.67 Male 355.1 304.5–408.9 0.51 0.51 0.56 Female 352.1 286.5–420.4 0.52 0.28 0.79 CKD Entire 361.0 339.2–386.3 0.55 0.41 0.71 Male 361.0 330.4–394.8 0.56 0.52 0.62 Female 353.6 310.8 -400.5 0.55 0.30 0.83 DR: Diabetic Retinopathy, CKD: Chronic Kidney Disease, AUC: area under the curve, 95% CIs: 95% confidence intervals Table 3 Characteristics of the entire population grouped according to the identified thresholds for a risk of DR Group Low SUA High SUA p-value SUA range (median) 100.0-354.1 (280.1) 354.1–986.0 (408.7) Number of subjects 650 365 Male (%) 317 (48.8) 272 (74.5) < 0.001 Age (year) 60.0 (13.0) 58.0 (15.0) 0.002 Duration (months) 124.0 (97.0) 122.0 (85) 0.101 BMI (kg/m 2 ) 24.20 (4.40) 25.20 (4.11) < 0.001 SBP (mmHg) 126.0 (22.0) 130.0 (21.0) 0.002 DBP (mmHg) 76.0 (12.0) 78.0 (14.0) < 0.001 BUN (mmol/L) 5.50 (2.05) 5.70 (2.47) 0.001 Scr (µmol/L) 54.6 (19.12) 66.7 (20.8) < 0.001 eGFR (mL/min/1.73m 2 ) 102.44 (15.45) 97.69 (18.91) < 0.001 TC (mmol/L) 4.79 (1.71) 4.86 (1.65) 0.167 TG (mmol/L) 1.38 (0.90) 1.72 (1.30) < 0.001 HDL - c (mmol/L) 1.09 (0.41) 0.98 (0.30) < 0.001 LDL - c (mmol/L) 2.72 (1.35) 2.86 (1.30) 0.068 ALB (g/L) 44.10 (6.02) 45.30 (5.90) 0.001 HbA1c (%) 8.00 (2.40) 7.70 (2.30) 0.014 Glycated albumin 20.96 (8.74) 19.25 (7.60) < 0.001 0h - PG (mmol/L) 8.10 (3.42) 7.71 (2.95) 0.132 1h - PG (mmol/L) 13.31 (6.17) 12.85 (4.91) 0.481 2h - PG (mmol/L) 14.01 (7.46) 13.49 (6.22) 0.326 DR 169 (26.0) 125 (34.2) 0.005 NDR 481 (74.0) 240 (65.8) 0.086 Non-VTDR 143 (22.0) 98 (26.8) 0.299 VTDR 26 (4.0) 27 (7.4) 0.015 CKD 192 (29.5) 144 (39.5) 0.001 CKD1 (%) 146 (22.5) 96 (26.3) 0.205 CKD2 (%) 26 (4.0) 32 (8.8) 0.003 CKD3 (%) 12 (1.8) 13 (3.6) 0.091 Previous history Hypertension 300 (46.2) 197 (54.0) 0.021 Smoking 139 (21.4) 133 (36.4) < 0.001 Alcohol use 181 (27.8) 146 (40.0) < 0.001 SUA: Serum Uric Acid; BMI: Body Mass Index; SBP: Systolic Blood Pressure; DBP: Diastolic Blood Pressure; BUN: Blood Urea Nitrogen; Scr: Serum Creatinine; eGFR: Estimated Glomerular Filtration Rate; TC: Total Cholesterol; TG: Triglycerides; HDL-c: High-Density Lipoprotein Cholesterol; LDL-c: Low-Density Lipoprotein Cholesterol; ALB: Albumin; HbA1c: Hemoglobin A1c; PG: Plasma Glucose; DR: Diabetic Retinopathy; NDR: Non-Diabetic Retinopathy; VTDR: Vision-Threatening Diabetic Retinopathy; CKD: Chronic Kidney Disease; CKD1: Stage 1 CKD; CKD2: Stage 2 CKD; CKD3: Stage 3 CKD In the analysis of DR, 650 patients exhibited SUA levels below 354.0 umol/L (low UA group), while 365 had a SUA level equal to or above 354.1 umol/L (high SUA group). Table 4 summarizes the clinical characteristics of these two groups. The average age of the high SUA group was lower compared to that of the low UA group (p = 0.002). Patients in the high SUA group displayed higher systolic blood pressure (SBP), diastolic blood pressure (DBP), and a greater percentage in the history of hypertension, smoking and alcohol consumption compared to those in the low UA group. There were no significant differences between the two groups regarding diabetes duration and percentages of patients with NDR, non-VTDR, CKD1, and CKD3. In terms of laboratory parameters, BUN, Scr, TG levels were elevated in the high UA group compared to the low UA group (p < = 0.001 for all three parameters). However, there were no significant differences observed in TC and LDL-c levels between the two groups. Table 4 Orderly logistic regression analyses of the association between different levels of SUA and the prevalence of DR progression SUA Total SUA range (median) 100.0-354.0 (280.1) 354.0-986.0 (408.7) P value Crude Model Ref. 1.512 (1.148–1.991) 0.003 age-adjusted Model Ref. 1.439 (1.090–1.901) 0.010 Multivariable-adjusted model 1 Ref. 1.531 (1.138–2.059) 0.005 Multivariable-adjusted model 2 Ref. 1.571 (1.136–2.099) 0.006 Male SUA range (median) 145.7-355.1 (289.6) 355.1–986.0 (409.8) Crude Model Ref. 1.354 (0.960–1.910) 0.084 age-adjusted Model Ref. 1.317 (0.932–1.862) 0.119 Multivariable-adjusted model 3 Ref. 1.523 (1.058–2.191) 0.024 Multivariable-adjusted model 4 Ref. 1.498 (1.017–2.206) 0.041 Female SUA range (median) 100.0-352.1 (268.7) 352.1-604.5 (404.3) Crude Model Ref. 1.607 (0.980–2.635) 0.060 age-adjusted Model Ref. 1.537 (0.933–2.532) 0.091 Multivariable-adjusted model 3 Ref. 1.605 (0.967–2.665) 0.067 Multivariable-adjusted model 5 Ref. 1.818 (1.081–3.058) 0.024 1 Adjusted for age, sex, HbA1c and diabetes duration. 2 Adjusted for age, sex, diabetes duration, HbA1c, ALB, BUN, HDL-c, smoking status and eGFR. 3 Adjusted for age, HbA1c and diabetes duration. 4 Adjusted for age, diabetes duration, HbA1c, ALB, BUN, Cr, smoking status and eGFR. 5 Adjusted for age, diabetes duration, HbA1c, and glycated albumin. Considering the sex of the patients, the clinical characteristics of individuals with high and low SUA levels were analyzed based on sex-specific cutoffs. The results are presented in table S2 for males and table S3 for females. The thresholds for SUA for DR worsening were 355.1 umol/L in men and 352.1 umol/L in women. The thresholds for SUA for CKD worsening were 361.0 umol/L in men and 353.6 umol/L in women. Table 3 provides a summary of the sex-specific ideal cutoffs for DR and CKD as well as the ranges of sensitivity and specificity. High SUA are independent risk factors for the progression of DR and CKD In the analysis of univariate orderly logistic regression, there was a correlation between elevated SUA levels and an increased risk of DR progression in the overall population (OR, 1.512; 95% CI = 1.148–1.991; p < 0.003). However, this association was not observed in either male (OR, 1.354; 95% CI = 0.960–1.910; p = 0.084) or female (OR, 1.607; 95% CI = 0.980–2.635; p = 0.060) subpopulations according to the crude model results. After adjusting for multiple variables, high SUA levels remained a significant risk factor for DR progression. In male patients, we noted a significant association between elevated SUA levels and an increased likelihood of developing DR in two different models. The ORs for the development of DR in individuals with high SUA levels compared to those with low SUA levels were 1.317 (95% CI, 0.932–1.862; P = 0.119) after adjusting for age, 1.523 (95% CI, 1.058–2.191; P = 0.024) in multivariable-adjusted model 3, and 1.498 (95% CI, 1.017–2.206; P = 0 .041) after adjusting for age, diabetes duration, HbA1c, ALB, BUN, Cr, smoking status and eGFR. In female patients, the association between elevated SUA levels and DR was found to be significant only when adjusting for age, diabetes duration, HbA1c, and glycated albumin. The results regarding ORs for developing CKD remained consistent across male and female groups. High SUA levels were identified as an independent risk factor in all four models analyzed (Table 5 ). Table 5 Orderly logistic regression analyses of the association between different levels of SUA and the prevalence of CKD progression SUA Total SUA range (median) 100.0–361.0 (284.1) 361.0–986.0 (415.2) P value Crude Model Ref. 1.622 (1.245–2.111) < 0.001 age-adjusted Model Ref. 1.691 (1.296–2.206) < 0.001 Multivariable-adjusted model 1 Ref. 2.013 (1.516–2.674) < 0.001 Multivariable-adjusted model 2 Ref. 1.395 (1.033–1.885) 0.030 Male SUA range (median) 100.0–361.0 (284.1) 361.0–986.0 (415.2) Crude Model Ref. 1.687 (1.177–2.417) 0.004 age-adjusted Model Ref. 1.743 (1.214–2.501) 0.002 Multivariable-adjusted model 1 Ref. 2.213 (1.529–3.202) 0.000 Multivariable-adjusted model 2 Ref. 1.518 (1.015–2.269) 0.033 Female SUA range (median) 100.0–353.6 (280.1) 353.6–604.5 (408.7) Crude Model Ref. 2.000 (1.270–3.151) 0.003 age-adjusted Model Ref. 2.028 (1.297–3.232) 0.002 Multivariable-adjusted model 1 Ref. 2.230 (1.401–3.551) 0.001 Multivariable-adjusted model 2 Ref. 1.702 (1.035–2.801) 0.036 1 Adjusted for age, BMI, HbA1c and diabetes duration. 2 Adjusted for age, BMI, diabetes duration, HbA1c, ALB, BUN, TG, history of hypertension and eGFR. Discussion In this cross-sectional study, we observed a positive correlation between SUA levels and the severity of DR and CKD. Elevated SUA levels were found to be associated with a higher prevalence of both CKD and DR in diabetic patient independently of other well-known and potential risk factors. Logistic regression analysis revealed that for every 1 µmol/L increment in SUA level, there was a corresponding 0.2% increase in the risk of developing DR and a 0.5% increase in the risk of CKD progression. In the present study, the prevalence of DR among patients with diabetes for at least 5 years was 29.0%, and the prevalence of CKD was 33.1%. It is higher than the reported prevalence in Eastern China,[ 12 , 19 , 20 ] which is most likely due to the relatively long duration of diabetes history of the patients included in this study. Additionally, the currently acknowledged risk factors associated with DR or DN, [ 21 ] including the duration of diabetes, the younger age of onset of diabetes, and higher HbA1c levels were also reported in this study. It has been found that SUA levels in patients with T2DM increase with the severity of DR and the decline of renal function. [ 22 – 25 ] In our study, we also observed a higher level of SUA in patients with more severe DR and relatively high levels of CKD. Of note, there was no significant difference in SUA levels between the CKD2 and CKD3 groups, possibly due to the small sample size of the CKD3 group. Several other studies published have also suggested that SUA may be an independent risk factor for DR.[ 24 ] Two large cross-sectional studies reported that SUA is associated with an increased risk of DR or more severe DR.[ 14 , 26 ] In addition, higher quartiles of SUA were associated with an increased incidence of new-onset DR and progression to NPDR in two prospective cohort studies.[ 22 , 27 ] Our analyses indicated that higher levels of SUA were identified as independent risk factors for both DR and CKD, consistent with previous research findings. However, there are some studies that presented contrasting results regarding the association between SUA and DR. For example, a large-scale cross-sectional study involving 2961 patients with T2DM demonstrated an association between SUA levels and a higher prevalence of DN instead of DR.[ 12 ] Similarly, another cross-sectional study including 2809 patients reported that elevated concentrations of SUA independently increased the risk of DN but not DR. [ 13 ] Overall, despite evidence that UA is associated with the development of DR and CKD, whether elevated UA is a cause or a consequence of microangiopathy is still controversial, and a large number of prospective studies are needed to elucidate the causality. To investigate the potential impact of SUA on disease mechanisms, various experimental and clinical studies have identified several possible connections between UA and diabetic microangiopathy. Elevated levels of SUA may contribute to the development of diabetic complications by disturbing insulin pathway, triggering inflammation, oxidative stress, and impairing endothelial function.[ 28 ] A cross-sectional study conducted on a large population discovered a correlation between SUA levels and proinflammatory cytokines, including IL-6, TNF-alpha, and CRP, which play a pivotal role in the pathophysiology of diabetic complications.[ 29 ] Zhu et al. found that UA increased apoptosis and inflammatory chemokine productions in human retinal endothelial cells exposed to high concentrations of UA. A Similar alteration was observed in animal experiments that rats with hyperuricemia exhibited elevated levels of inflammatory cytokines. [ 30 ] Of note, there is sex difference in UA metabolism that males have higher circulating UA levels than females, as observed in our study. An increase in the risk of cardiovascular death (CVD) and SUA levels was associated with significant intergender differences.[ 31 ] However, the occurrence of diabetic complications in men does not always indicate a sex-specific susceptibility to UA. UA was reported to affect insulin function in both male and female populations. A recent study has revealed that there is an independent impact of SUA on insulin secretion among female patients, and in male patients, SUA was positively correlated with insulin secretion and insulin resistance index.[ 32 ] Clinical studies on DR showed that the sex-specific effect of SUA on microangiopathy is unclear. A cross-sectional study in Japan reported that higher SUA levels were associated with a high risk of developing DR in only males.[ 27 ] While another study showed that higher SUA levels are risk factor of VTDR in both sexes, it appears that females exhibited greater susceptibility to high SUA compared to males.[ 14 ] Therefore, we conducted a sex‐stratified analysis in this study. The present study indicated a significant positive correlation between SUA levels and DR progression in both males and females after adjustment for potential risk factors, and females seemed to be more susceptible to increasement in UA levels. At present, the existence of sex differences in SUA for diabetic microangiopathy still needs more researches to be verified. There are arguments regarding the association between SUA and diabetes as well as its complications in females, which may be influenced by their menopausal status. Understanding sex differences at the mechanistic level remains challenging. Sex differences in vascular endothelial cell function and oxidant/antioxidant responses have been shown at the cellular level.[ 33 , 34 ] Investigating the impact of interventions targeting UA levels on the progression of DR and nephropathy is another promising avenue. However, there is no consensus on the optimal target for SUA levels in patients with diabetes. UA exhibits physiological solubility up to approximately 6.4 mg/dL. UA-binding proteins contribute to enhancing solubility to around 7.0 mg/dL before reaching supersaturation. Beyond this point, crystallization of serum UA may occur, leading to the development of hyperuricemia.[ 35 ] Typically, hyperuricemia is defined as having UA levels exceeding 420 µmol/L for males and 360 µmol/L for females. Multiple studies have demonstrated that even when within a normal range, an elevated SUA level is linked to a higher prevalence of diabetic complications after adjusting for confounding factors.[ 27 , 36 – 38 ] Our results showed that in general population the threshold UA levels were 354.0 umol/L and 361.0 umol/L for DR and CKD occurrence, respectively. When considering the sex of the patients, it is interesting to note that the identified cutoff values for SUA associated with the worsening of DR were similar, and the SUA thresholds associated with CKD were only slightly higher in men than in women. The previous studies have not provided explicit data regarding the level of UA that contribute to the development of DR. However, there are researches indicating the threshold values for SUA in CVD and CKD. Virdis et al. identified critical threshold levels for UA associated with adverse outcomes that 4.7 mg/dL for all-cause mortality and 5.6 mg/dL for cardiovascular mortality.[ 39 ] Another cohort study revealed that in patients with T2DM, SUA levels exceeding 6.3 mg/dL (374.85 µmol/L) independently increased the risk of CKD progression.[ 40 ] Although there is no recommendation to initiate UA-lowering therapy in patients with asymptomatic hyperuricemia,[ 41 ] it is important to establish an optimal target range of SUA levels in patients with diabetes. On the one hand it helps to reduce the risk of developing diabetic complications, on the other hand, it is beneficial to avoid hypouricemia which has been observed to be associated with decreased renal function and increased mortality. [ 42 , 43 ] Our study has several limitations. Firstly, as a cross-sectional observational study and not an intervention study, no causal conclusions could be drawn. Secondly, a history of renin-angiotensin-aldosterone system indicators is absent in this study, which may be one of the important confounding factors that influence estimating the impact of high SUA level. Thirdly, the sample size in this study is not large enough, resulting in a small number of subjects with severer level of DR and CKD. Lastly, the assessment of DME with fundus pictures may be less reliable than the OCT imaging, leading to error of grouping. Conclusion In summary, our study revealed a positive correlation between elevated SUA levels and the progression of both DR and CKD in Chinese individuals with at least a 5-year duration of diabetes, after adjustment for potential confounding factors. The increased risk of DR and worsening was found among subjects with a SUA level higher than 354.0 umol/L and 361.0 umol/L in total population, respectively, with no significant sex-differences. This finding provides evidence and possibilities for future studies to refine UA risk stratification and treatment interventions in patients with long-term diabetes. Declarations Conflict of Interest Disclosures: The authors declare no financial/conflicting interests. Funding: This study was supported by National Natural Science Foundation of China (82171071), Program of Shanghai Academic/Technology Research Leader (21XD1402700). Authors' contributions ： HW performed the statistical analysis, and was a major contributor in writing the manuscript. LG and YM collected original data and pictures, and LG organized all data. XX, YQ, XS, XL, HW, QZ, YS, CC and LS read the fundus pictures. YW and KL conceived, organized and conducted this clinical study. All authors read and approved the final manuscript. References Khan MAB, Hashim MJ, King JK, Govender RD, Mustafa H, Al Kaabi J. Epidemiology of Type 2 Diabetes - Global Burden of Disease and Forecasted Trends. 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Lee JJ, Yang IH, Kuo HK, Chung MS, Chen YJ, Chen CH, et al. Serum uric acid concentration is associated with worsening in severity of diabetic retinopathy among type 2 diabetic patients in Taiwan–a 3-year prospective study. Diabetes Res Clin Pract. 2014;106:366–72. Cai XL, Wang F, Ji LN. Risk factors of diabetic retinopathy in type 2 diabetic patients. Chin Med J (Engl). 2006;119:822–6. Liang CC, Lin PC, Lee MY, Chen SC, Shin SJ, Hsiao PJ et al. Association of Serum Uric Acid Concentration with Diabetic Retinopathy and Albuminuria in Taiwanese Patients with Type 2 Diabetes Mellitus. Int J Mol Sci. 2016;17. Fukui M, Tanaka M, Shiraishi E, Harusato I, Hosoda H, Asano M, et al. Serum uric acid is associated with microalbuminuria and subclinical atherosclerosis in men with type 2 diabetes mellitus. Metabolism. 2008;57:625–9. Cui J, Ren JP, Chen DN, Xin Z, Yuan MX, Xu J, et al. Prevalence and associated factors of diabetic retinopathy in Beijing, China: a cross-sectional study. BMJ Open. 2017;7:e015473. Kuwata H, Okamura S, Hayashino Y, Tsujii S, Ishii H. Serum uric acid levels are associated with increased risk of newly developed diabetic retinopathy among Japanese male patients with type 2 diabetes: A prospective cohort study (diabetes distress and care registry at Tenri [DDCRT 13]). Diabetes Metab Res Rev. 2017;33. Xiong Q, Liu J, Xu Y. Effects of Uric Acid on Diabetes Mellitus and Its Chronic Complications. Int J Endocrinol. 2019;2019:9691345. Tsalamandris S, Antonopoulos AS, Oikonomou E, Papamikroulis GA, Vogiatzi G, Papaioannou S, et al. The Role of Inflammation in Diabetes: Current Concepts and Future Perspectives. Eur Cardiol. 2019;14:50–9. Zhu DD, Wang YZ, Zou C, She XP, Zheng Z. The role of uric acid in the pathogenesis of diabetic retinopathy based on Notch pathway. Biochem Biophys Res Commun. 2018;503:921–9. Huang JH, Li RH, Huang SL, Sia HK, Yu CH, Tang FC. Gender Difference in the Relationships between Inflammatory Markers, Serum Uric Acid and Framingham Risk Score. Int J Environ Res Public Health. 2021;18. Hu Y, Liu J, Li H, Zhu H, Liu L, Yuan Y, et al. The association between elevated serum uric acid levels and islet β-cell function indexes in newly diagnosed type 2 diabetes mellitus: a cross-sectional study. PeerJ. 2018;6:e4515. Takenouchi Y, Kobayashi T, Matsumoto T, Kamata K. Gender differences in age-related endothelial function in the murine aorta. Atherosclerosis. 2009;206:397–404. Kamper EF, Chatzigeorgiou A, Tsimpoukidi O, Kamper M, Dalla C, Pitychoutis PM, et al. Sex differences in oxidant/antioxidant balance under a chronic mild stress regime. Physiol Behav. 2009;98:215–22. Kuwabara M, Hyperuricemia. Cardiovascular Disease, and Hypertension. Pulse (Basel). 2016;3:242–52. Feig DI, Johnson RJ. Hyperuricemia in childhood primary hypertension. Hypertension. 2003;42:247–52. Nakagawa T, Tuttle KR, Short RA, Johnson RJ. Hypothesis: fructose-induced hyperuricemia as a causal mechanism for the epidemic of the metabolic syndrome. Nat Clin Pract Nephrol. 2005;1:80–6. Niskanen LK, Laaksonen DE, Nyyssönen K, Alfthan G, Lakka HM, Lakka TA, et al. Uric acid level as a risk factor for cardiovascular and all-cause mortality in middle-aged men: a prospective cohort study. Arch Intern Med. 2004;164:1546–51. Virdis A, Masi S, Casiglia E, Tikhonoff V, Cicero AFG, Ungar A, et al. Identification of the Uric Acid Thresholds Predicting an Increased Total and Cardiovascular Mortality Over 20 Years. Hypertension. 2020;75:302–8. Chang YH, Lei CC, Lin KC, Chang DM, Hsieh CH, Lee YJ. Serum uric acid level as an indicator for CKD regression and progression in patients with type 2 diabetes mellitus-a 4.6-year cohort study. Diabetes Metab Res Rev. 2016;32:557–64. Sivera F, Andrés M, Carmona L, Kydd AS, Moi J, Seth R, et al. Multinational evidence-based recommendations for the diagnosis and management of gout: integrating systematic literature review and expert opinion of a broad panel of rheumatologists in the 3e initiative. Ann Rheum Dis. 2014;73:328–35. Park JH, Jo YI, Lee JH. Renal effects of uric acid: hyperuricemia and hypouricemia. Korean J Intern Med. 2020;35:1291–304. Lee CL, Tsai SF. Association between mortality and serum uric acid levels in non-diabetes-related chronic kidney disease: An analysis of the National Health and Nutrition Examination Survey, USA, 1999–2010. Sci Rep. 2020;10:17585. Additional Declarations No competing interests reported. Supplementary Files Appendices.docx Cite Share Download PDF Status: Published Journal Publication published 28 Mar, 2025 Read the published version in Diabetology & Metabolic Syndrome → Version 1 posted Editorial decision: Revision requested 30 Jan, 2025 Reviews received at journal 16 Jan, 2025 Reviewers agreed at journal 07 Jan, 2025 Reviewers agreed at journal 01 Dec, 2024 Reviews received at journal 30 Jul, 2024 Reviewers agreed at journal 29 Jul, 2024 Reviewers invited by journal 24 Jul, 2024 Editor assigned by journal 18 Jul, 2024 Submission checks completed at journal 18 Jul, 2024 First submitted to journal 17 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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17:06:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4757783/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4757783/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13098-025-01656-1","type":"published","date":"2025-03-28T15:57:44+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62729271,"identity":"b112587b-23f2-4ee6-8c23-fd06024b9a08","added_by":"auto","created_at":"2024-08-18 22:59:26","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":69313,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSerum concentrations of uric acid in groups with different stage of DR (A) and CKD (B). \u003c/strong\u003eThe average serum uric acid (SUA) level increased as the severity of DR and CKD increased. DR: Diabetic Retinopathy; NDR: Non-Diabetic Retinopathy; VTDR: Vision-Threatening Diabetic Retinopathy; CKD: Chronic Kidney Disease; CKD1: Stage 1 CKD; CKD2: Stage 2 CKD; CKD3: Stage 3 CKD；ns：Non-Significant；*：p\u0026lt;0.05; ***p\u0026lt;0.001; ****:P\u0026lt;0.0001\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4757783/v1/483dc0ab32bde4d45e879269.jpg"},{"id":62729273,"identity":"2d6dcaaa-2779-4760-98d1-25db9fe7b504","added_by":"auto","created_at":"2024-08-18 22:59:26","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":113459,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest plot demonstrating odds ratios and 95% CIs for associations between SUA and DR prevalence (A) and prevalence of CKD (B) \u003c/strong\u003eSUA: Serum Uric Acid; BMI: Body Mass Index; HDL-C: High-Density Lipoprotein Cholesterol; ALB: Albumin; HbA1c: Hemoglobin A1c; Hb: Hemoglobin, DR: Diabetic Retinopathy; CKD: Chronic Kidney Disease\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4757783/v1/3d8fe3fd1c26bdd2333f9897.jpg"},{"id":79605005,"identity":"2af41ce3-e95a-442a-977b-25dfa0c83896","added_by":"auto","created_at":"2025-03-31 16:10:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1275237,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4757783/v1/5b164f80-33f2-4ca6-b026-32c298d9e14a.pdf"},{"id":62729274,"identity":"b1c10331-2fa8-477c-802e-d519d34292f5","added_by":"auto","created_at":"2024-08-18 22:59:27","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":24890,"visible":true,"origin":"","legend":"","description":"","filename":"Appendices.docx","url":"https://assets-eu.researchsquare.com/files/rs-4757783/v1/5a3043976e9f3b018464a04a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"High Levels of Serum Uric Acid are Associated with Microvascular Complications in Patients with Long-term Diabetes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDiabetes mellitus (DM), a chronic metabolic disorder characterized by elevated blood glucose levels, has seen a notable increase in prevalence, making it a considerable public health concern. Recent data from the World Health Organization (WHO) suggest that an estimated 462\u0026nbsp;million individuals globally are living with type 2 diabetes.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] Both type 1 and type 2 diabetes are associated with cardiovascular, renal, ocular and neurological complications.[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eDiabetic retinopathy (DR) and diabetic nephropathy (DN) are common complications in patients with diabetes and the most frequent causes of blindness and death.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] Both of them are microvascular injuries caused by hyperglycemia, thus share some common metabolic alterations that contribute to the pathogenesis of diabetic complications. Several research suggested the development and progression of DN and retinopathy are influenced not just by hyperglycemia but also by factors including age, smoking, obesity, hypertension, dyslipidemia, and inflammation.[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] Therefore, identifying additional contributors to the pathophysiological mechanisms underlying diabetic complications is crucial.\u003c/p\u003e \u003cp\u003eUric acid (UA) is the degradation product of purines, and hyperuricemia is highly prevalent in patients with diabetes,[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] due to impaired renal function resulting in decreased renal excretion of UA .[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] Serum uric acid (SUA) has been recently recognized as a risk factor for both macrovascular and microvascular diseases. On the one hand, previous studies[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] have suggested a potential link between elevated UA levels and the development and progression of diabetes. On the other hand, high levels of UA can also contribute to inflammation, oxidative stress, and apoptosis,[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] potentially playing a significant role in the development of diabetic complications. Several clinical studies have shown an association between elevated UA levels and DN.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] However, clinical trials have yielded inconsistent findings regarding the link between UA and diabetic retinopathy (DR).[\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] Our previous clinical study,[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] a metabolomics-based investigation, showed a significant increase of uric acid levels in vitreous samples from patients with proliferative diabetic retinopathy (PDR) compared to non-diabetic controls (UA intensity, 694.2 vs 475.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). This result suggests a potential involvement of UA in the development of DR. The elevated levels of UA in the vitreous may be due to both local metabolic changes within the retina and a potential increase in systemic UA levels. Although alterations in vitreous uric acid levels exhibit more relevant to disease mechanisms, the assessment of SUA remains more suitable for disease prevention and management.\u003c/p\u003e \u003cp\u003eTherefore, we conducted a cross-sectional study in patients with diabetes for at least 5 years to better understand the relationship between SUA and the occurrence of diabetic microvascular complications.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eThe cross-sectional study recruited patients with diabetes (including both Type 1 and Type 2 diabetes mellitus), who were from the Department of Endocrinology at Shanghai General Hospital, China between October 2018 and October 2021. Diabetes was determined through the assessment of plasma glucose levels, specifically with criteria such as fasting blood glucose (FBG)\u0026thinsp;\u0026ge;\u0026thinsp;7.0 mmol/L or 2-hour plasma glucose (2h PG) exceeding 11.1 mmol/L during a 75 g oral glucose tolerance test.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] Patients were included if diagnosed with diabetes for \u0026gt;\u0026thinsp;5 years, with available SUA data and fundus photography. We excluded patients with gestational diabetes or diabetes induced by medication use or other endocrine diseases. Finally, a total of 1015 subjects were included in this study. Written informed consent was obtained from each participant before the study began, and the study was approved by the Ethics Committee of Shanghai General Hospital.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDiagnose of Diabetic retinopathy (DR)\u003c/h2\u003e \u003cp\u003eFor each eye of each subject, one standard color fundus image was obtained with 45\u0026deg; field of view, non-stereoscopic and macula-centered. A modified grading scale reported previously was used for the classification of DR and diabetic macular edema (DME).[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] Patients are grouped according to the degree of the eye with the worse grade when the grades of both eyes were inconsistent. Then the patients were grouped into non-DR (NDR), non-vision threatened diabetic retinopathy (non-VTDR) which including mild and moderate non proliferative diabetic retinopathy (NPDR), and VTDR which including severe NPDR, PDR and DME. All fundus images were assessed by the Ophthalmology Center of the Shanghai General Hospital (National Clinical Research Center for Eye Diseases).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDemographic data and laboratory measurements\u003c/h2\u003e \u003cp\u003eIn the survey, patients were subjected to a standard inquiry regarding their medical history, physical examination, and laboratory tests. Various demographic information including age, sex, height, weight, blood pressure, smoking or alcohol consumption habits were recorded. Additionally, their medical history encompassing both microvascular and macrovascular complications along with treatment approaches including medications for hypertension and diabetes were documented.\u003c/p\u003e \u003cp\u003eIn this study, demographic information of the patients including age, sex, height, weight, blood pressure, history of smoking and alcohol consumption, medical history and treatment were obtained. Blood samples were obtained from the patients\u0026rsquo; antecubital vein at overnight fasting for biochemical measurement, including lipid profile (total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C)), blood urea nitrogen (BUN), serum creatinine, SUA, fasting blood glucose and postprandial blood glucose. Urine samples were collected to test the levels of urinary albumin\u0026ndash;creatinine ratio (UACR). The estimated glomerular filtration rate (eGFR) is used to estimate kidney function and determine chronic kidney disease (CKD) staging, using the following formula: eGFR [mL/ (min \u0026times; 1.73 m\u003csup\u003e2\u003c/sup\u003e)]\u0026thinsp;=\u0026thinsp;194 \u0026times; Cr\u003csup\u003e\u0026minus;\u0026thinsp;1.094\u003c/sup\u003e \u0026times; age\u003csup\u003e\u0026minus;\u0026thinsp;0.287\u003c/sup\u003e (\u0026times;0.739 for female patients).[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eMultiple imputation was conducted in this study to impute missing values using the MI procedure in SPSS software (version 26.0.0.2; SPSS, Chicago, IL, USA). UA levels\u0026thinsp;\u0026ge;\u0026thinsp;7.0 mg/dL in men and \u0026ge;\u0026thinsp;6 mg/dL in women were defined as hyperuricemia. All continuous variables were non-normally distributed and expressed as median plus interquartile range (IQR). Differences between groups were evaluated using nonparametric tests. Categorical variables were presented as numbers (proportions) and comparisons between groups were made using the chi-square test. Correlations between UA levels and other measures were evaluated by Pearson's correlation analysis and linear regression analysis. To identify independent risk factors associated with the prevalence of DR and CKD, orderly logistic regression analyses were performed. Variables known or thought to be associated with DR or CKD were selected as covariates in statistical models. Results were presented as odds ratios (ORs) and 95% confidence intervals (95% CIs), considering P values less than 0.05 as statistically significant. Receiver operating characteristics (ROC) curves and SUA cutoff points were derived to obtain UA groupings (low SUA group and high SUA group). Statistical analyses were performed using SPSS software and GraphPad Prism (version 9.5.0; GraphPad Software Inc., San Diego, CA, USA). The 95% CIs of SUA cutoff points were computed in Python (version 3.12).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics\u003c/h2\u003e \u003cp\u003eBaseline characteristics of the study participants are depicted in Table\u0026nbsp;1. A total of 1015 participants were included, comprising 721 patients with NDR (71.03%), 241 with non-VTDR (23.7%), and 53 diagnosed with VTDR (5.2%). The mean baseline SUA was 315.1, 322.5 and 356.0 \u0026micro;mol/L, respectively. Comparing individuals without DR, those with VTDR exhibited higher baseline SUA levels (315.1 \u0026micro;mol/L vs. 356.0 \u0026micro;mol/L; P\u0026thinsp;=\u0026thinsp;0.019) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Observations also indicate an increased prevalence of hyperuricemia among individuals at DR (14% vs. 19%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The duration of diabetes (P\u0026thinsp;=\u0026thinsp;0.002), sex distribution (P\u0026thinsp;=\u0026thinsp;0.049) and the level of HbA1c (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) differ between the groups. The indicators that also present inter-group differences include glycated albumin, BUN, HDL- C and ALB. There was no statistically significant difference in BMI between the two groups (P\u0026thinsp;=\u0026thinsp;0.306).\u003c/p\u003e \u003cp\u003e\u003cstrong\u003eTable 1 Characteristics of the population grouped by diabetic retinopathy\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"615\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003eNDR (n=721)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003eNon-VTDR (n=241)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003eVTDR (n=53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eAge (year)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e60.0 (13.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e57.0 (14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e56.0 (18.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eEye (right, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e343 (47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e111 (46.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e22 (41.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.664\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eSex (Male, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e401 (55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e155 (64.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e33 (62.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eduration(months)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e122.0 (97.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e131.0 (88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e157.0 (136)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eBMI (kg/m2)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e24.60 (4.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e24.90 (4.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e24.90 (4.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.306\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eSBP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e127.0 (21.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e126.0 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e126.0 (26.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eDBP (mmHg)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e76.0 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e78.0 (16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e78.0 (13.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.441\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eBUN (mmol/L)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e5.52 (2.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e5.52 (2.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e6.43 (3.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eSUA (umol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e315.1 (121.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e322.5 (120.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e356.0 (129.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Normal (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e620 (86.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e200 (83.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e38 (71.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.75970425138632%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;High (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.735674676524955%\" valign=\"top\"\u003e\n \u003cp\u003e101 (14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.062846580406653%\" valign=\"top\"\u003e\n \u003cp\u003e41 (17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.44177449168207%\" valign=\"top\"\u003e\n \u003cp\u003e15 (28.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eScr (\u0026mu;mol/L)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e59.0 (20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e58.8 (23.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e65.4 (27.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eeGFR (mL/min/1.73m2)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e100.64 (15.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e104.27 (20.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e101.99 (24.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e\u0026nbsp;0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e86 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e42 (17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e9 (17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\" rowspan=\"3\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.75970425138632%\" valign=\"top\"\u003e\n \u003cp\u003e90-120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.735674676524955%\" valign=\"top\"\u003e\n \u003cp\u003e517 (71.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.062846580406653%\" valign=\"top\"\u003e\n \u003cp\u003e165 (68.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.44177449168207%\" valign=\"top\"\u003e\n \u003cp\u003e29 (54.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.75970425138632%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;89\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.735674676524955%\" valign=\"top\"\u003e\n \u003cp\u003e119 (16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.062846580406653%\" valign=\"top\"\u003e\n \u003cp\u003e34 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.44177449168207%\" valign=\"top\"\u003e\n \u003cp\u003e15 (28.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eTC (mmol/L)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e4.78 (1.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e4.89 (1.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e4.76 (2.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.332\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eTG (mmol/L)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e1.40 (1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e1.58 (1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e1.63 (1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.271\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eHDL-c(mmol/L)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e1.06 (0.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e1.01 (0.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e1.00 (0.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eLDL-c(mmol/L)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e2.73 (1.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e2.83 (1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e2.89 (1.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.410\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eALB (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e44.80 (5.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e44.40 (6.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e42.30 (8.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eHbA1c (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e7.80 (2.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e8.70 (2.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e8.90 (2.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;7 (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e221 (30.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e51 (21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e10 (18.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.75970425138632%\" valign=\"top\"\u003e\n \u003cp\u003e7-9 (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.735674676524955%\" valign=\"top\"\u003e\n \u003cp\u003e314 (43.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.062846580406653%\" valign=\"top\"\u003e\n \u003cp\u003e89 (36.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.44177449168207%\" valign=\"top\"\u003e\n \u003cp\u003e17 (32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.75970425138632%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;(n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.735674676524955%\" valign=\"top\"\u003e\n \u003cp\u003e186 (25.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.062846580406653%\" valign=\"top\"\u003e\n \u003cp\u003e101 (41.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.44177449168207%\" valign=\"top\"\u003e\n \u003cp\u003e26 (49.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eGlycated albumin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e19.47 (7.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e22.50 (8.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e24.22 (10.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e0h-PG (mmol/L)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e7.79 (3.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e8.43 (3.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e7.89 (4.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e1h-PG (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e13.26 (5.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e12.84 (6.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e11.05 (7.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e2h-PG (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e13.89 (6.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e13.48 (7.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e11.73 (9.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eUACR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e14.23 (29.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e18.14 (54.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e74.86 (365.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eNormal (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e517 (71.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e155 (64.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e21 (39.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.75970425138632%\" valign=\"top\"\u003e\n \u003cp\u003e30-300 (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.735674676524955%\" valign=\"top\"\u003e\n \u003cp\u003e163 (22.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.062846580406653%\" valign=\"top\"\u003e\n \u003cp\u003e60 (24.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.44177449168207%\" valign=\"top\"\u003e\n \u003cp\u003e16 (30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.75970425138632%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt; 300 (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.735674676524955%\" valign=\"top\"\u003e\n \u003cp\u003e41 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.062846580406653%\" valign=\"top\"\u003e\n \u003cp\u003e26 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.44177449168207%\" valign=\"top\"\u003e\n \u003cp\u003e16 (30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eCKD (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e194 (26.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e85 (35.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e33 (62.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eCKD1 (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e143 (19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e66 (27.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e22 (41.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.75970425138632%\" valign=\"top\"\u003e\n \u003cp\u003eCKD2 (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.735674676524955%\" valign=\"top\"\u003e\n \u003cp\u003e38 (5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.062846580406653%\" valign=\"top\"\u003e\n \u003cp\u003e10 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.44177449168207%\" valign=\"top\"\u003e\n \u003cp\u003e8 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.75970425138632%\" valign=\"top\"\u003e\n \u003cp\u003eCKD3 (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.735674676524955%\" valign=\"top\"\u003e\n \u003cp\u003e13 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.062846580406653%\" valign=\"top\"\u003e\n \u003cp\u003e9 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.44177449168207%\" valign=\"top\"\u003e\n \u003cp\u003e3 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003ePrevious history\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eHypertension\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e354 (49.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e114 (47.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e29 (54.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.786\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003esmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e271 (37.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e116 (48.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e21 (39.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eDrinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e325 (45.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e120 (49.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e24 (45.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.441\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eDyslipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e190 (26.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e62 (25.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e18 (34.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.668\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eCoronary Heart Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e63 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e18 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e6 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.790\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.136363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eStroke\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.967532467532468%\" valign=\"top\"\u003e\n \u003cp\u003e35 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88961038961039%\" valign=\"top\"\u003e\n \u003cp\u003e11 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.83116883116883%\" valign=\"top\"\u003e\n \u003cp\u003e4 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.175324675324676%\"\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSUA: Serum Uric Acid; BMI: Body Mass Index; SBP: Systolic Blood Pressure; DBP: Diastolic Blood Pressure; BUN: Blood Urea Nitrogen; Scr: Serum Creatinine; eGFR: Estimated Glomerular Filtration Rate; TC: Total Cholesterol; TG: Triglycerides; HDL-c: High-Density Lipoprotein Cholesterol; LDL-c: Low-Density Lipoprotein Cholesterol; ALB: Albumin; HbA1c: Hemoglobin A1c; PG: Plasma Glucose; DR: Diabetic Retinopathy; NDR: Non-Diabetic Retinopathy; VTDR: Vision-Threatening Diabetic Retinopathy; CKD: Chronic Kidney Disease; CKD1: Stage 1 CKD; CKD2: Stage 2 CKD; CKD3: Stage 3 CKD\u003c/p\u003e\u003cp\u003eSubsequently, we categorized all patients into three groups based on CKD staging (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Compared to the CKD 1 group, patients with CKD 2\u0026amp;3 exhibited significantly higher SUA levels (314.2\u0026thinsp;\u0026plusmn;\u0026thinsp;134.3 \u0026micro;mol/L vs 362.9\u0026thinsp;\u0026plusmn;\u0026thinsp;144.5 \u0026micro;mol/L, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; 314.2\u0026thinsp;\u0026plusmn;\u0026thinsp;134.3\u0026micro;mol/L vs 359.1\u0026thinsp;\u0026plusmn;\u0026thinsp;173.2 \u0026micro;mol/L, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively). An analysis of diagnosed hyperuricemia proportions within each group revealed a higher prevalence of hyperuricemia among individuals in advanced CKD stages (12.6% vs 30.0%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; 12.6% vs 30.0%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively). Several parameters exhibit significant differences between patients at different stages of CKD, including age, the duration of diabetes, DBP, ALB, BUN, Scr, eGFR, 0h-PG and the prevalence of hypertension.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSUA levels are independent risk factors for both DR and CKD\u003c/h2\u003e \u003cp\u003eUpon examination of SUA as a continuous variable, an orderly logistic regression analysis revealed that SUA was an independent risk factor for the progression of both DR and CKD (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). After adjusting for sex, age, diabetic duration, smoking history, HDL-C, ALB, and HbA1c, the risk factors for DR progression were high SUA (OR: 1.002, 95% CI: 1.001\u0026ndash;1.004), longer duration of DM (OR, 1.005; 95% CI\u0026thinsp;=\u0026thinsp;1.125\u0026ndash;1.310; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), younger age (OR, 0.959; 95% CI\u0026thinsp;=\u0026thinsp;0.945\u0026ndash;0.972; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), low ALB (OR, 0.951; 95% CI\u0026thinsp;=\u0026thinsp;0.921\u0026ndash;0.981; p\u0026thinsp;=\u0026thinsp;0.02), and high HbA1c (OR, 1.214; 95% CI\u0026thinsp;=\u0026thinsp;1.125\u0026ndash;1.310; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The study found that independent risk factors for CKD, after multivariate adjustments, included high SUA levels (OR: 1.008, 95% CI: 1.006\u0026ndash;1.011), low Hb (OR, 0.977; 95% CI\u0026thinsp;=\u0026thinsp;0.965\u0026ndash;0.989; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and older age (OR, 1.155; 95% CI\u0026thinsp;=\u0026thinsp;1.121\u0026ndash;1.188; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eROC curves and ideal SUA cutoff for prediction of DR and CKD\u003c/h2\u003e \u003cp\u003eIn order to determine clinically meaningful SUA thresholds for predicting the occurrence of DR and CKD, we utilized ROC curves to obtain cutoffs to optimize both sensitivity and specificity (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). To discriminate DR or CKD from patients with diabetes, the average cutoff values for SUA in general population were 354.0 umol/L (95% CI: 318.9-393.2) and 361.0 umol/L (95% CI: 339.2-386.3), respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of receiver operating characteristic curve identifying the threshold of serum uric acid for DR and CKD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCut off points, umol/L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CIs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEntire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e354.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e318.9\u0026ndash;393.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e355.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e304.5\u0026ndash;408.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e352.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e286.5\u0026ndash;420.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCKD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEntire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e361.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e339.2\u0026ndash;386.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e361.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e330.4\u0026ndash;394.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e353.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e310.8 -400.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eDR: Diabetic Retinopathy, CKD: Chronic Kidney Disease, AUC: area under the curve, 95% CIs: 95% confidence intervals\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the entire population grouped according to the identified thresholds for a risk of DR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eLow SUA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh SUA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSUA range (median)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100.0-354.1 (280.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e354.1\u0026ndash;986.0 (408.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of subjects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e650\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e317 (48.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e272 (74.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.0 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e58.0 (15.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124.0 (97.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e122.0 (85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.20 (4.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e25.20 (4.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126.0 (22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e130.0 (21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.0 (12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e78.0 (14.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.50 (2.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e5.70 (2.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScr (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.6 (19.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e66.7 (20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eeGFR (mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102.44 (15.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e97.69 (18.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.79 (1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e4.86 (1.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.38 (0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1.72 (1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL - c (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.09 (0.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.98 (0.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL - c (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.72 (1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2.86 (1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALB (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.10 (6.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e45.30 (5.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1c (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.00 (2.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e7.70 (2.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlycated albumin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.96 (8.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e19.25 (7.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0h - PG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.10 (3.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e7.71 (2.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1h - PG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.31 (6.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e12.85 (4.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.481\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2h - PG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.01 (7.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e13.49 (6.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.326\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e169 (26.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e125 (34.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e481 (74.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e240 (65.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-VTDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143 (22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e98 (26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.299\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVTDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e27 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCKD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e192 (29.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e144 (39.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCKD1 (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146 (22.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e96 (26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCKD2 (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e32 (8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCKD3 (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e13 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300 (46.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e197 (54.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e139 (21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e133 (36.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e181 (27.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e146 (40.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSUA: Serum Uric Acid; BMI: Body Mass Index; SBP: Systolic Blood Pressure; DBP: Diastolic Blood Pressure; BUN: Blood Urea Nitrogen; Scr: Serum Creatinine; eGFR: Estimated Glomerular Filtration Rate; TC: Total Cholesterol; TG: Triglycerides; HDL-c: High-Density Lipoprotein Cholesterol; LDL-c: Low-Density Lipoprotein Cholesterol; ALB: Albumin; HbA1c: Hemoglobin A1c; PG: Plasma Glucose; DR: Diabetic Retinopathy; NDR: Non-Diabetic Retinopathy; VTDR: Vision-Threatening Diabetic Retinopathy; CKD: Chronic Kidney Disease; CKD1: Stage 1 CKD; CKD2: Stage 2 CKD; CKD3: Stage 3 CKD\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the analysis of DR, 650 patients exhibited SUA levels below 354.0 umol/L (low UA group), while 365 had a SUA level equal to or above 354.1 umol/L (high SUA group). Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e summarizes the clinical characteristics of these two groups. The average age of the high SUA group was lower compared to that of the low UA group (p\u0026thinsp;=\u0026thinsp;0.002). Patients in the high SUA group displayed higher systolic blood pressure (SBP), diastolic blood pressure (DBP), and a greater percentage in the history of hypertension, smoking and alcohol consumption compared to those in the low UA group. There were no significant differences between the two groups regarding diabetes duration and percentages of patients with NDR, non-VTDR, CKD1, and CKD3. In terms of laboratory parameters, BUN, Scr, TG levels were elevated in the high UA group compared to the low UA group (p\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;0.001 for all three parameters). However, there were no significant differences observed in TC and LDL-c levels between the two groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOrderly logistic regression analyses of the association between different levels of SUA and the prevalence of DR progression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eSUA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSUA range (median)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.0-354.0 (280.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e354.0-986.0 (408.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCrude Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.512 (1.148\u0026ndash;1.991)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage-adjusted Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.439 (1.090\u0026ndash;1.901)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultivariable-adjusted model \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.531 (1.138\u0026ndash;2.059)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultivariable-adjusted model \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.571 (1.136\u0026ndash;2.099)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSUA range (median)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e145.7-355.1 (289.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e355.1\u0026ndash;986.0 (409.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCrude Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.354 (0.960\u0026ndash;1.910)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage-adjusted Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.317 (0.932\u0026ndash;1.862)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultivariable-adjusted model \u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.523 (1.058\u0026ndash;2.191)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultivariable-adjusted model \u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.498 (1.017\u0026ndash;2.206)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSUA range (median)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.0-352.1 (268.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e352.1-604.5 (404.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCrude Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.607 (0.980\u0026ndash;2.635)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage-adjusted Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.537 (0.933\u0026ndash;2.532)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultivariable-adjusted model \u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.605 (0.967\u0026ndash;2.665)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultivariable-adjusted model \u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.818 (1.081\u0026ndash;3.058)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e1\u003c/sup\u003eAdjusted for age, sex, HbA1c and diabetes duration. \u003csup\u003e2\u003c/sup\u003eAdjusted for age, sex, diabetes duration, HbA1c, ALB, BUN, HDL-c, smoking status and eGFR. \u003csup\u003e3\u003c/sup\u003e Adjusted for age, HbA1c and diabetes duration. \u003csup\u003e4\u003c/sup\u003eAdjusted for age, diabetes duration, HbA1c, ALB, BUN, Cr, smoking status and eGFR. \u003csup\u003e5\u003c/sup\u003eAdjusted for age, diabetes duration, HbA1c, and glycated albumin.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eConsidering the sex of the patients, the clinical characteristics of individuals with high and low SUA levels were analyzed based on sex-specific cutoffs. The results are presented in table S2 for males and table S3 for females. The thresholds for SUA for DR worsening were 355.1 umol/L in men and 352.1 umol/L in women. The thresholds for SUA for CKD worsening were 361.0 umol/L in men and 353.6 umol/L in women. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e provides a summary of the sex-specific ideal cutoffs for DR and CKD as well as the ranges of sensitivity and specificity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eHigh SUA are independent risk factors for the progression of DR and CKD\u003c/h2\u003e \u003cp\u003eIn the analysis of univariate orderly logistic regression, there was a correlation between elevated SUA levels and an increased risk of DR progression in the overall population (OR, 1.512; 95% CI\u0026thinsp;=\u0026thinsp;1.148\u0026ndash;1.991; p\u0026thinsp;\u0026lt;\u0026thinsp;0.003). However, this association was not observed in either male (OR, 1.354; 95% CI\u0026thinsp;=\u0026thinsp;0.960\u0026ndash;1.910; p\u0026thinsp;=\u0026thinsp;0.084) or female (OR, 1.607; 95% CI\u0026thinsp;=\u0026thinsp;0.980\u0026ndash;2.635; p\u0026thinsp;=\u0026thinsp;0.060) subpopulations according to the crude model results. After adjusting for multiple variables, high SUA levels remained a significant risk factor for DR progression. In male patients, we noted a significant association between elevated SUA levels and an increased likelihood of developing DR in two different models. The ORs for the development of DR in individuals with high SUA levels compared to those with low SUA levels were 1.317 (95% CI, 0.932\u0026ndash;1.862; P\u0026thinsp;=\u0026thinsp;0.119) after adjusting for age, 1.523 (95% CI, 1.058\u0026ndash;2.191; P\u0026thinsp;=\u0026thinsp;0.024) in multivariable-adjusted model 3, and 1.498 (95% CI, 1.017\u0026ndash;2.206; P\u0026thinsp;=\u0026thinsp;0 .041) after adjusting for age, diabetes duration, HbA1c, ALB, BUN, Cr, smoking status and eGFR. In female patients, the association between elevated SUA levels and DR was found to be significant only when adjusting for age, diabetes duration, HbA1c, and glycated albumin. The results regarding ORs for developing CKD remained consistent across male and female groups. High SUA levels were identified as an independent risk factor in all four models analyzed (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOrderly logistic regression analyses of the association between different levels of SUA and the prevalence of CKD progression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eSUA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSUA range (median)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.0\u0026ndash;361.0 (284.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e361.0\u0026ndash;986.0 (415.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCrude Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.622 (1.245\u0026ndash;2.111)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage-adjusted Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.691 (1.296\u0026ndash;2.206)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultivariable-adjusted model \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.013 (1.516\u0026ndash;2.674)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultivariable-adjusted model \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.395 (1.033\u0026ndash;1.885)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSUA range (median)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.0\u0026ndash;361.0 (284.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e361.0\u0026ndash;986.0 (415.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCrude Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.687 (1.177\u0026ndash;2.417)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage-adjusted Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.743 (1.214\u0026ndash;2.501)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultivariable-adjusted model \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.213 (1.529\u0026ndash;3.202)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultivariable-adjusted model \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.518 (1.015\u0026ndash;2.269)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSUA range (median)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.0\u0026ndash;353.6 (280.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e353.6\u0026ndash;604.5 (408.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCrude Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.000 (1.270\u0026ndash;3.151)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage-adjusted Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.028 (1.297\u0026ndash;3.232)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultivariable-adjusted model \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.230 (1.401\u0026ndash;3.551)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultivariable-adjusted model \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.702 (1.035\u0026ndash;2.801)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e1\u003c/sup\u003eAdjusted for age, BMI, HbA1c and diabetes duration. \u003csup\u003e2\u003c/sup\u003eAdjusted for age, BMI, diabetes duration, HbA1c, ALB, BUN, TG, history of hypertension and eGFR.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this cross-sectional study, we observed a positive correlation between SUA levels and the severity of DR and CKD. Elevated SUA levels were found to be associated with a higher prevalence of both CKD and DR in diabetic patient independently of other well-known and potential risk factors. Logistic regression analysis revealed that for every 1 \u0026micro;mol/L increment in SUA level, there was a corresponding 0.2% increase in the risk of developing DR and a 0.5% increase in the risk of CKD progression.\u003c/p\u003e \u003cp\u003eIn the present study, the prevalence of DR among patients with diabetes for at least 5 years was 29.0%, and the prevalence of CKD was 33.1%. It is higher than the reported prevalence in Eastern China,[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] which is most likely due to the relatively long duration of diabetes history of the patients included in this study. Additionally, the currently acknowledged risk factors associated with DR or DN, [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] including the duration of diabetes, the younger age of onset of diabetes, and higher HbA1c levels were also reported in this study.\u003c/p\u003e \u003cp\u003eIt has been found that SUA levels in patients with T2DM increase with the severity of DR and the decline of renal function. [\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] In our study, we also observed a higher level of SUA in patients with more severe DR and relatively high levels of CKD. Of note, there was no significant difference in SUA levels between the CKD2 and CKD3 groups, possibly due to the small sample size of the CKD3 group. Several other studies published have also suggested that SUA may be an independent risk factor for DR.[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] Two large cross-sectional studies reported that SUA is associated with an increased risk of DR or more severe DR.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] In addition, higher quartiles of SUA were associated with an increased incidence of new-onset DR and progression to NPDR in two prospective cohort studies.[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] Our analyses indicated that higher levels of SUA were identified as independent risk factors for both DR and CKD, consistent with previous research findings. However, there are some studies that presented contrasting results regarding the association between SUA and DR. For example, a large-scale cross-sectional study involving 2961 patients with T2DM demonstrated an association between SUA levels and a higher prevalence of DN instead of DR.[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] Similarly, another cross-sectional study including 2809 patients reported that elevated concentrations of SUA independently increased the risk of DN but not DR. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] Overall, despite evidence that UA is associated with the development of DR and CKD, whether elevated UA is a cause or a consequence of microangiopathy is still controversial, and a large number of prospective studies are needed to elucidate the causality.\u003c/p\u003e \u003cp\u003eTo investigate the potential impact of SUA on disease mechanisms, various experimental and clinical studies have identified several possible connections between UA and diabetic microangiopathy. Elevated levels of SUA may contribute to the development of diabetic complications by disturbing insulin pathway, triggering inflammation, oxidative stress, and impairing endothelial function.[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] A cross-sectional study conducted on a large population discovered a correlation between SUA levels and proinflammatory cytokines, including IL-6, TNF-alpha, and CRP, which play a pivotal role in the pathophysiology of diabetic complications.[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] Zhu et al. found that UA increased apoptosis and inflammatory chemokine productions in human retinal endothelial cells exposed to high concentrations of UA. A Similar alteration was observed in animal experiments that rats with hyperuricemia exhibited elevated levels of inflammatory cytokines. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eOf note, there is sex difference in UA metabolism that males have higher circulating UA levels than females, as observed in our study. An increase in the risk of cardiovascular death (CVD) and SUA levels was associated with significant intergender differences.[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] However, the occurrence of diabetic complications in men does not always indicate a sex-specific susceptibility to UA. UA was reported to affect insulin function in both male and female populations. A recent study has revealed that there is an independent impact of SUA on insulin secretion among female patients, and in male patients, SUA was positively correlated with insulin secretion and insulin resistance index.[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] Clinical studies on DR showed that the sex-specific effect of SUA on microangiopathy is unclear. A cross-sectional study in Japan reported that higher SUA levels were associated with a high risk of developing DR in only males.[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] While another study showed that higher SUA levels are risk factor of VTDR in both sexes, it appears that females exhibited greater susceptibility to high SUA compared to males.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] Therefore, we conducted a sex‐stratified analysis in this study. The present study indicated a significant positive correlation between SUA levels and DR progression in both males and females after adjustment for potential risk factors, and females seemed to be more susceptible to increasement in UA levels. At present, the existence of sex differences in SUA for diabetic microangiopathy still needs more researches to be verified. There are arguments regarding the association between SUA and diabetes as well as its complications in females, which may be influenced by their menopausal status. Understanding sex differences at the mechanistic level remains challenging. Sex differences in vascular endothelial cell function and oxidant/antioxidant responses have been shown at the cellular level.[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eInvestigating the impact of interventions targeting UA levels on the progression of DR and nephropathy is another promising avenue. However, there is no consensus on the optimal target for SUA levels in patients with diabetes. UA exhibits physiological solubility up to approximately 6.4 mg/dL. UA-binding proteins contribute to enhancing solubility to around 7.0 mg/dL before reaching supersaturation. Beyond this point, crystallization of serum UA may occur, leading to the development of hyperuricemia.[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] Typically, hyperuricemia is defined as having UA levels exceeding 420 \u0026micro;mol/L for males and 360 \u0026micro;mol/L for females. Multiple studies have demonstrated that even when within a normal range, an elevated SUA level is linked to a higher prevalence of diabetic complications after adjusting for confounding factors.[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] Our results showed that in general population the threshold UA levels were 354.0 umol/L and 361.0 umol/L for DR and CKD occurrence, respectively. When considering the sex of the patients, it is interesting to note that the identified cutoff values for SUA associated with the worsening of DR were similar, and the SUA thresholds associated with CKD were only slightly higher in men than in women. The previous studies have not provided explicit data regarding the level of UA that contribute to the development of DR. However, there are researches indicating the threshold values for SUA in CVD and CKD. Virdis et al. identified critical threshold levels for UA associated with adverse outcomes that 4.7 mg/dL for all-cause mortality and 5.6 mg/dL for cardiovascular mortality.[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] Another cohort study revealed that in patients with T2DM, SUA levels exceeding 6.3 mg/dL (374.85 \u0026micro;mol/L) independently increased the risk of CKD progression.[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] Although there is no recommendation to initiate UA-lowering therapy in patients with asymptomatic hyperuricemia,[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] it is important to establish an optimal target range of SUA levels in patients with diabetes. On the one hand it helps to reduce the risk of developing diabetic complications, on the other hand, it is beneficial to avoid hypouricemia which has been observed to be associated with decreased renal function and increased mortality. [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eOur study has several limitations. Firstly, as a cross-sectional observational study and not an intervention study, no causal conclusions could be drawn. Secondly, a history of renin-angiotensin-aldosterone system indicators is absent in this study, which may be one of the important confounding factors that influence estimating the impact of high SUA level. Thirdly, the sample size in this study is not large enough, resulting in a small number of subjects with severer level of DR and CKD. Lastly, the assessment of DME with fundus pictures may be less reliable than the OCT imaging, leading to error of grouping.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, our study revealed a positive correlation between elevated SUA levels and the progression of both DR and CKD in Chinese individuals with at least a 5-year duration of diabetes, after adjustment for potential confounding factors. The increased risk of DR and worsening was found among subjects with a SUA level higher than 354.0 umol/L and 361.0 umol/L in total population, respectively, with no significant sex-differences. This finding provides evidence and possibilities for future studies to refine UA risk stratification and treatment interventions in patients with long-term diabetes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest Disclosures:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no financial/conflicting interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by National Natural Science Foundation of China (82171071), Program of Shanghai Academic/Technology Research Leader (21XD1402700).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHW performed the statistical analysis, and was a major contributor in writing the manuscript. LG and YM collected original data and pictures, and LG organized all data. XX, YQ, XS, XL, HW, QZ, YS, CC and LS read the fundus pictures. YW and KL conceived, organized and conducted this clinical study. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKhan MAB, Hashim MJ, King JK, Govender RD, Mustafa H, Al Kaabi J. Epidemiology of Type 2 Diabetes - Global Burden of Disease and Forecasted Trends. J Epidemiol Glob Health. 2020;10:107\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eForbes JM, Cooper ME. Mechanisms of diabetic complications. Physiol Rev. 2013;93:137\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eValencia WM, Florez H. How to prevent the microvascular complications of type 2 diabetes beyond glucose control. BMJ. 2017;356:i6505.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCallaghan BC, Xia R, Banerjee M, de Rekeneire N, Harris TB, Newman AB, et al. 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Identification of the Uric Acid Thresholds Predicting an Increased Total and Cardiovascular Mortality Over 20 Years. Hypertension. 2020;75:302\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChang YH, Lei CC, Lin KC, Chang DM, Hsieh CH, Lee YJ. Serum uric acid level as an indicator for CKD regression and progression in patients with type 2 diabetes mellitus-a 4.6-year cohort study. Diabetes Metab Res Rev. 2016;32:557\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSivera F, Andr\u0026eacute;s M, Carmona L, Kydd AS, Moi J, Seth R, et al. Multinational evidence-based recommendations for the diagnosis and management of gout: integrating systematic literature review and expert opinion of a broad panel of rheumatologists in the 3e initiative. Ann Rheum Dis. 2014;73:328\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark JH, Jo YI, Lee JH. Renal effects of uric acid: hyperuricemia and hypouricemia. Korean J Intern Med. 2020;35:1291\u0026ndash;304.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee CL, Tsai SF. Association between mortality and serum uric acid levels in non-diabetes-related chronic kidney disease: An analysis of the National Health and Nutrition Examination Survey, USA, 1999\u0026ndash;2010. Sci Rep. 2020;10:17585.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"diabetology-and-metabolic-syndrome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dims","sideBox":"Learn more about [Diabetology \u0026 Metabolic Syndrome](http://dmsjournal.biomedcentral.com/)","snPcode":"13098","submissionUrl":"https://submission.nature.com/new-submission/13098/3","title":"Diabetology \u0026 Metabolic Syndrome","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"serum uric acid, diabetic retinopathy, chronic kidney disease, diabetes mellitus","lastPublishedDoi":"10.21203/rs.3.rs-4757783/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4757783/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eAims\u003c/h2\u003e \u003cp\u003eTo assess the association between serum uric acid (SUA) level and the prevalence of diabetic retinopathy (DR) and chronic kidney disease (CKD) in patients with long-term diabetes.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional analysis was conducted involving diabetic patients from Shanghai General hospital during October 2018 and October 2021. Participants underwent measurements of SUA, renal function test and DR assessments via fundus photography. Multivariable ordinal logistic regression models assessed odd ratios (ORs) and 95% confidence intervals (95% CIs) for the progression of DR and CKD. Receiver operating characteristics (ROC) curves identified SUA thresholds, categorizing participants into low and high SUA groups.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong the 1015 patients with diabetes, SUA levels were higher in individuals with more sever CKD (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, compared with CKD1) and those with vision-threatening diabetic retinopathy (VTDR) (p\u0026thinsp;=\u0026thinsp;0.019, compared with no diabetic retinopathy (NDR)). Adjustments for potential confounders revealed that each 1 \u0026micro;mol/L increase in SUA was associated with an OR of 1.002 (95% CI: 1.001\u0026ndash;1.004) for DR and 1.008 (95% CI: 1.006\u0026ndash;1.011) for CKD. The risk of DR and CKD was elevated when SUA levels surpassed 354.0 \u0026micro;mol/L (95% CI: 318.9\u0026ndash;393.2) and 361.0 \u0026micro;mol/L (95% CI: 339.2\u0026ndash;386.3), respectively, with ORs of 1.571 (95% CI: 1.136\u0026ndash;2.099, P\u0026thinsp;=\u0026thinsp;0.006) for DR and 1.395 (95% CI: 1.033\u0026ndash;1.885, P\u0026thinsp;=\u0026thinsp;0.030) for CKD. Gender-specific analyses also demonstrated a positive correlation between higher SUA levels and the incidence of DR and CKD in both males and females.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eElevated SUA levels are independently associated with increased risks of DR and CKD, highlighting the importance of managing SUA levels in the patients with diabetes.\u003c/p\u003e","manuscriptTitle":"High Levels of Serum Uric Acid are Associated with Microvascular Complications in Patients with Long-term Diabetes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-18 22:59:21","doi":"10.21203/rs.3.rs-4757783/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-01-30T09:34:06+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-01-17T04:28:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"101105606767025103358088381594410429440","date":"2025-01-07T12:26:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"100464902428040310666586318024542358959","date":"2024-12-01T08:23:31+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-30T17:40:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"82371362794356140012190509870935538575","date":"2024-07-29T10:56:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-24T09:15:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-18T08:58:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-18T08:57:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"Diabetology \u0026 Metabolic Syndrome","date":"2024-07-17T17:03:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"diabetology-and-metabolic-syndrome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dims","sideBox":"Learn more about [Diabetology \u0026 Metabolic Syndrome](http://dmsjournal.biomedcentral.com/)","snPcode":"13098","submissionUrl":"https://submission.nature.com/new-submission/13098/3","title":"Diabetology \u0026 Metabolic Syndrome","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c4e3e2cb-6d60-4e78-b33f-5e2da4982af2","owner":[],"postedDate":"August 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-31T16:05:48+00:00","versionOfRecord":{"articleIdentity":"rs-4757783","link":"https://doi.org/10.1186/s13098-025-01656-1","journal":{"identity":"diabetology-and-metabolic-syndrome","isVorOnly":false,"title":"Diabetology \u0026 Metabolic Syndrome"},"publishedOn":"2025-03-28 15:57:44","publishedOnDateReadable":"March 28th, 2025"},"versionCreatedAt":"2024-08-18 22:59:21","video":"","vorDoi":"10.1186/s13098-025-01656-1","vorDoiUrl":"https://doi.org/10.1186/s13098-025-01656-1","workflowStages":[]},"version":"v1","identity":"rs-4757783","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4757783","identity":"rs-4757783","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}