Elevated serum uric acid level correlates with the severity of renal histopathology in IgA nephropathy and establishment of a nomogram model

Elevated serum uric acid level correlates with the severity of renal histopathology in IgA nephropathy and establishment of a nomogram model | 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 Elevated serum uric acid level correlates with the severity of renal histopathology in IgA nephropathy and establishment of a nomogram model Huifang Wang, Jun Liu, Chunhui Jiang, Xuemei Liu, Yan Xu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5904892/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background. IgA nephropathy (IgAN), the most common primary glomerulonephritis worldwide, is also a major cause of end stage renal disease (ESRD). We aimed to explore the relationship between the levels of serum uric acidand the degree of renal histopathological damage in patients with IgA nephropathy (IgAN) and build a nomogram model. Methods . It was a retrospective study. The clinical and histopathologicaldata of patients with primary IgAN diagnosed by renal biopsy were collected. Risk factors of severe renal histopathologicaldamage in IgAN patients were identified by logistic regression analysis. A nomogram model was established based on the multivariate logistic regression analysis. The C-index and calibration plots were used for the evaluation of the discrimination and calibration performance, respectively. Results . A total of 594 patients were retrospectively analyzedin the study. Compared with patients without hyperuricemia, patients with hyperuricemia had lower eGFR and higher body mass index, mean arterial pressure (MAP), hemoglobin, serum uric acid, triglycerides, IgA, complement 3, complement 4, proteinuria and severe renal histopathological damage ( p <0.05). Hemoglobin, serum uric acid, eGFR, IgA and proteinuria were identified and entered into the nomogram models. The C-index of this prediction model was 0.689 (95% CI 0.639–0.738). KM survival curve analysis showed that hyperuricemia and severe renal histopathological damage had a higher risk of progression to death or ESRD( p <0.001). Conclusions . Serum uric acid levels are independently associated with severe renal histopathological damage and poor prognosis in IgAN patients. IgA nephropathy serum uric acid kidney biopsy renal pathology Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide, characterized by the deposition predominantly of IgA in the glomerular mesangium, whereas the etiology and pathology of IgAN remain unclear[ 1 ]. Approximately, IgAN substantially accounts for nearly half of the primary glomerular diseases in China and one-third of IgAN patients progress to end stage renal disease (ESRD) within 20 to 30 years after diagnosis [ 2 ]. Due to the poor renal prognosis associated with IgA nephropathy, identifying modifiable risk factors for its progression is crucial. Currently, renal biopsy is the gold standard for the diagnosis of IgA nephropathy. The Oxford histopathological classification of IgAN developed by the International IgA Nephropathy Network has been widely used and can reflect the severity of renal pathological damage in IgAN [ 3 ]. Research has revealed that elevated uric acid levels are not merely a common complication of chronic kidney disease (CKD), but also an independent predictor of CKD advancement and the risk of cardiovascular mortality. Multiple studies indicate that hyperuricemia is an independent risk factor for the need for renal replacement therapy [ 4 , 5 ]. Research indicated that elevated uric acid levels independently predict the progression to CKD in individuals with normal renal function [ 6 , 7 ]. Nevertheless, IgAN is characterized by variation of pathological features, and much less is understood regarding histological changes related to elevated serum uric acid. In the present study, we aimed to explore the independent risk factors of severe renal histopathological damage in IgAN patients and build a nomogram model. The role of serum uric acid as an independent risk factor for severity of renal histopathological damage also was investigated. Methods Study Design This single center, retrospective, cross-sectional cohort study included primary IgAN patients who underwent kidney biopsies between January 2014 and January 2023 in the Affiliated Hospital of Qingdao University. Because the database used in this study did not contain personal identifiers, and the study was designed to be retrospective and observational, the requirement for informed consent was waived. The study adhered to all relevant tenets of the Declaration of Helsinki and was approved by the Ethics Committee of the Affiliated Hospital of Qingdao University (IRB approval no.: QYFY WZLL 28800). Data Collection and Definitions We included primary IgAN patients and a follow-up of at least 1 year. The exclusion criteria were: (1) age < 18 years; (2) no complete clinical data at baseline; (3) less than 8 glomeruli in renal biopsy specimens for light microscopic examination; (4) secondary IgAN, including systemic lupus erythematosus, Henoch-Schönlein purpura, viral hepatitis, human immunodeficiency virus (HIV) infection and antineutrophil cytoplasmic antibody related glomerulonephritis; (5) malignancy, infectious disease or other serious disease. The patients’ general information, vital signs [blood pressure (BP), heart rate], laboratory examination (creatinine, eGFR, SUA and proteinuria, etc.) and histologic features were measured in the Affiliated Hospital of Qingdao University at the time of kidney biopsy. Hyperuricemia was defined as a serum UA level > 7.0 mg/dL. The estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration equations (CKD-EPI) formula [ 8 ]. Histopathological Parameters Biopsies were scored according to the Oxford Classification of IgAN (MEST-C score) [ 9 ]. (1) absence/presence of mesangial hypercellularity (M0/M1): More than 50% of the mesangial cells in the mesangial area of the glomerulus are > 3, which can be diagnosed as M1. (2) absence/presence of endocapillary cellularity (E0/E1). (3) absence/presence of segmental sclerosis (S0/S1). (4) absence/presence of tubular atrophy/interstitial fibrosis (T0/T1/T2): tubular atrophy or interstitial fibrosis ≤ 25% is T0, 26%-50% is T1, and > 50% is T2. (5) absence/presence of crescents (C0/C1/C2): no crescent is C0, < 25% is C1, ≥ 25% is C2. The renal tissue pathology was completed by two pathologists from Qingdao University Hospital, who read the slides independently. According to the IgAN Oxford classification criteria, the patients were divided into mild renal pathological injury group (< 3 pathologic types) and severe renal pathological injury group (≥ 3 pathological types) [ 1 ]. Outcome Outcome The analysis aimed to evaluate the relationship between serum uric acid (SUA) levels and the severity of renal histopathological damage in IgAN patients. Patients were followed from the initial visit at the time of renal biopsy until the onset of ESRD, defined as eGFR < 15 mL/min/1.73 m 2 or the initiation of commencement of renal replacement therapy, or death from any cause, or until January 1, 2024. Statistical Analysis Statistical analysis was performed using statistical software SPSS 25.0 (SPSS, Chicago, IL). All numerical variables were expressed as mean ± standard deviation (SD) or median (interquartile range [IQR]). Categorical variables were expressed in number and frequency. Differences in quantitative data were compared using Student’s t tests or Mann–Whitney U tests, and the chi-square test was used for categorical data. A multivariate logistic regression analysis was used to describe the risk factors for severe renal histopathological damage in IgAN patients with kidney biopsies (only variables with P < 0.05 were imported into the model), and a nomogram prediction model was developed using a stepwise approach to identify useful combinations of factors to predict the degree of renal histopathological damage in IgAN patients. The C-index and calibration plot with bootstrap resampling were used to assess the discrimination and calibration of the models. The results were expressed as odds ratios (OR) and 95% confidence intervals (CI). In addition, Kaplan–Meier curves were used to analyze patients’ cumulative survival from death or ESRD. Univariate survival analysis was carried out using the log-rank test. P -values < 0.05 were considered statistically significant. Results Baseline characteristics A total of 594 patients were retrospectively analyzed (Figure 1) in this study, and the baseline characteristics of IgAN patients at the time of renal biopsy are shown in Table 1.The mean patient age was 42.20±13.42 years old, and 47.6% of patients were female. Compared with patients in the non-hyperuricemia group, patients in the hyperuricemia group had lower baseline eGFR ( p <0.05) and higher body mass index, mean arterial pressure (MAP), hemoglobin, serum uric acid, serum creatinine, serum urea nitrogen, triglycerides, IgA, complement 3, complement 4, proteinuria and severe renal histopathological damage (all p <0.05). In the IgAN Oxford Classification, the differences in M1, E1, S1 and C1-2 prevalence were not statistically significant in the hyperuricemia and non-hyperuricemia groups. But T1-2 and severe renal histopathological damage is higher in the hyperuricemia group compared with the non-hyperuricemia group ( p 0.05). Table 2 summarizes the differences in clinical data between IgAN patients with kidney biopsies according to the degree of renal histopathological damage. Compared with patients in the mild renal histopathological damage group, patients in the severe renal histopathological damage group had lower hemoglobin, eGFR ( p <0.05) and higher MAP, serum uric acid, serum creatinine, serum urea nitrogen, IgA, complement 3, URBC≥30/uL, proteinuria and corticosteroids and/or immunosuppressors (all p <0.05). During follow-up, the majority of patients (88.9%) received RASi treatment, and 184 (31.0%) patients received corticosteroids and/or immunosuppressive treatment. Associations between serum uric acid levels and renal histopathological damage degree In univariable and multivariable logistic regression analyses, the baseline serum uric acid levels were examined as continuous variable. Univariate analysis showed that low hemoglobin, low eGFR, high MAP, high serum uric acid, high triglycerides, high IgA, high complement 4, URBC≥30/uL, use of proteinuria and corticosteroids and/or immunosuppressors were correlated closely with severe renal histopathological damage ( Table 3 ). While after adjusting for potential confounders, multivariate logistic regression analysis showed that the significant independent factors associated with severe renal histopathological damage included hemoglobin (OR= 0.982; 95% CI : 0.972-0.993; p = 0.001), serum uric acid (OR= 1.203; 95% CI : 1.012-1.368; p = 0.026), eGFR (OR= 0.990; 95% CI : 0.983-0.997; p = 0.004), IgA (OR= 1.234; 95% CI : 1.025-1.486; p = 0.027) and proteinuria (OR= 1.182; 95% CI : 1.080-1.293; p <0.001, Table 3 ). Establish and validate the nomogram prognostic model Combining the above five factors, a nomogram model for predicting severe renal histopathological damage in IgAN patients was constructed, as shown in the Figure 2 . The C-indices for discrimination evaluation of this model was 0.689 (95% CI 0.639–0.738). The calibration against the nomogram model was also evaluated with the calibration curve ( Figure 3 ) and the figure shows that the predictions are close to the observed results, which further demonstrates the reliability of the nomogram model in predicting risk of severe renal histopathological damage in IgAN patients. Correlations between hyperuricemia, renal histopathological damage and outcome During a median follow-up time of 45.50(32.00, 67.00) months, 49 (8.2%) patients were into ESRD or death. As shown in Figure 4A , the Kaplan-Meier curve of the probability of ESRD or death in IgAN patients showed that patients with hyperuricemia was at a higher risk of progression to death or ESRD compared to patients without hyperuricemia (Kaplan Maier survival analysis, log rank test p <0.001, Figure 4A ). Patients having severe renal histopathological damage, showed a significantly lower survival from primary outcome as compared to those in the mild renal histopathological damage group (log rank test p <0.001, Figure 4B ). Table 1 Baseline characteristics and outcomes in IgAN patients with or without hyperuricemia. Variables Total ( n =594) Hyperuricemia ( n =184) Non-hyperuricemia ( n =410) P value Age, years (mean ± SD) 42.20±13.42 41.40±13.63 42.56±13.32 0.329 Female, n (%) 283(47.6) 89(48.4) 194(47.3) 0.812 Body mass index, kg/m 2 (median, IQR) 24.79(22.70, 27.70) 25.95(23.50, 28.79) 24.35(22.30, 26.83) <0.001 Systolic BP, mmHg (median, IQR) 136.00(126.00, 148.00) 141.00(130.00, 150.00) 134.00(123.75, 145.00) <0.001 Diastolic BP, mmHg (median, IQR) 84.00(76.00, 93.00) 87.00(80.00, 96.00) 82.00(75.00, 91.00) <0.001 MAP, mmHg (median, IQR) 101.33(94.00, 110.33) 104.67(97.00, 113.25) 99.33(92.00, 108.00) <0.001 Laboratory Hemoglobin, g/L (median, IQR) 133.00(120.00, 146.25) 139.00(121.25, 152.00) 131.00(120.00, 143.00) 0.002 Platelet counts, 10 9 /L (mean ± SD) 247.36±62.73 249.90 ±66.70 246.22±60.92 0.509 Serum uric acid, μmol/L (median, IQR) 364.75(301.75, 441.00) 482.50(446.50, 519.85) 329.00(279.03, 369.00) <0.001 Serum creatinine, μmol/L (median, IQR) 85.00(68.00, 112.00) 109.40(87.73, 139.45) 77.80(62.00, 96.00) <0.001 Serum urea nitrogen, mmol/L (median, IQR) 5.64(4.59, 7.52) 7.09(5.14, 9.37) 5.37(4.40, 6.68) <0.001 eGFR, ml/min/1.73m 2 (median, IQR) 86.58(62.29, 108.68) 69.44(45.04, 91.43) 93.58(70.63, 112.65) <0.001 Serum albumin, g/L (mean ± SD) 36.36±6.85 36.78±7.28 36.17±6.65 0.317 Triglycerides, mmol/L (median, IQR) 1.44(1.00, 2.07) 1.71(1.23, 2.37) 1.31(0.94, 1.90) <0.001 Total cholesterol, mmol/L (mean ± SD) 5.1±2.10 4.97±2.28 5.16±2.02 0.312 LDL-C, mmol/L (mean ± SD) 3.26±1.36 3.32±1.52 3.23±1.28 0.414 IgA, g/L (mean ± SD) 3.15±1.04 3.30±1.21 3.09±0.95 0.023 Complement 3 (g/L) (median, IQR) 1.06(0.91, 1.20) 1.10(0.93, 1.23) 1.04(0.91, 1.18) 0.033 Complement 4 (g/L) (median, IQR) 0.25(0.21, 0.30) 0.26(0.23, 0.32) 0.25(0.20, 0.29) 0.002 URBC≥30/uL, n (%) 291(49.0) 91(49.5) 200(48.8) 0.879 Proteinuria (g/day) (median, IQR) 1.32(0.68, 2.57) 1.79(0.96, 3.08) 1.15(0.63, 2.28) <0.001 Histological characteristics M1 (%) 443(74.6) 137(74.5) 306(74.6) 0.963 E1 (%) 115(19.4) 30(16.3) 85(20.7) 0.207 S1 (%) 319(53.7) 106(57.6) 213(52.0) 0.201 T1-2 (%) 90(15.2) 54(29.3) 36(8.8) <0.001 C1-2 (%) 78(13.1) 29(15.8) 49(12.0) 0.204 Severe renal histopathological damage, n (%) 147(24.7) 58(31.5) 89(21.7) 0.010 RASB treatment, n (%) 528(88.9) 162(88.0) 366(89.3) 0.661 Corticosteroids and/or immunosuppressors, n (%) 184(31.0) 63(34.2) 121(29.5) 0.249 ESRD and/or death, n (%) 49(8.2) 32(17.4) 17(4.1) <0.001 Data are presented as the mean ± standard deviation (SD), median (interquartile range), or number (percentage). Abbreviations: BP, blood pressure; eGFR, estimated glomerular filtration rate; ESRD: end stage renal disease; Low-density lipoprotein cholesterol; MAP, mean arterial pressure; RASB, renin-angiotensin system blockade; URBC, urinary red blood cell. Table 2 Baseline characteristics and outcomes in IgAN patients with kidney biopsies stratified by the degree of renal histopathological damage. Variables Severe renal histopathological damage ( n =147) Mild renal histopathological damage ( n =447) P value Age, years (mean ± SD) 41.18±13.41 42.54±13.42 0.287 Female, n (%) 76(51.7) 207(46.3) 0.256 Body mass index, kg/m 2 (mean ± SD) 25.57±3.91 25.18±3.97 0.298 Systolic BP, mmHg (mean ± SD) 139.97±17.20 136.38±17.52 0.031 Diastolic BP, mmHg (mean ± SD) 87.37±12.81 84.23±12.93 0.011 MAP, mmHg (mean ± SD) 104.91±13.22 101.62±13.31 0.009 Laboratory Hemoglobin, g/L (mean ± SD) 125.95±21.13 135.02±19.46 <0.001 Platelet counts, 10 9 /L (mean ± SD) 252.89±68.66 245.54±60.63 0.218 Serum uric acid, μmol/L (mean ± SD) 392.86±108.99 371.36±96.89 0.024 Serum creatinine, μmol/L (mean ± SD) 118.71±75.25 91.42±53.33 <0.001 Serum urea nitrogen, mmol/L (mean ± SD) 7.72±4.00 6.23±2.93 <0.001 eGFR, ml/min/1.73m 2 (mean ± SD) 74.24±32.77 88.35±29.13 <0.001 Serum albumin, g/L (mean ± SD) 35.89±6.46 36.52±6.98 0.335 Triglycerides, mmol/L (mean ± SD) 1.88±1.33 1.68±1.18 0.076 Total cholesterol, mmol/L (mean ± SD) 5.12±1.68 5.10±2.22 0.913 LDL-C, mmol/L (mean ± SD) 3.24±1.09 3.26±1.44 0.901 IgA, g/L (mean ± SD) 3.30±1.17 3.10±0.99 0.046 Complement 3 (g/L) (mean ± SD) 1.09±0.23 1.06±0.22 0.162 Complement 4 (g/L) (mean ± SD) 0.29±0.11 0.26±0.09 0.008 URBC≥30/uL, n (%) 83(56.5) 208(46.5) 0.037 Proteinuria (g/day) (mean ± SD) 2.64±2.08 1.81±1.97 <0.001 Histological characteristics M1 (%) 146(99.3) 297(66.4) <0.001 E1 (%) 67(45.6) 48(10.7) <0.001 S1 (%) 138(93.9) 181(40.5) <0.001 T1-2 (%) 70(47.6) 20(4.5) <0.001 C1-2 (%) 66(44.9) 12(2.7) <0.001 RASB treatment, n (%) 128(87.1) 400(89.5) 0.420 Corticosteroids and/or immunosuppressors, n (%) 58(39.5) 126(28.2) 0.010 ESRD and/or death, n (%) 26(17.7) 23(5.1) <0.001 Data are presented as the mean ± standard deviation (SD), median (interquartile range), or number (percentage). Abbreviations: BP, blood pressure; eGFR, estimated glomerular filtration rate; ESRD: end stage renal disease; Low-density lipoprotein cholesterol; MAP, mean arterial pressure; RASB, renin-angiotensin system blockade; URBC, urinary red blood cell. Table 3 Logistic regression analyses for severe renal histopathological damage in IgAN patients with kidney biopsies. Variables Univariable logistic regression Multivariable logistic regression β OR (95% CI ) P value β OR (95% CI ) P value Age, each year increase -0.008 0.992(0.978-1.006) 0.286 Female, sex -0.216 0.806(0.555-1.170) 0.257 Body mass index, each kg/m 2 increase 0.025 1.025(0.978-1.074) 0.298 MAP, each mmHg increase 0.018 1.018(1.004-1.032) 0.010 Hemoglobin, each g/L increase -0.023 0.978(0.968, 0.987) <0.001 -0.018 0.982(0.972-0.993) 0.001 Platelet counts, each 10 9 /L increase 0.002 1.002(0.999, 1.005) 0.218 Serum uric acid, each 100 μmol/L increase 0.210 1.233(1.027, 1.481) 0.015 0.185 1.203(1.012-1.368) 0.026 eGFR, each ml/min/1.73m 2 increase -0.015 0.985(0.978, 0.991) <0.001 -0.010 0.990(0.983-0.997) 0.004 Serum albumin, each g/dL increase -0.013 0.987(0.961, 1.014) 0.334 Triglycerides, each mmol/L increase 0.126 1.135(0.985, 1.307) 0.081 Total cholesterol, each mmol/L increase 0.005 1.005(0.920, 1.098) 0.913 LDL-C, mmol/L, each mmol/L increase -0.009 0.991(0.863, 1.138) 0.901 IgA, each g/L increase 0.177 1.193(1.002, 1.421) 0.047 0.210 1.234(1.025-1.486) 0.027 Complement 3, each g/L increase 0.598 1.818(0.786, 4.202) 0.162 Complement 4, each g/L increase 2.323 10.203(1.634, 63.707) 0.013 URBC≥30/uL 0.399 1.490(1.024, 2.169) 0.037 Proteinuria, each g/day increase 0.180 1.197(1.099, 1.304) <0.001 0.167 1.182(1.080-1.293) <0.001 RASB treatment, n (%) -0.234 0.792(0.448, 1.398) 0.421 Corticosteroids and/or immunosuppressors, n (%) 0.507 1.660(1.124, 2.451) 0.011 Abbreviations: eGFR, estimated glomerular filtration rate; Low-density lipoprotein cholesterol; MAP, mean arterial pressure; RASB, renin-angiotensin system blockade; URBC, urinary red blood cell. Discussion IgA nephropathy (IgAN) is one of the most widespread types of primary glomerulonephritis, which makes it one of the leading causes of ESRD. For unknown reasons, the clinical and histopathological manifestations of IgAN exhibit a wide range of variability. The Oxford histopathological classification of IgAN has been widely used to reflect the severity of renal pathological damage in IgAN [3]. Therefore, it is essential to emphasize the importance of early detection of risk factors associated with the degree of renal histopathological damage in IgAN patients, as well as interventions aimed at delaying disease progression and preventing ESRD. Nevertheless, IgAN is characterized by variation of pathological features, and a few studies have investigated the serum uric acid and degree of histopathological damage of IgAN patients. In this study, we conducted a retrospective analysis to explore the independent risk factors for severe renal histopathological damage in IgAN patients and to establish a predictive model, while also investigating the impact of serum uric acid on renal pathology and prognosis. Currently, clinical predictive models, which statistically analyze various clinical data, are being increasingly applied in clinical diagnosis and treatment decision-making. Nomograms, which are based on multivariate regression analysis to predict the incidence of certain clinical outcomes, are one of the most widely used statistical methods in clinical research [10]. This study applied nomograms to the risk study of the degree of renal histopathological damage in patients with IgAN. The nomogram models we developed showed that hemoglobin, serum uric acid, eGFR, IgA and proteinuria may be used as independent risk factors for severe renal histopathological damage in patients with IgAN. Among the histological parameters evaluated, tubular atrophy/interstitial fibrosis which can lead to renal interstitial fibrosis at a later stage was identified as the strongest risk factor for the progression of IgAN [4, 11], suggesting that elevated serum uric acid levels may independently contribute to the progression of IgAN by causing damage to the tubulointerstitial tissue [11]. Previous studies have confirmed that hyperuricemia is an independent risk factor for the progression of tubular atrophy/interstitial fibrosis in patients with IgAN [11, 12]. Our study also found that the hyperuricemia group had higher tubular atrophy/interstitial fibrosis compared to the non-hyperuricemia group in patients with IgAN (29.3% versus 8.8%, p <0.001). Several possible mechanisms have been proposed to explain the development of serum uric acid induced histological lesions, including oxidative stress, alteration of the nitric oxide pathway, insulin resistance, inflammatory activation, and stimulation of the renin-angiotensin system [13]. Serum uric acid can also induce phenotypic transitions of epithelial and endothelial cells [14] and cause kidney damage through Th1/Th2 polarization and the expression of extracellular matrix genes [15], which may be one of the mechanisms. However, the increase in serum uric acid levels may be due to a low eGFR, which leads to a reduction in the excretion of uric acid. We also found that severe renal histopathological damage correlates with decreased eGFR in patients with IgAN. Therefore, further clinical studies are required to investigate the correlation between renal histopathological damage and prognosis in patients with IgAN. Additionally, this study found that a decrease in hemoglobin is an independent risk factor for severe renal pathological damage in IgAN patients. These findings have been reported in previous studies and may be related to anemia as one of the frequent complications of CKD. Anemia might lead to hypoxic injury in kidneys through the hypoxia-inducible factor (HIF) signaling pathway [16]. Previous studies have indicated an association between anemia-induced hypoxia and glomerular disease through the HIF signaling pathway. This HIF pathway in turn damages podocytes, promotes the excretion of proteinuria, and accelerates the progression of glomerular diseases [17]. Another important cause of renal anemia is the insufficient production of erythropoietin (EPO), which may be related to severe renal histopathological damage in IgAN. Erythropoietin-producing cells are essentially renal interstitial fibroblasts [18], and under the action of hypoxia, this trigger regulates the production of EPO through the PHD2-HIF2α-EPO signaling pathway [19]. This suggests that anemia is closely related to the degree of more severe renal lesions in IgAN, especially tubulointerstitial damage. Hypoxic damage to the glomerulus and tubulointerstitium caused by anemia could account for the link between anemia and poor renal prognosis. This study also found that high IgA was closely related to the severity of renal histopathological damage in IgAN. IgA nephropathy is generally presumed to be IgA immune complex or polymerized IgA-mediated glomerulonephritis. Accumulated mesangial IgA triggers the activation of the complement protein C3, resulting in the activation of macrophages that release inflammatory cytokines and extracellular matrix components [20]. Ishiguro et al. [21] reported that patients with IgAN have higher serum IgA levels and lower C3 levels compared to non-IgA nephropathy, and these are closely related to the prediction of the diagnosis and prognostic grading in patients with IgAN. Yasuhiko et al. presented that elevated IgA plays an important role in assessing hematuria and persistent proteinuria and combined evaluation of serum IgA/C3 and glomerular C3 staining can predict IgAN prognosis [22]. Our study has several limitations. First, our study was a retrospective single-center cohort design, and no cause-and-effect relationships can be inferred between serum uric acid and renal histopathological damage. Second, the exact mechanism of serum uric acid involvement in renal histopathological damage is unclear. Furthermore, the prediction model formulated in this study requires additional external verification for confirmation. Therefore, further well-designed multicenter prospective cohort studies with longer regular follow-up and larger sample sizes are needed. Conclusion Hyperuricemia appeared to be a common symptom in IgAN. We have found that elevated serum uric acid levels were independently associated with severe renal histopathological damage and poor prognosis in patients with IgAN. Serum uric acid, as a factor contributing to more severe renal histopathological damage, is crucial for guiding treatment decisions and assessing prognosis. Declarations Conflict of interest statement The authors declare that they have no conflicts of interest. Funding This study was funded by Qingdao Key Health Discipline Development Fund, Qingdao Key Clinical Specialty Elite Discipline, Taishan Scholar Program of Shandong Province [No. tstp20230665] and Qingdao University Affiliated Hospital “Clinical Medicine + X” (QDFY + X2023208, QDFY + X2023106). Author Contribution H.W.: wrote the main manuscript text. J.L.: prepared figures. C.J.: prepared tables. X.L. and Y.X. review and edit the manuscript. All authors reviewed the manuscript. Acknowledgments The authors sincerely thank all the patients who took part in this study and the funding support. Data availability statement The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. References Tomino Y, Sakai H: Clinical guidelines for immunoglobulin A (IgA) nephropathy in Japan, second version. CLIN EXP NEPHROL 2003, 7(2):93-97. D'Amico G: Natural history of idiopathic IgA nephropathy: role of clinical and histological prognostic factors. AM J KIDNEY DIS 2000, 36(2):227-237. Barbour SJ, Espino-Hernandez G, Reich HN, Coppo R, Roberts IS, Feehally J, Herzenberg AM, Cattran DC: The MEST score provides earlier risk prediction in lgA nephropathy. KIDNEY INT 2016, 89(1):167-175. Zhu B, Yu DR, Lv JC, Lin Y, Li Q, Yin JZ, Du YY, Tang XL, Mao LC, Li QF et al : Uric Acid as a Predictor of Immunoglobulin A Nephropathy Progression: A Cohort Study of 1965 Cases. AM J NEPHROL 2018, 48(2):127-136. Le W, Liang S, Hu Y, Deng K, Bao H, Zeng C, Liu Z: Long-term renal survival and related risk factors in patients with IgA nephropathy: results from a cohort of 1155 cases in a Chinese adult population. NEPHROL DIAL TRANSPL 2012, 27(4):1479-1485. Obermayr RP, Temml C, Gutjahr G, Knechtelsdorfer M, Oberbauer R, Klauser-Braun R: Elevated uric acid increases the risk for kidney disease. J AM SOC NEPHROL 2008, 19(12):2407-2413. Kohagura K, Kochi M, Miyagi T, Kinjyo T, Maehara Y, Nagahama K, Sakima A, Iseki K, Ohya Y: An association between uric acid levels and renal arteriolopathy in chronic kidney disease: a biopsy-based study. HYPERTENS RES 2013, 36(1):43-49. 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Choi WJ, Hong YA, Min JW, Koh ES, Kim HD, Ban TH, Kim YS, Kim YK, Shin SJ, Kim SY et al : The Serum Uric Acid Level Is Related to the More Severe Renal Histopathology of Female IgA Nephropathy Patients. J CLIN MED 2021, 10(9). Zhu W, Liang A, Shi P, Yuan S, Zhu Y, Fu J, Zheng T, Wen Z, Wu X: Higher serum uric acid to HDL-cholesterol ratio is associated with onset of non-alcoholic fatty liver disease in a non-obese Chinese population with normal blood lipid levels. BMC GASTROENTEROL 2022, 22(1):196. Kang DH: Hyperuricemia and Progression of Chronic Kidney Disease: Role of Phenotype Transition of Renal Tubular and Endothelial Cells. CONTRIB NEPHROL 2018, 192:48-55. Tomino Y: IgA nephropathy: lessons from an animal model, the ddY mouse. J NEPHROL 2008, 21(4):463-467. Ito M, Tanaka T, Ishii T, Wakashima T, Fukui K, Nangaku M: Prolyl hydroxylase inhibition protects the kidneys from ischemia via upregulation of glycogen storage. KIDNEY INT 2020, 97(4):687-701. Matoba K, Kawanami D, Okada R, Tsukamoto M, Kinoshita J, Ito T, Ishizawa S, Kanazawa Y, Yokota T, Murai N et al : Rho-kinase inhibition prevents the progression of diabetic nephropathy by downregulating hypoxia-inducible factor 1alpha. KIDNEY INT 2013, 84(3):545-554. Yasuoka Y, Izumi Y, Fukuyama T, Oshima T, Yamazaki T, Uematsu T, Kobayashi N, Nanami M, Shimada Y, Nagaba Y et al : Tubular Endogenous Erythropoietin Protects Renal Function against Ischemic Reperfusion Injury. INT J MOL SCI 2024, 25(2). Suzuki N: Erythropoietin gene expression: developmental-stage specificity, cell-type specificity, and hypoxia inducibility. TOHOKU J EXP MED 2015, 235(3):233-240. Selvaskandan H, Shi S, Twaij S, Cheung CK, Barratt J: Monitoring Immune Responses in IgA Nephropathy: Biomarkers to Guide Management. FRONT IMMUNOL 2020, 11:572754. Ishiguro C, Yaguchi Y, Funabiki K, Horikoshi S, Shirato I, Tomino Y: Serum IgA/C3 ratio may predict diagnosis and prognostic grading in patients with IgA nephropathy. NEPHRON 2002, 91(4):755-758. Tomino Y, Suzuki S, Imai H, Saito T, Kawamura T, Yorioka N, Harada T, Yasumoto Y, Kida H, Kobayashi Y et al : Measurement of serum IgA and C3 may predict the diagnosis of patients with IgA nephropathy prior to renal biopsy. J CLIN LAB ANAL 2000, 14(5):220-223. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5904892","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":407687770,"identity":"720a261a-e746-4a2a-ad3c-26ad5b6892a5","order_by":0,"name":"Huifang Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYBACNmbmAwck/7DVgxjEaeFjZ0s8YNnAl8DP3pZAnBY5fh7jA5UNcgmSPWcMiHUYg8GBmzvM8gxu5Hy88YbBTk63gbCWhIMzz6QVG9zI3Ww5hyHZ2OwAYS0HDkuwHWPccCN3mzQPw4HEbYS1MDYc/sP2H6gl5xmxWoDWSLaxJc7sOcNGrBY2hgMSZ9iMgYFsbDnHgAi/yPef//xBooJNDmjdwxtvKuzkCGpBARI8REYNshZSdYyCUTAKRsGIAADnT0GCWAs4wgAAAABJRU5ErkJggg==","orcid":"","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":true,"prefix":"","firstName":"Huifang","middleName":"","lastName":"Wang","suffix":""},{"id":407687771,"identity":"c358b217-bcd3-4323-a0b1-e5f1d2b0558f","order_by":1,"name":"Jun Liu","email":"","orcid":"","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Liu","suffix":""},{"id":407687772,"identity":"8cab4681-708b-4423-a50f-5b693ea538e7","order_by":2,"name":"Chunhui Jiang","email":"","orcid":"","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":false,"prefix":"","firstName":"Chunhui","middleName":"","lastName":"Jiang","suffix":""},{"id":407687773,"identity":"fc845d14-5fd7-4f3e-80a1-9fd1ea766bd1","order_by":3,"name":"Xuemei Liu","email":"","orcid":"","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":false,"prefix":"","firstName":"Xuemei","middleName":"","lastName":"Liu","suffix":""},{"id":407687774,"identity":"df2f74e4-0577-4dc7-8a01-373804c59c0a","order_by":4,"name":"Yan Xu","email":"","orcid":"","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2025-01-26 06:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5904892/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5904892/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":75408523,"identity":"aba12cc6-5586-40ec-a9f1-9be205004020","added_by":"auto","created_at":"2025-02-04 09:00:15","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":30783,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram for the study population.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5904892/v1/9b5f1b4066ea38c4dc820840.jpg"},{"id":75408529,"identity":"0fc7ff81-4cf0-4f20-9bca-5287ec74cb65","added_by":"auto","created_at":"2025-02-04 09:00:16","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":242157,"visible":true,"origin":"","legend":"\u003cp\u003eNomogram predicts risk of severe renal histopathological damage in IgAN patients.\u003c/p\u003e\n\u003cp\u003eCalculation method: The value of each predictive parameter corresponds upward to the value on the Point axis, and then the “Points” values of all parameters are summed to correspond to the value on the “total points” axis, and downward to the risk of severe renal histopathological damage in IgAN patients.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5904892/v1/ba889edb5fecc9ba15a27c4a.jpg"},{"id":75406361,"identity":"c7102e71-5571-4cff-b186-0a16c906c8e3","added_by":"auto","created_at":"2025-02-04 08:52:16","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":52247,"visible":true,"origin":"","legend":"\u003cp\u003eCalibration of the nomogram for severe renal histopathological damage in IgAN patients. The x-axis shows the predicted probability of risk of severe renal histopathological damage in IgAN, and the y-axis shows the observed probability of risk of severe renal histopathological damage in IgAN.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5904892/v1/0626dba5f861695562af33e3.jpg"},{"id":75406365,"identity":"9aa47f51-4f6b-4459-bf6f-fbd9b3f811b9","added_by":"auto","created_at":"2025-02-04 08:52:16","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":106865,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier curves of survival without death or ESRD for IgAN patients on the basis of hyperuricemia (A, log-rank test, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) and degree of renal pathological damage (B, log-rank test, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5904892/v1/f8a86e8b251e55f46495261b.jpg"},{"id":78225656,"identity":"1a41444f-02e7-469a-8802-4370e679e4b0","added_by":"auto","created_at":"2025-03-11 06:53:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1351205,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5904892/v1/d4004168-43ae-4d7c-b0ce-321a7ce0f5bf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Elevated serum uric acid level correlates with the severity of renal histopathology in IgA nephropathy and establishment of a nomogram model","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide, characterized by the deposition predominantly of IgA in the glomerular mesangium, whereas the etiology and pathology of IgAN remain unclear[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Approximately, IgAN substantially accounts for nearly half of the primary glomerular diseases in China and one-third of IgAN patients progress to end stage renal disease (ESRD) within 20 to 30 years after diagnosis [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Due to the poor renal prognosis associated with IgA nephropathy, identifying modifiable risk factors for its progression is crucial. Currently, renal biopsy is the gold standard for the diagnosis of IgA nephropathy. The Oxford histopathological classification of IgAN developed by the International IgA Nephropathy Network has been widely used and can reflect the severity of renal pathological damage in IgAN [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eResearch has revealed that elevated uric acid levels are not merely a common complication of chronic kidney disease (CKD), but also an independent predictor of CKD advancement and the risk of cardiovascular mortality. Multiple studies indicate that hyperuricemia is an independent risk factor for the need for renal replacement therapy [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Research indicated that elevated uric acid levels independently predict the progression to CKD in individuals with normal renal function [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Nevertheless, IgAN is characterized by variation of pathological features, and much less is understood regarding histological changes related to elevated serum uric acid.\u003c/p\u003e \u003cp\u003eIn the present study, we aimed to explore the independent risk factors of severe renal histopathological damage in IgAN patients and build a nomogram model. The role of serum uric acid as an independent risk factor for severity of renal histopathological damage also was investigated.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThis single center, retrospective, cross-sectional cohort study included primary IgAN patients who underwent kidney biopsies between January 2014 and January 2023 in the Affiliated Hospital of Qingdao University. Because the database used in this study did not contain personal identifiers, and the study was designed to be retrospective and observational, the requirement for informed consent was waived. The study adhered to all relevant tenets of the Declaration of Helsinki and was approved by the Ethics Committee of the Affiliated Hospital of Qingdao University (IRB approval no.: QYFY WZLL 28800).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Collection and Definitions\u003c/h3\u003e\n\u003cp\u003eWe included primary IgAN patients and a follow-up of at least 1 year. The exclusion criteria were: (1) age\u0026thinsp;\u0026lt;\u0026thinsp;18 years; (2) no complete clinical data at baseline; (3) less than 8 glomeruli in renal biopsy specimens for light microscopic examination; (4) secondary IgAN, including systemic lupus erythematosus, Henoch-Sch\u0026ouml;nlein purpura, viral hepatitis, human immunodeficiency virus (HIV) infection and antineutrophil cytoplasmic antibody related glomerulonephritis; (5) malignancy, infectious disease or other serious disease.\u003c/p\u003e \u003cp\u003eThe patients\u0026rsquo; general information, vital signs [blood pressure (BP), heart rate], laboratory examination (creatinine, eGFR, SUA and proteinuria, etc.) and histologic features were measured in the Affiliated Hospital of Qingdao University at the time of kidney biopsy. Hyperuricemia was defined as a serum UA level\u0026thinsp;\u0026gt;\u0026thinsp;7.0 mg/dL. The estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration equations (CKD-EPI) formula [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eHistopathological Parameters\u003c/h3\u003e\n\u003cp\u003eBiopsies were scored according to the Oxford Classification of IgAN (MEST-C score) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. (1) absence/presence of mesangial hypercellularity (M0/M1): More than 50% of the mesangial cells in the mesangial area of the glomerulus are \u0026gt;\u0026thinsp;3, which can be diagnosed as M1. (2) absence/presence of endocapillary cellularity (E0/E1). (3) absence/presence of segmental sclerosis (S0/S1). (4) absence/presence of tubular atrophy/interstitial fibrosis (T0/T1/T2): tubular atrophy or interstitial fibrosis\u0026thinsp;\u0026le;\u0026thinsp;25% is T0, 26%-50% is T1, and \u0026gt;\u0026thinsp;50% is T2. (5) absence/presence of crescents (C0/C1/C2): no crescent is C0, \u0026lt;\u0026thinsp;25% is C1, \u0026ge;\u0026thinsp;25% is C2. The renal tissue pathology was completed by two pathologists from Qingdao University Hospital, who read the slides independently. According to the IgAN Oxford classification criteria, the patients were divided into mild renal pathological injury group (\u0026lt;\u0026thinsp;3 pathologic types) and severe renal pathological injury group (\u0026ge;\u0026thinsp;3 pathological types) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eOutcome\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eOutcome\u003c/div\u003e \u003cp\u003eThe analysis aimed to evaluate the relationship between serum uric acid (SUA) levels and the severity of renal histopathological damage in IgAN patients. Patients were followed from the initial visit at the time of renal biopsy until the onset of ESRD, defined as eGFR\u0026thinsp;\u0026lt;\u0026thinsp;15 mL/min/1.73 m\u003csup\u003e2\u003c/sup\u003e or the initiation of commencement of renal replacement therapy, or death from any cause, or until January 1, 2024.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed using statistical software SPSS 25.0 (SPSS, Chicago, IL). All numerical variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or median (interquartile range [IQR]). Categorical variables were expressed in number and frequency. Differences in quantitative data were compared using Student\u0026rsquo;s t tests or Mann\u0026ndash;Whitney U tests, and the chi-square test was used for categorical data. A multivariate logistic regression analysis was used to describe the risk factors for severe renal histopathological damage in IgAN patients with kidney biopsies (only variables with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were imported into the model), and a nomogram prediction model was developed using a stepwise approach to identify useful combinations of factors to predict the degree of renal histopathological damage in IgAN patients. The C-index and calibration plot with bootstrap resampling were used to assess the discrimination and calibration of the models. The results were expressed as odds ratios (OR) and 95% confidence intervals (CI). In addition, Kaplan\u0026ndash;Meier curves were used to analyze patients\u0026rsquo; cumulative survival from death or ESRD. Univariate survival analysis was carried out using the log-rank test. \u003cem\u003eP\u003c/em\u003e-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBaseline characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 594 patients were retrospectively analyzed (Figure 1) in this study, and the baseline characteristics of IgAN patients at the time of renal biopsy are shown in Table 1.The mean patient age was 42.20\u0026plusmn;13.42 years old, and 47.6% of patients were female. Compared with patients in the non-hyperuricemia group, patients in the hyperuricemia group had lower baseline eGFR (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05) and higher body mass index, mean arterial pressure (MAP), hemoglobin, serum uric acid, serum creatinine, serum urea nitrogen, triglycerides, IgA, complement 3, complement 4, proteinuria and severe renal histopathological damage (all \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). In the IgAN Oxford Classification, the differences in M1, E1, S1 and C1-2 prevalence were not statistically significant in the hyperuricemia and non-hyperuricemia groups. But T1-2 and severe renal histopathological damage is higher in the hyperuricemia group compared with the non-hyperuricemia group (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). However, there were no differences in other factors in \u003cstrong\u003eTable 1\u003c/strong\u003e between IgAN patients with or without hyperuricemia (\u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e summarizes the differences in clinical data between IgAN patients with kidney biopsies according to the degree of renal histopathological damage. Compared with patients in the mild renal histopathological damage group, patients in the severe renal histopathological damage group had lower hemoglobin, eGFR (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05) and higher MAP, serum uric acid, serum creatinine, serum urea nitrogen, IgA, complement 3, URBC\u0026ge;30/uL, proteinuria and corticosteroids and/or immunosuppressors (all \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). During follow-up, the majority of patients (88.9%) received RASi treatment, and 184 (31.0%) patients received corticosteroids and/or immunosuppressive treatment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociations between serum uric acid levels and renal histopathological damage degree\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn univariable and multivariable logistic regression analyses, the baseline serum uric acid levels were examined as continuous variable. Univariate analysis showed that low hemoglobin, low eGFR, high MAP, high serum uric acid, high triglycerides, high IgA, high complement 4, URBC\u0026ge;30/uL, use of proteinuria and corticosteroids and/or immunosuppressors were correlated closely with severe renal\u0026nbsp;histopathological\u0026nbsp;damage\u0026nbsp;(\u003cstrong\u003eTable 3\u003c/strong\u003e). While after adjusting for potential confounders, multivariate logistic regression analysis showed that the significant independent factors associated with severe renal\u0026nbsp;histopathological\u0026nbsp;damage\u0026nbsp;included hemoglobin (OR=\u0026nbsp;0.982; 95% \u003cem\u003eCI\u003c/em\u003e:\u0026nbsp;0.972-0.993; \u003cem\u003ep\u0026nbsp;\u003c/em\u003e=\u0026nbsp;0.001), serum uric acid (OR=\u0026nbsp;1.203; 95% \u003cem\u003eCI\u003c/em\u003e:\u0026nbsp;1.012-1.368; \u003cem\u003ep\u0026nbsp;\u003c/em\u003e=\u0026nbsp;0.026), eGFR (OR=\u0026nbsp;0.990; 95% \u003cem\u003eCI\u003c/em\u003e:\u0026nbsp;0.983-0.997; \u003cem\u003ep\u0026nbsp;\u003c/em\u003e=\u0026nbsp;0.004),\u0026nbsp;IgA\u0026nbsp;(OR=\u0026nbsp;1.234; 95% \u003cem\u003eCI\u003c/em\u003e:\u0026nbsp;1.025-1.486; \u003cem\u003ep\u0026nbsp;\u003c/em\u003e=\u0026nbsp;0.027) and proteinuria (OR=\u0026nbsp;1.182; 95% \u003cem\u003eCI\u003c/em\u003e: 1.080-1.293; \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt;0.001,\u0026nbsp;\u003cstrong\u003eTable 3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstablish and validate the nomogram prognostic model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCombining the above five factors, a nomogram model for predicting severe renal histopathological damage in IgAN patients was constructed, as shown in the \u003cstrong\u003eFigure 2\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eThe C-indices for discrimination evaluation of this model was 0.689 (95% CI 0.639\u0026ndash;0.738). The calibration against the nomogram model was also evaluated with the calibration curve (\u003cstrong\u003eFigure 3\u003c/strong\u003e) and the figure shows that the predictions are close to the observed results, which further demonstrates the reliability of the nomogram model in predicting risk of severe renal histopathological damage in IgAN patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelations between hyperuricemia, renal\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ehistopathological\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;damage\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and outcome\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring a median follow-up time of 45.50(32.00, 67.00) months, 49 (8.2%) patients were into ESRD or death. As shown in\u003cstrong\u003e\u0026nbsp;Figure 4A\u003c/strong\u003e, the Kaplan-Meier curve of the probability of ESRD or death in IgAN patients showed that patients with hyperuricemia was at a higher risk of progression to death or ESRD compared to patients without hyperuricemia (Kaplan Maier survival analysis, log rank test \u003cem\u003ep\u003c/em\u003e \u0026lt;0.001, \u003cstrong\u003eFigure 4A\u003c/strong\u003e). Patients having severe renal histopathological damage, showed a significantly lower survival from primary outcome as compared to those in the mild renal histopathological damage group (log rank test \u003cem\u003ep\u003c/em\u003e \u0026lt;0.001, \u003cstrong\u003eFigure 4B\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003e Baseline characteristics and outcomes in IgAN patients with or without hyperuricemia.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"678\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003en\u003c/em\u003e=594)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eHyperuricemia (\u003cem\u003en\u003c/em\u003e=184)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eNon-hyperuricemia\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003en\u003c/em\u003e=410)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eAge, years (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e42.20\u0026plusmn;13.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e41.40\u0026plusmn;13.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e42.56\u0026plusmn;13.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.329\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eFemale, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e283(47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e89(48.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e194(47.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.812\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eBody mass index, kg/m\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e(median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e24.79(22.70, 27.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e25.95(23.50, 28.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e24.35(22.30, 26.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eSystolic\u0026nbsp;BP,\u0026nbsp;mmHg\u0026nbsp;(median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e136.00(126.00, 148.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e141.00(130.00, 150.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e134.00(123.75, 145.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eDiastolic BP, mmHg (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e84.00(76.00, 93.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e87.00(80.00, 96.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e82.00(75.00, 91.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eMAP, mmHg\u0026nbsp;(median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e101.33(94.00, 110.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e104.67(97.00, 113.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e99.33(92.00, 108.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eHemoglobin, g/L (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e133.00(120.00, 146.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e139.00(121.25, 152.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e131.00(120.00, 143.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003ePlatelet counts, 10\u003csup\u003e9\u003c/sup\u003e/L (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e247.36\u0026plusmn;62.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e249.90 \u0026plusmn;66.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e246.22\u0026plusmn;60.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.509\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eSerum uric acid, \u0026mu;mol/L (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e364.75(301.75, 441.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e482.50(446.50, 519.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e329.00(279.03, 369.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eSerum creatinine, \u0026mu;mol/L\u0026nbsp;(median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e85.00(68.00, 112.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e109.40(87.73, 139.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e77.80(62.00, 96.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eSerum urea nitrogen, mmol/L (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e5.64(4.59, 7.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e7.09(5.14, 9.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e5.37(4.40, 6.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eeGFR, ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e86.58(62.29, 108.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e69.44(45.04, 91.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e93.58(70.63, 112.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eSerum albumin, g/L (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e36.36\u0026plusmn;6.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e36.78\u0026plusmn;7.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e36.17\u0026plusmn;6.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.317\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eTriglycerides, mmol/L\u0026nbsp;(median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.44(1.00, 2.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.71(1.23, 2.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e1.31(0.94, 1.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eTotal cholesterol, mmol/L (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e5.1\u0026plusmn;2.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e4.97\u0026plusmn;2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e5.16\u0026plusmn;2.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.312\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eLDL-C, mmol/L (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3.26\u0026plusmn;1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3.32\u0026plusmn;1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e3.23\u0026plusmn;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.414\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eIgA, g/L\u0026nbsp;(mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3.15\u0026plusmn;1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3.30\u0026plusmn;1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e3.09\u0026plusmn;0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eComplement 3 (g/L) (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.06(0.91, 1.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.10(0.93, 1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e1.04(0.91, 1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eComplement 4 (g/L) (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e0.25(0.21, 0.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e0.26(0.23, 0.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.25(0.20, 0.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eURBC\u0026ge;30/uL, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e291(49.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e91(49.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e200(48.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.879\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eProteinuria (g/day) (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.32(0.68, 2.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.79(0.96, 3.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e1.15(0.63, 2.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistological characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eM1 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e443(74.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e137(74.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e306(74.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.963\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eE1 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e115(19.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e30(16.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e85(20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eS1 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e319(53.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e106(57.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e213(52.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.201\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eT1-2 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e90(15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e54(29.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e36(8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eC1-2 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e78(13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e29(15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e49(12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.204\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eSevere renal histopathological damage, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e147(24.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e58(31.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e89(21.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eRASB treatment,\u0026nbsp;n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e528(88.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e162(88.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e366(89.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.661\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eCorticosteroids and/or immunosuppressors, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e184(31.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e63(34.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e121(29.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.249\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eESRD and/or death, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e49(8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e32(17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e17(4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as the mean\u0026nbsp;\u0026plusmn;\u0026nbsp;standard deviation (SD), median (interquartile range), or number (percentage).\u003c/p\u003e\n\u003cp\u003eAbbreviations: BP, blood pressure;\u0026nbsp;eGFR, estimated glomerular filtration rate; ESRD: end stage renal disease; Low-density lipoprotein cholesterol; MAP, mean arterial pressure; RASB, renin-angiotensin system blockade; URBC, urinary red blood cell.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003e Baseline characteristics and outcomes in IgAN patients with kidney biopsies stratified by the degree of renal histopathological damage.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"650\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eSevere renal histopathological damage (\u003cem\u003en\u003c/em\u003e=147)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eMild renal histopathological damage (\u003cem\u003en\u003c/em\u003e=447)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eAge, years (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e41.18\u0026plusmn;13.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e42.54\u0026plusmn;13.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.287\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eFemale, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e76(51.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e207(46.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eBody mass index, kg/m\u003csup\u003e2\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e25.57\u0026plusmn;3.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e25.18\u0026plusmn;3.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.298\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eSystolic\u0026nbsp;BP,\u0026nbsp;mmHg (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e139.97\u0026plusmn;17.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e136.38\u0026plusmn;17.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eDiastolic BP, mmHg (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e87.37\u0026plusmn;12.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e84.23\u0026plusmn;12.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eMAP, mmHg (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e104.91\u0026plusmn;13.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e101.62\u0026plusmn;13.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eHemoglobin, g/L (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e125.95\u0026plusmn;21.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e135.02\u0026plusmn;19.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003ePlatelet counts, 10\u003csup\u003e9\u003c/sup\u003e/L (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e252.89\u0026plusmn;68.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e245.54\u0026plusmn;60.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.218\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eSerum uric acid, \u0026mu;mol/L (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e392.86\u0026plusmn;108.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e371.36\u0026plusmn;96.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eSerum creatinine, \u0026mu;mol/L (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e118.71\u0026plusmn;75.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e91.42\u0026plusmn;53.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eSerum urea nitrogen, mmol/L (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e7.72\u0026plusmn;4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e6.23\u0026plusmn;2.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eeGFR, ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e74.24\u0026plusmn;32.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e88.35\u0026plusmn;29.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eSerum albumin, g/L (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e35.89\u0026plusmn;6.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e36.52\u0026plusmn;6.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.335\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eTriglycerides, mmol/L (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e1.88\u0026plusmn;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e1.68\u0026plusmn;1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eTotal cholesterol, mmol/L (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e5.12\u0026plusmn;1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e5.10\u0026plusmn;2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.913\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eLDL-C, mmol/L (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e3.24\u0026plusmn;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e3.26\u0026plusmn;1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.901\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eIgA, g/L\u0026nbsp;(mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e3.30\u0026plusmn;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e3.10\u0026plusmn;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eComplement 3 (g/L) (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e1.09\u0026plusmn;0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e1.06\u0026plusmn;0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eComplement 4 (g/L) (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e0.29\u0026plusmn;0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e0.26\u0026plusmn;0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eURBC\u0026ge;30/uL, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e83(56.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e208(46.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eProteinuria (g/day) (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e2.64\u0026plusmn;2.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e1.81\u0026plusmn;1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistological characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eM1 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e146(99.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e297(66.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eE1 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e67(45.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e48(10.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eS1 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e138(93.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e181(40.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eT1-2 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e70(47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e20(4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eC1-2 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e66(44.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e12(2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eRASB treatment,\u0026nbsp;n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e128(87.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e400(89.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.420\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eCorticosteroids and/or immunosuppressors, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e58(39.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e126(28.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eESRD and/or death, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e26(17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e23(5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as the mean\u0026nbsp;\u0026plusmn;\u0026nbsp;standard deviation (SD), median (interquartile range), or number (percentage).\u003c/p\u003e\n\u003cp\u003eAbbreviations: BP, blood pressure;\u0026nbsp;eGFR, estimated glomerular filtration rate; ESRD: end stage renal disease; Low-density lipoprotein cholesterol; MAP, mean arterial pressure; RASB, renin-angiotensin system blockade; URBC, urinary red blood cell.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003e Logistic regression analyses for severe renal histopathological damage in IgAN patients with kidney biopsies.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"730\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 229px;\"\u003e\n \u003cp\u003eUnivariable logistic regression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eMultivariable logistic regression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cem\u003eOR\u003c/em\u003e (95% \u003cem\u003eCI\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cem\u003eOR\u003c/em\u003e (95% \u003cem\u003eCI\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eAge, each year increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.992(0.978-1.006)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eFemale, sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.806(0.555-1.170)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eBody mass index, each kg/m\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eincrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.025(0.978-1.074)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eMAP, each mmHg increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.018(1.004-1.032)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eHemoglobin, each g/L increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.978(0.968, 0.987)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.982(0.972-0.993)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003ePlatelet counts, each 10\u003csup\u003e9\u003c/sup\u003e/L increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.002(0.999, 1.005)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eSerum uric acid, each 100 \u0026mu;mol/L increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.233(1.027, 1.481)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.203(1.012-1.368)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eeGFR, each ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.985(0.978, 0.991)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.990(0.983-0.997)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eSerum albumin, each g/dL increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.987(0.961, 1.014)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eTriglycerides, each mmol/L increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.135(0.985, 1.307)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eTotal cholesterol, each mmol/L increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.005(0.920, 1.098)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.913\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eLDL-C, mmol/L, each mmol/L increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.991(0.863, 1.138)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.901\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eIgA, each g/L increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.193(1.002, 1.421)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.234(1.025-1.486)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eComplement 3, each g/L increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.818(0.786, 4.202)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eComplement 4, each g/L increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e2.323\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e10.203(1.634, 63.707)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eURBC\u0026ge;30/uL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.490(1.024, 2.169)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eProteinuria, each g/day increase\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.197(1.099, 1.304)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.182(1.080-1.293)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eRASB treatment, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.792(0.448, 1.398)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003eCorticosteroids and/or immunosuppressors, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.660(1.124, 2.451)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: eGFR, estimated glomerular filtration rate; Low-density lipoprotein cholesterol; MAP, mean arterial pressure; RASB, renin-angiotensin system blockade; URBC, urinary red blood cell.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIgA nephropathy (IgAN) is one of the most widespread types of primary glomerulonephritis, which makes it one of the leading causes of ESRD. For unknown reasons, the clinical and histopathological manifestations of IgAN exhibit a wide range of variability. The Oxford histopathological classification of IgAN has been widely used to reflect the severity of renal pathological damage in IgAN\u0026nbsp;[3]. Therefore, it is essential to emphasize the importance of early detection of risk factors associated with the degree of renal histopathological damage in IgAN patients, as well as interventions aimed at delaying disease progression and preventing ESRD. Nevertheless, IgAN is characterized by variation of pathological features, and a few studies have investigated the serum uric acid and degree of histopathological damage of IgAN patients. In this study, we conducted a retrospective analysis to explore the independent risk factors for severe renal\u0026nbsp;histopathological\u0026nbsp;damage in IgAN patients and to establish a predictive model, while also investigating the impact of serum uric acid on renal pathology and prognosis.\u003c/p\u003e\n\u003cp\u003eCurrently, clinical predictive models, which statistically analyze various clinical data, are being increasingly applied in clinical diagnosis and treatment decision-making. Nomograms, which are based on multivariate regression analysis to predict the incidence of certain clinical outcomes, are one of the most widely used statistical methods in clinical research\u0026nbsp;[10]. This study applied nomograms to the risk study of the degree of renal histopathological damage in patients with IgAN. The nomogram models we developed showed that hemoglobin, serum uric acid, eGFR, IgA and proteinuria may be used as independent risk factors for severe renal histopathological damage in patients with IgAN.\u003c/p\u003e\n\u003cp\u003eAmong the histological parameters evaluated, tubular atrophy/interstitial fibrosis which can lead to renal interstitial fibrosis at a later stage was identified as the strongest risk factor for the progression of IgAN\u0026nbsp;[4, 11], suggesting that elevated serum uric acid levels may independently contribute to the progression of IgAN by causing damage to the tubulointerstitial tissue\u0026nbsp;[11]. Previous studies have confirmed that hyperuricemia is an independent risk factor for the progression of tubular atrophy/interstitial fibrosis in patients with IgAN\u0026nbsp;[11, 12]. Our study also found that the hyperuricemia group had higher tubular atrophy/interstitial fibrosis compared to the non-hyperuricemia group in patients with IgAN (29.3% versus 8.8%, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001). Several possible mechanisms have been proposed to explain the development of serum uric acid induced histological lesions, including oxidative stress, alteration of the nitric oxide pathway, insulin resistance, inflammatory activation, and stimulation of the renin-angiotensin system\u0026nbsp;[13]. Serum uric acid can also induce phenotypic transitions of epithelial and endothelial cells\u0026nbsp;[14]\u0026nbsp;and cause kidney damage through Th1/Th2 polarization and the expression of extracellular matrix genes\u0026nbsp;[15], which may be one of the mechanisms.\u0026nbsp;However, the increase in serum uric acid levels may be due to a low eGFR, which leads to a reduction in the excretion of uric acid.\u0026nbsp;We also found that severe renal histopathological damage correlates with decreased eGFR in patients with IgAN. Therefore, further clinical studies are required to investigate the correlation between renal histopathological damage and prognosis in patients with IgAN.\u003c/p\u003e\n\u003cp\u003eAdditionally, this study found that a decrease in hemoglobin is an independent risk factor for severe renal pathological damage in IgAN patients. These findings have been reported in previous studies and may be related to anemia as one of the frequent complications of CKD. Anemia might lead to hypoxic injury in kidneys through the hypoxia-inducible factor (HIF) signaling pathway\u0026nbsp;[16]. Previous studies have indicated an association between anemia-induced hypoxia and glomerular disease through the HIF signaling pathway. This HIF pathway in turn damages podocytes, promotes the excretion of proteinuria, and accelerates the progression of glomerular diseases\u0026nbsp;[17]. Another important cause of renal anemia is the insufficient production of erythropoietin (EPO), which may be related to severe renal histopathological damage in IgAN. Erythropoietin-producing cells are essentially renal interstitial fibroblasts\u0026nbsp;[18], and under the action of hypoxia, this trigger regulates the production of EPO through the PHD2-HIF2\u0026alpha;-EPO signaling pathway\u0026nbsp;[19]. This suggests that anemia is closely related to the degree of more severe renal lesions in IgAN, especially tubulointerstitial damage. Hypoxic damage to the glomerulus and tubulointerstitium caused by anemia could account for the link between anemia and poor renal prognosis.\u003c/p\u003e\n\u003cp\u003eThis study also found that high IgA was closely related to the severity of renal histopathological damage in IgAN. IgA nephropathy is generally presumed to be IgA immune complex or polymerized IgA-mediated glomerulonephritis. Accumulated mesangial IgA triggers the activation of the complement protein C3, resulting in the activation of macrophages that release inflammatory cytokines and extracellular matrix components\u0026nbsp;[20]. Ishiguro et al.\u0026nbsp;[21]\u0026nbsp;reported that patients with IgAN have higher serum IgA levels and lower C3 levels compared to non-IgA nephropathy, and these are closely related to the prediction of the diagnosis and prognostic grading in patients with IgAN. Yasuhiko et al. presented that elevated IgA plays an important role in assessing hematuria and persistent proteinuria and combined evaluation of serum IgA/C3 and glomerular C3 staining can predict IgAN prognosis\u0026nbsp;[22].\u003c/p\u003e\n\u003cp\u003eOur study has several limitations. First, our study was a retrospective single-center cohort design, and no cause-and-effect relationships can be inferred between serum uric acid and renal histopathological damage. Second, the exact mechanism of serum uric acid involvement in renal histopathological damage is unclear. Furthermore, the prediction model formulated in this study requires additional external verification for confirmation. Therefore, further well-designed multicenter prospective cohort studies with longer regular follow-up and larger sample sizes are needed.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eHyperuricemia appeared to be a common symptom in IgAN. We have found that elevated serum uric acid levels were independently associated with severe renal histopathological damage and poor prognosis in patients with IgAN. Serum uric acid, as a factor contributing to more severe renal histopathological damage, is crucial for guiding treatment decisions and assessing prognosis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of interest statement\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study was funded by Qingdao Key Health Discipline Development Fund, Qingdao Key Clinical Specialty Elite Discipline, Taishan Scholar Program of Shandong Province [No. tstp20230665] and Qingdao University Affiliated Hospital \u0026ldquo;Clinical Medicine\u0026thinsp;+\u0026thinsp;X\u0026rdquo; (QDFY\u0026thinsp;+\u0026thinsp;X2023208, QDFY\u0026thinsp;+\u0026thinsp;X2023106).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eH.W.: wrote the main manuscript text. J.L.: prepared figures. C.J.: prepared tables. X.L. and Y.X. review and edit the manuscript. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThe authors sincerely thank all the patients who took part in this study and the funding support.\u003c/p\u003e\u003ch2\u003eData availability statement\u003c/h2\u003e \u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTomino Y, Sakai H: Clinical guidelines for immunoglobulin A (IgA) nephropathy in Japan, second version. \u003cem\u003eCLIN EXP NEPHROL\u003c/em\u003e 2003, 7(2):93-97.\u003c/li\u003e\n\u003cli\u003eD\u0026apos;Amico G: Natural history of idiopathic IgA nephropathy: role of clinical and histological prognostic factors. \u003cem\u003eAM J KIDNEY DIS\u003c/em\u003e 2000, 36(2):227-237.\u003c/li\u003e\n\u003cli\u003eBarbour SJ, Espino-Hernandez G, Reich HN, Coppo R, Roberts IS, Feehally J, Herzenberg AM, Cattran DC: The MEST score provides earlier risk prediction in lgA nephropathy. \u003cem\u003eKIDNEY INT\u003c/em\u003e 2016, 89(1):167-175.\u003c/li\u003e\n\u003cli\u003eZhu B, Yu DR, Lv JC, Lin Y, Li Q, Yin JZ, Du YY, Tang XL, Mao LC, Li QF\u003cem\u003e et al\u003c/em\u003e: Uric Acid as a Predictor of Immunoglobulin A Nephropathy Progression: A Cohort Study of 1965 Cases. \u003cem\u003eAM J NEPHROL\u003c/em\u003e 2018, 48(2):127-136.\u003c/li\u003e\n\u003cli\u003eLe W, Liang S, Hu Y, Deng K, Bao H, Zeng C, Liu Z: Long-term renal survival and related risk factors in patients with IgA nephropathy: results from a cohort of 1155 cases in a Chinese adult population. \u003cem\u003eNEPHROL DIAL TRANSPL\u003c/em\u003e 2012, 27(4):1479-1485.\u003c/li\u003e\n\u003cli\u003eObermayr RP, Temml C, Gutjahr G, Knechtelsdorfer M, Oberbauer R, Klauser-Braun R: Elevated uric acid increases the risk for kidney disease. \u003cem\u003eJ AM SOC NEPHROL\u003c/em\u003e 2008, 19(12):2407-2413.\u003c/li\u003e\n\u003cli\u003eKohagura K, Kochi M, Miyagi T, Kinjyo T, Maehara Y, Nagahama K, Sakima A, Iseki K, Ohya Y: An association between uric acid levels and renal arteriolopathy in chronic kidney disease: a biopsy-based study. \u003cem\u003eHYPERTENS RES\u003c/em\u003e 2013, 36(1):43-49.\u003c/li\u003e\n\u003cli\u003eLiao Y, Liao W, Liu J, Xu G, Zeng R: Assessment of the CKD-EPI equation to estimate glomerular filtration rate in adults from a Chinese CKD population. \u003cem\u003eJ INT MED RES\u003c/em\u003e 2011, 39(6):2273-2280.\u003c/li\u003e\n\u003cli\u003eCattran DC, Coppo R, Cook HT, Feehally J, Roberts IS, Troyanov S, Alpers CE, Amore A, Barratt J, Berthoux F\u003cem\u003e et al\u003c/em\u003e: The Oxford classification of IgA nephropathy: rationale, clinicopathological correlations, and classification. \u003cem\u003eKIDNEY INT\u003c/em\u003e 2009, 76(5):534-545.\u003c/li\u003e\n\u003cli\u003eZhou H, Zhang Y, Qiu Z, Chen G, Hong S, Chen X, Zhang Z, 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non-alcoholic fatty liver disease in a non-obese Chinese population with normal blood lipid levels. \u003cem\u003eBMC GASTROENTEROL\u003c/em\u003e 2022, 22(1):196.\u003c/li\u003e\n\u003cli\u003eKang DH: Hyperuricemia and Progression of Chronic Kidney Disease: Role of Phenotype Transition of Renal Tubular and Endothelial Cells. \u003cem\u003eCONTRIB NEPHROL\u003c/em\u003e 2018, 192:48-55.\u003c/li\u003e\n\u003cli\u003eTomino Y: IgA nephropathy: lessons from an animal model, the ddY mouse. \u003cem\u003eJ NEPHROL\u003c/em\u003e 2008, 21(4):463-467.\u003c/li\u003e\n\u003cli\u003eIto M, Tanaka T, Ishii T, Wakashima T, Fukui K, Nangaku M: Prolyl hydroxylase inhibition protects the kidneys from ischemia via upregulation of glycogen storage. \u003cem\u003eKIDNEY INT\u003c/em\u003e 2020, 97(4):687-701.\u003c/li\u003e\n\u003cli\u003eMatoba K, Kawanami D, Okada R, Tsukamoto M, Kinoshita J, Ito T, Ishizawa S, Kanazawa Y, Yokota T, Murai N\u003cem\u003e et al\u003c/em\u003e: Rho-kinase inhibition prevents the progression of diabetic nephropathy by downregulating hypoxia-inducible factor 1alpha. \u003cem\u003eKIDNEY INT\u003c/em\u003e 2013, 84(3):545-554.\u003c/li\u003e\n\u003cli\u003eYasuoka Y, Izumi Y, Fukuyama T, Oshima T, Yamazaki T, Uematsu T, Kobayashi N, Nanami M, Shimada Y, Nagaba Y\u003cem\u003e et al\u003c/em\u003e: Tubular Endogenous Erythropoietin Protects Renal Function against Ischemic Reperfusion Injury. \u003cem\u003eINT J MOL SCI\u003c/em\u003e 2024, 25(2).\u003c/li\u003e\n\u003cli\u003eSuzuki N: Erythropoietin gene expression: developmental-stage specificity, cell-type specificity, and hypoxia inducibility. \u003cem\u003eTOHOKU J EXP MED\u003c/em\u003e 2015, 235(3):233-240.\u003c/li\u003e\n\u003cli\u003eSelvaskandan H, Shi S, Twaij S, Cheung CK, Barratt J: Monitoring Immune Responses in IgA Nephropathy: Biomarkers to Guide Management. \u003cem\u003eFRONT IMMUNOL\u003c/em\u003e 2020, 11:572754.\u003c/li\u003e\n\u003cli\u003eIshiguro C, Yaguchi Y, Funabiki K, Horikoshi S, Shirato I, Tomino Y: Serum IgA/C3 ratio may predict diagnosis and prognostic grading in patients with IgA nephropathy. \u003cem\u003eNEPHRON\u003c/em\u003e 2002, 91(4):755-758.\u003c/li\u003e\n\u003cli\u003eTomino Y, Suzuki S, Imai H, Saito T, Kawamura T, Yorioka N, Harada T, Yasumoto Y, Kida H, Kobayashi Y\u003cem\u003e et al\u003c/em\u003e: Measurement of serum IgA and C3 may predict the diagnosis of patients with IgA nephropathy prior to renal biopsy. \u003cem\u003eJ CLIN LAB ANAL\u003c/em\u003e 2000, 14(5):220-223.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"IgA nephropathy, serum uric acid, kidney biopsy, renal pathology","lastPublishedDoi":"10.21203/rs.3.rs-5904892/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5904892/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground. \u003c/strong\u003eIgA nephropathy (IgAN), the most common primary glomerulonephritis worldwide, is also a major cause of end stage renal disease (ESRD). We aimed to explore the relationship between the levels of serum uric acidand the degree of renal histopathological damage in patients with IgA nephropathy (IgAN) and build a nomogram model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e. It was a retrospective study. The clinical and histopathologicaldata of patients with primary IgAN diagnosed by renal biopsy were collected. Risk factors of severe renal histopathologicaldamage in IgAN patients were identified by logistic regression analysis. A nomogram model was established based on the multivariate logistic regression analysis. The C-index and calibration plots were used for the evaluation of the discrimination and calibration performance, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e. A total of 594 patients were retrospectively analyzedin the study. Compared with patients without hyperuricemia, patients with hyperuricemia had lower eGFR and higher body mass index, mean arterial pressure (MAP), hemoglobin, serum uric acid, triglycerides, IgA, complement 3, complement 4, proteinuria and severe renal histopathological damage ( \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). Hemoglobin, serum uric acid, eGFR, IgA and proteinuria were identified and entered into the nomogram models. The C-index of this prediction model was 0.689 (95% CI 0.639–0.738). KM survival curve analysis showed that hyperuricemia and severe renal histopathological damage had a higher risk of progression to death or ESRD(\u003cem\u003ep\u003c/em\u003e \u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e. Serum uric acid levels are independently associated with severe renal histopathological damage and poor prognosis in IgAN patients.\u003c/p\u003e","manuscriptTitle":"Elevated serum uric acid level correlates with the severity of renal histopathology in IgA nephropathy and establishment of a nomogram model","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-04 08:52:11","doi":"10.21203/rs.3.rs-5904892/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dcc2e657-e0d1-4669-abae-4453c5c1d99c","owner":[],"postedDate":"February 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-11T06:53:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-04 08:52:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5904892","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5904892","identity":"rs-5904892","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}