Abelmoschus manihot alleviates insulin resistance in biopsy-proven diabetic kidney disease through attenuation of inflammation

Abelmoschus manihot alleviates insulin resistance in biopsy-proven diabetic kidney disease through attenuation of inflammation | 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 Abelmoschus manihot alleviates insulin resistance in biopsy-proven diabetic kidney disease through attenuation of inflammation Xiansen Wei, Shimin Jiang, Jiao Zhang, Xia Gu, Hongmei Gao, Jian Lu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7003564/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Nov, 2025 Read the published version in BMC Nephrology → Version 1 posted 18 You are reading this latest preprint version Abstract Background : Research is lacking on the effects of Abelmoschus Manihot on insulin resistance (IR) and chronic microinflammation in patients with diabetic kidney disease (DKD). This study aims to explore the effects of Abelmoschus Manihot on IR and high-sensitivity C-reactive protein (hs-CRP) levels in DKD, as well as to analyze the relationship between the two factors. Methods: Biopsy-proven DKD patients with a homeostatic model assessment of IR (HOMA-IR) ≥ 5 and hsCRP ≥ 1 mg/L were recruited from the Department of Nephrology at China-Japan Friendship Hospital between January 2012 and December 2023. All patients received standard care medications, and those in the Manihot group were treated with Abelmoschus Manihot for 12 months. Participants were followed up every 3 months for a total of 1 year. Changes in HOMA-IR, hsCRP, 24-hour urine protein excretion (24-h-UPE), and estimated glomerular filtration rate (eGFR) from baseline during follow-up were assessed. Additionally, differences in 24-h-UPE, eGFR, and major cardiovascular and cerebrovascular events between the groups after treatment were evaluated. Adverse events and laboratory test abnormalities were also recorded. Results: A total of 94 biopsy-proven DKD patients were included. Among them, 45 patients received standard care (control group), while 49 additionally took standard care plus Abelmoschus Manihot . The results revealed a statistically significant reduction in 24-h-UPE in the manihot group compared to the control group at 6 months (−232.9 vs −145.8 mg, P = 0.04) and beyond. Since the 9-month follow-ups, the manihot group exhibited a significantly slower eGFR decline (-3.2 vs -4.7 mL/min/1.73m 2 , P < 0.05). Additionally, IR in the manihot group was significantly reduced in both within- and between-groups (compared to the control), and hsCRP also exhibited analogous findings. In the manihot group, a significant positive correlation was observed between the decrease in hsCRP and the decrease in HOMA-IR, with P-value < 0.01. In contrast, no such significant correlation was observed in the control group, where the P-value was 0.1. No significant adverse events or laboratory test abnormalities were observed. Conclusion: This study demonstrates that in biopsy-confirmed DKD patients, A. manihot not only enhances the clinical outcomes of standard care,but also significantly alleviaties IR, potentially through its anti-inflammatory effects. Abelmoschus manihot diabetic kidney disease insulin resistance high-sensitivity C-reactive protein proteinuria glomerular filtration rate Figures Figure 1 Figure 2 Figure 3 Figure 4 1 Introduction Diabetic kidney disease (DKD) is the leading cause of end-stage kidney failure, accounting for 45% of cases requiring dialysis [ 1 ]. Its increasing prevalence poses a significant and growing threat to patient well-being and exacerbates the strain on healthcare systems. The standard care recommended by the American Diabetes Association includes the use of renin-angiotensin system inhibitors (RASi), non-steroidal mineralocorticoid receptor antagonists (MRAs), and sodium-glucose cotransporter-2 (SGLT2) inhibitors to reduce proteinuria and slow the progression of renal function deterioration. Despite improving blood glucose control and renal protection, a residual risk of chronic kidney disease progression remains [ 2 ]. Insulin resistance (IR) is a key characteristic of type 2 diabetes and one of its fundamental pathological mechanisms, closely associated with the development of both macrovascular and microvascular complications (including DKD). IR is affected by genetic predisposition, lifestyle factors [ 3 ], as well as chronic microinflammation [ 4 , 5 ], which is also considered a contributing factor to the residual risk of DKD. In the renal tissues of diabetic individuals, nuclear factor kappa B (NF-κB) is activated, leading to the overexpression of chemotactic factors including monocyte chemoattractant protein-1 (MCP-1) [ 6 ]. Although previous studies have shown that the combination of Abelmoschus Manihot (A. Manihot) and irbesartan is effective in reducing proteinuria [ 7 ], and animal experiments have demonstrated its potential to modulate the inflammatory response by inhibiting the TLR4/NF-κB pathway [ 8 ], there is currently a lack of research on the effects of A. manihot on IR and chronic microinflammation in patients with DKD. Therefore, the primary objective of this retrospective analysis is to evaluate the impact of combining A. manihot with standard treatment on IR and hs-CRP levels in DKD patients. 2 Methods 2.1 Study Design This was a retrospective study involving 511 biopsy-proven DKD patients recruited from the Department of Nephrology at China-Japan Friendship Hospital. The inclusion criteria and grouping were (1) Patients aged 18–75 years involved between January 1, 2012, and December 31, 2023. (2) Patients diagnosed with DKD, confirmed by renal pathology. (3) Patients receiving A. manihot treatment were allocated to the manihot group, whereas those with comparable eGFR and proteinuria levels who did not receive A. manihot treatment were assigned to the control group. The date of the initial prescription of A. manihot or standard care medications following renal biopsy was taken as the baseline for both cohorts. (4) All patients had an estimated glomerular filtration rate (eGFR) > 30 mL/min/1.73 m 2 , 24-hour urine protein excretion (24-h-UPE) > 1 g. (5) Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) ≥ 5 and high-sensitivity C-reactive protein (hsCRP) ≥ 1 mg/L. All measurements were obtained within 2 weeks of the study baseline. (6) The patients were monitored during the follow-up period, with at least four 24-h-UPE and eGFR measurements and at least one HOMA-IR and hsCRP measurement. Exclusion criteria were (1) Type 1 diabetes. (2) Coexisting non-DKDs. (3) Tumors or chronic infectious diseases. (4) the treatment regimen involving insulin or its analogues (5) Acute diseases occurring within 4 weeks prior to baseline and up to 4 weeks after the conclusion of follow-up assessments. 2.2 Treatment Regimen Both patient groups were free of contraindications and underwent a standard care regimen comprising RASi, SGLT2 inhibitors, and MRAs. Patients in the manihot group took five Huangkui capsules (Suzhong Pharmaceutical Group Co., Ltd., Taizhou, China) thrice daily (6.45 g/day). Prescription details were recorded throughout the follow-up period, ensuring a maximum interval of 2 months between consecutive prescriptions. 2.3 Data Collection The pooled medical history data included date of birth, sex, height, weight ,blood pressure, duration of diabetes, presence of retinopathy, concomitant medications (SGLT2 inhibitors, RASi, sacubitril/valsartan, or MRAs), comorbidities (hypertension, cardiovascular and cerebrovascular diseases, or peripheral arterial disease), medication adverse reactions during the follow-up period and acute diseases occurring within 4 weeks prior to baseline and up to 4 weeks after the conclusion of follow-up assessments . Laboratory test results were collected at baseline, 2–4 months, 5–7 months, 8–10 months, and 11–13 months. These included serum creatinine, 24-h-UPE, serum albumin, and glycated hemoglobin, as well as items from blood routine and liver function tests. The CKD-EPI equation, adjusted for sex, age, and serum creatinine, was used to calculate eGFR. The HOMA-IR was calculated as (fasting insulin [µIU/mL] × fasting glucose [mmol/L])/22.5 [ 9 ]. According to the classification criteria for DKD pathology published in the American Journal of Kidney Diseases [ 10 ], the following parameters were evaluated: global and segmental glomerulosclerosis, interstitial fibrosis and tubular atrophy (IFTA), interstitial inflammation, arteriolar hyalinosis, and arteriosclerosis. The scoring for glomerulosclerosis and IFTA was based on the proportion of tissue affected by each lesion, categorized as follows: 0 for 0–10%, 1 for 10–25%, 2 for 26–50%, and 3 for > 50%. Interstitial inflammation was graded as 0 for absent, 1 for infiltration only related to IFTA, and 2 for infiltration in areas without IFTA. Arteriolar hyalinosis was scored as 0 when absent and 1 when at least one area was affected. Arteriosclerosis was scored based on the thickness of intima compared to media, as follows: 0 for intimal thickening less than media and 1 for intimal thickening equal to or greater than media. The scores of these components were summed to derive the total chronicity score, categorized as minimal for a score of 0–1, mild for 2–4, moderate for 5–7, and severe for 8–10. Scoring was completed by two renal pathology experts, with discrepancies resolved through consensus. The patients’ final outcomes were not known at the time of scoring. 2.4 Outcomes The primary outcomes were the changes of HOMA-IR, hsCRP,24-h-UPE and eGFR compared to baseline at different time points. The formulas for calculating these changes were as follows: Δ24-h-UPE = 24-h-UPE (follow-up) − 24-h-UPE (baseline) ΔeGFR = eGFR (follow-up) − eGFR (baseline) ΔHOMA-IR = HOMA-IR (follow-up) − HOMA-IR (baseline) ΔhsCRP = hsCRP (follow-up) − hsCRP (baseline) The secondary outcomes included comparisons of 24-h-UPE, eGFR, and major cardiovascular and cerebrovascular events (MACE) before and after treatment between the groups. Safety indicators were assessed based on comparisons of voluntarily reported adverse events and various laboratory parameters, including blood routine and liver function tests. 2.5 Statistical Analysis Continuous variables were assessed for normality of distribution using the Shapiro-Wilk test. Data conforming to a normal distribution are reported as mean ± standard deviation. For data with skewed distributions, descriptive statistics are presented, including the median, first quartile, and third quartile. Qualitative data are presented as percentages or composition ratios. Continuous variables with a normal distribution were compared using the t -test, while the Wilcoxon signed-rank test or Mann-Whitney U test was applied to non-normally distributed variables, depending on whether the comparison was within or between groups. Correlation between changes in hs-CRP and HOMA-IR was assessed using Spearman's rank correlation test. Composition ratios were compared using the chi-square or Fisher’s exact test. All tests were two-tailed, with statistical significance set at P < 0.05. All analyses were conducted using SPSS Statistics for Windows (version 27.0; IBM Corp., Armonk, NY, USA). 3 Results 3.1 Demographic and Clinical Characteristics Between January 1, 2012, and December 31, 2023, 511 patients were diagnosed with DKD through renal biopsy. After applying the exclusion criteria, 170 patients were included at baseline, comprising 84 females and 86 males. Among them, 81 patients received standard care, while 89 patients took A. manihot in addition to receiving standard care. However, 29 patients had incomplete laboratory results, and 14 patients developed acute infectious diseases. 26 patients were excluded due to irregular medication intake. Eventually, a total of 94 patients completed 12 months of treatment (49 in the manihot group and 45 in the control group), as shown in Fig. 1 . At baseline, there were no statistically significant differences in age, duration of diabetes, retinopathy, or macrovascular disease between the groups (Table 1 ). Similarly, comparisons of the renal protective medications revealed no statistical differences between the two groups. In terms of histopathological findings, there were no statistically significant differences in glomerular, tubule-interstitial, or vascular lesions between the two groups. Detailed baseline characteristics of renal histopathological data are shown in Table 2 . Table 1 Baseline clinical features of the two groups Manihot group (n = 49) Control group (n = 45) Test statistic P Age (years) 58.4 ± 7.1 57.6 ± 9.6 0.49 0.63 Male 28 (57.1%) 22 (48.8%) 0.35 0.55 Female 21 (42.8%) 23 (51.1%) Body Weight Index 26.9 ± 3.38 26.6 ± 3.68 0.41 0.68 Systolic BP (mmHg) 137 ± 10.1 136 ± 9.9 0.62 0.54 Diastolic BP (mmHg) 76.3 ± 12.3 76.8 ± 11.6 -0.22 0.82 Duration of diabetes (months) 54 (36, 68) 55 (40, 68) 1165 0.80 Diabetic retinopathy 30 (61.2%) 33 (73.3%) 1.06 0.30 Macrovascular complication 35 (71.4%) 35 (77.7%) 0.22 0.64 Serum albumin (g/L) 28.8 ± 7.1 29.22 ± 4.7 -0.44 0.66 Hemoglobin A1c (%) 7.2 (6.7, 7.8) 7.3 (6.8, 7.9) 1154 0.74 eGFR (ml/min/1.73m2) 59.3 ± 4.8 59.0 ± 5.0 0.28 0.77 24-h-UPE (mg) 2642 ± 484 2669 ± 461 -0.28 0.78 hsCRP (mg/L) 10.7 (6.2, 18.6) 10.6 (6.1, 16.2) 1096 0.46 LDL-C (mmol/L) 2.61 ± 1.04 2.59 ± 0.91 0.08 0.94 Triacylglycerol (mmol/L) 2.35 ± 0.86 2.45 ± 0.77 -0.56 0.57 Serum uric acid (µmol/L) 391 ± 102 396 ± 84.0 -0.26 0.74 Drugs DPP-4i 13 (26.5%) 9 (20.0%) 0.25 0.64 GLP-1RA 10 (20.1%) 11 (24.4%) 0.05 0.82 SGLT2i 20 (40.8%) 15 (33.3%) 0.28 0.59 Insulin analogs 34 (69.3%) 33 (73.3%) 0.04 0.85 ACEIs 10 (20.4%) 12 (26.6%) 0.22 0.64 ARBs 21 (42.7%) 16 (35.5%) 0.26 0.61 Sacubitril valsartan 17 (34.6%) 18 (40.0%) 0.10 0.75 Finerenone 12 (24.4%) 14 (31.1%) 0.24 0.63 Diuretics 28 (57.1%) 24 (53.3%) 0.03 0.87 Data are expressed in mean ± standard deviation or mean (25th percentile, 75th percentile). Manihot, Abelmoschus Manihot; eGFR, estimated Glomerular Filtration Rate; 24-h-UPE, 24-hour urine protein excretion; hsCRP,high-sensitivity C-reactive protein; LDL-C, Low-density Lipoprotein Cholesterol; GLP-1RA, glucagon-like peptide-1 (GLP-1) receptor agonists; DPP-4i, Dipeptidyl peptidase-4 inhibitors; SGLT2i,Sodium-glucose cotransporter 2 inhibitors; ACEIs, angiotensin-converting enzyme inhibitors; ARBs, angiotensin II receptor blockers. Table 2 Baseline histopathological features of the two groups Manihot group (n = 49) Control group (n = 45) Test statistic P Number of intact glomeruli 17 (10, 27) 17 (8, 20) 1386 0.19 Global and segmental glomerulosclerosis 0.78 0.68 IIa 13 (26.5%) 13 (28.8%) IIb 27 (55.1%) 21 (46.6%) III 9 (18.3%) 11 (24.4%) Interstitial fibrosis and tubular atrophy 2.10 0.55 0 7 (14.2%) 9 (10.2%) 1 20 (40.8%) 22 (48.8%) 2 17 (34.6%) 10 (22.2%) 3 5 (10.2%) 4 (8.8%) Interstitial inflammation 0.93 0.63 0 12 (24.4%) 14 (31.1%) 1 34 (69.3%) 27 (60.0%) 2 3 (6.1%) 4 (8.8%) Arteriolar hyalinosis 0.91 0.63 0 12 (24.4%) 15 (33.3%) 1 24 (48.9%) 19 (42.2%) 2 13 (26.5%) 11 (24.4%) Arteriosclerosis 2.10 0.35 0 28 (57.1%) 19 (42.4%) 1 18 (36.7%) 22 (48.8%) 2 3 (6.1%) 4 (8.8%) Total chronicity score 1.32 0.52 Mild 14 (28.5%) 14 (31.1%) Moderate 24 (48.9%) 25 (55.5%) Severe 11 (22.4%) 6 (13.3%) Manihot, Abelmoschus manihot. 3.2 Changes in 24-h-UPE At baseline, the 24-h-UPE values for the standard care and A. manihot groups were 2,640 ± 390 mg and 2,673 ± 368 mg, respectively, with no significant difference ( P = 0.66). After 3 months of treatment, no statistically significant differences were observed between the groups. However, by the 6-month follow-up, a significant decrease in urinary protein was observed in the A. manihot group (− 232.9 ± 206.5 mg vs − 145.8 ± 210.6 mg, P = 0.04). The differences between the two groups became more pronounced at the 9- and 12-month follow-ups ( P = 0.03, P = 0.02, Fig. 2 A). These findings suggested that supplementing standard care with A. manihot could lead to a further reduction in urinary protein, with a progressively greater impact over time. Within-group comparisons revealed a significant decrease in urinary protein for the A. manihot group compared to baseline ( P = 0.04). In the group, the rate of urinary protein reduction was fastest during the initial 3 months of treatment, and there was a statistically significant difference between the 6- and 3-month time points. Similar differences were also observed at 9 months compared to 3 months. In the A. manihot group, the rate of urinary protein reduction was fastest during the initial 3 months of treatment. Statistically significant differences were also observed between the 3rd and 6th months ( P < 0.05), as well as between the 3rd and 9th months ( P < 0.01). In the control group, a significant decrease in urinary protein was observed only when comparing the values at the 3rd and 9th month ( P = 0.03, Fig. 2 A). Comparison of 24-h-UPE between the two groups showed statistically significant differences at 9 and 12 months ( P < 0.05, Fig. 2 C). 3.3 Changes in eGFR At baseline, the eGFRs for the A. manihot and control groups were 59.3 ± 4.8 and 59.0 ± 5.2 mL/min/1.73 m 2 , respectively, showing no significant difference ( P = 0.77). Throughout the follow-up period, the A. manihot group showed a slower decline in eGFR compared to the control group, with the difference becoming increasingly evident over time and reaching statistical significance at 9 and 12 months ( P < 0.05, Fig. 2 B). In the control group, there was a notable decline in eGFR between consecutive time points. However, in the A. manihot group, statistically significant differences were only observed when comparing alternating adjacent time points. The eGFR levels in the two groups are presented in Fig. 2 D. At 12 months, the eGFR in the A. manihot group was higher than that in the control group ( P = 0.035, Fig. 2 D). 3.4 Changes in HOMA-IR At baseline, there was no significant difference in HOMA-IR levels between the two groups ( P = 0.93). By 12 months, both groups exhibited a decline in HOMA-IR levels. Wilcoxon signed-rank test revealed the reduction in HOMA-IR levels among patients in the A. manihot group a statistic of 211.5 ( P = 0.03), indicating a significant difference between pre- and post-treatment measurements. Wilcoxon signed-rank test revealed a statistic of 211.5 ( P < 0.001), indicating a significant reduction in HOMA-IR levels between pre- and post-treatment measurements in the A. manihot group, while no significant change was observed in the control group ( P = 0.21, Fig. 3 A). At 12 months, the A. manihot group exhibited a significantly greater decrease in HOMA-IR levels than the control group, as evidenced by a Mann-Whitney U statistic of 895.5 ( P = 0.03, Fig. 3 A). 3.5 Changes in hsCRP At baseline, there was no significant difference in hsCRP levels between the two groups ( P = 0.80). By 12 months, both groups exhibited a decline in hsCRP levels. The reduction in hsCRP among patients in the A. manihot group was statistically significant ( P < 0.001), while that in the control group did not reach statistical significance ( P = 0.10). At 12 months, the decrease in hsCRP levels was significantly more pronounced in the A. manihot group compared to the control group ( P = 0.04, Fig. 3 B). Spearman's rank correlation test was employed to explore the relationship between the changes in hsCRP and HOMA-IR. In the A. manihot group, a positive correlation was observed between the decrease in hsCRP and the decrease in HOMA-IR, with a ρ of 0.48 and P < 0.01, indicating statistical significance. In contrast, no such correlation was observed in the control group, where the ρ was 0.25 and the P-value was 0.1, as shown in Fig. 4 . 3.6 MACEs IR is an important risk factor for macrovascular complications in diabetes. We evaluated the occurrence of MACE during the follow-up period. A total of 3 MACEs were recorded, with 1 patient in the A. manihot group experiencing acute myocardial infarction, and 2 patients in the control group, who developed acute myocardial infarction and cerebral infarction, respectively. Fisher's exact test was performed, yielding a p-value of 0.605, indicating no statistically significant difference 3.7 Adverse Events According to the patients' medical records, there were four individuals in the A. manihot group who developed gastric distension, and three patients in the control group who experienced mild dizziness and/or fatigue. All of them had mild symptoms and were able to continue treatment after receiving symptomatic treatment. Laboratory examinations indicated no significant differences in complete blood counts, serum electrolytes, coagulation parameters, or liver function tests between the two groups ( P > 0.05), indicating that A. manihot did not result in any abnormalities in the safety indicators (Table 3 ). Table 3 Comparison of safety parameters following treatment in both groups. Manihot group (n = 49) Control group (n = 45) t P White blood cells (×10 9 /L) 0.47 ± 1.37 0.42 ± 1.68 0.16 0.88 Red blood cells (×10 12 /L) 0.24 ± 0.28 0.32 ± 0.36 -1.2 0.24 Platelets (×10 9 /L) -12.6 ± 108 -35.0 ± 96.0 1.06 0.29 Alanine aminotransferase (U/L) 4.92 ± 18.8 8.68 ± 15.9 -1.05 0.30 Serum total bilirubin (µmol/L) 3.56 ± 3.24 2.84 ± 3.28 1.07 0.29 Serum total protein (g/L) -4.02 ± 3.03 -4.21 ± 2.69 0.32 0.75 Alkaline phosphatase (U/L) 12.5 ± 5.12 13.2 ± 7.06 -0.55 0.59 Fibrinogen (g/L) 0.41 ± 0.78 0.34 ± 0.68 0.46 0.64 Serum potassium (mmol/L) 0.71 ± 1.38 0.66 ± 1.52 0.17 0.87 Hemoglobin A1c (%) -0.46 ± 0.54 -0.34 ± 0.48 -1.14 0.26 LDL-C (mmol/L) -0.35 ± 0.72 -0.58 ± 0.76 1.50 0.14 Triacylglycerol (mmol/L) -0.31 ± 0.68 -0.42 ± 0.68 0.78 0.44 Serum uric acid (µmol/L) 36.2 ± 78.3 48.1 ± 75.6 -0.75 0.46 LDL-C, low-density lipoprotein cholesterol 4. Discussion This retrospective study is the first to evaluate the effects of the extract from the flowers of A. manihot on IR and hsCRP in patients with DKD, to the best of our knowledge. In combination with standard care, A. manihot treatment over 12 months resulted in additional reductions in urinary protein levels and preservation of renal function, while also reducing hsCRP and improving IR, with a favorable safety profile. Our study population exhibited notable differences compared to previous investigations. We identified patients with DKD through renal biopsy, a method that not only reduced selection bias but also ensured the inclusion of individuals who required targeted management. In our cohort, the mean 24-h-UPE was approximately 2,600 mg, and the mean eGFR was 59 mL/min/1.73 m². IR is a critical underlying pathological change in diabetes. The gold standard for assessing its severity is the hyperinsulinemic euglycemic clamp, although this method is technically complex and difficult to implement. Consequently, other reliable biomarkers, such as HOMA-IR, are frequently used in clinical research, with higher HOMA-IR values indicating more pronounced IR. A 2025 study demonstrated an L-shaped relationship between HOMA-IR and DKD, with HOMA-IR showing strong predictive performance [ 11 ]. In a cohort of Chinese diabetic patients, those with HOMA-IR ≥ 5, falling within the highest quartile, exhibited a higher degree of IR [ 12 ]. Given that our study population already presents with proteinuria, a microvascular complication of diabetes, we have also selected HOMA-IR ≥ 5 as our inclusion criterion. The studies have shown that IR is closely associated with the onset and progression of DKD. In patients with type 2 diabetes, more severe IR is independently associated with microalbuminuria [ 13 ]. DBA2J db/db mice have been confirmed to have early albuminuria and glomerulosclerosis that correlate with systemic IR [ 14 ]. In diabetic patients with IR, elevated levels of inflammatory factors, such as Interleukin 1, Interleukin 6 and tumor necrosis factor (TNF) [ 15 ], not only exacerbate IR but also promote the progression of DKD [ 16 ], thereby forming a self-perpetuating cycle. The treatment of IR primarily involves two strategies: reducing body weight and using pharmacological interventions. For DKD patients, it is essential to avoid high-intensity calorie expenditure to prevent further strain on the kidneys. Although some anti-diabetic medications can improve IR, their effectiveness in slowing the progression of DKD remains unsatisfactory. Traditional Chinese medicine offers a novel approach through its ability to simultaneously target multiple pathways. The major pharmacologically active components in the flower extract of A. manihot are seven flavonoids, including Rutin, Hyperoside, Hibifolin, Isoquercetin, Myricetin, Quercetin, and Quercetin-3-O-robinobioside, as confirmed by modern pharmacological studies [ 17 ]. It has been approved by the China State Food and Drug Administration for chronic kidney disease treatment since 1999.Consistent with the results of Zhao et al. [ 18 ], Our findings indicated that patients taking A. manihot experienced a greater reduction in urinary protein at 6 months and exhibited protection of renal function with prolonged use. In addition, we also observed that patients taking A. manihot showed a significant decrease in hsCRP levels and an improvement in HOMA-IR, with a positive correlation between the changes in both. As a marker of systemic inflammation, hsCR can be upregulated through the transcription factor subunit p50 of NF-κB, as demonstrated in vitro studies [ 19 ]. NF-κB is a ubiquitously expressed transcription factor, and its activation is modulated by various stimuli, including TNF receptors and TLRs [ 20 ]. This indicates that hsCRP synthesis is regulated through multiple inflammatory pathways. Furthermore, CRP has been shown to play an active role in inducing hepatic IR in rat models [ 21 ]. In human subjects, CRP levels are typically elevated in individuals who are obese and IR, and these levels decrease in parallel with improvements in insulin sensitivity following weight loss. Notably, the relationship between CRP concentrations and IR is independent of obesity [ 22 ]. This suggests that CRP contributes to the pathophysiology of insulin resistance. Quercetin, a key component of A. manihot , has been shown in vitro to significantly inhibit CRP expression [ 23 ] and suppress the expression of other inflammatory mediators, such as inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) [ 24 ]. Additionally, rutin, another component, has been demonstrated to inhibit Nox4-induced oxidative stress and ROS-sensitive NLRP3 inflammasome activation, thereby protecting endothelial cell function [ 25 ]. Furthermore, A. manihot has been shown to modulate inflammatory responses in a 5/6 nephrectomy mouse model [ 26 ]. Oral administration of the drug significantly reduced the phosphorylation levels of PI3K, Akt, and ERK1/2, as well as the expression of endothelial nitric oxide synthase (eNOS), while decreasing renal fibrosis markers such as α-SMA, vimentin, and fibronectin. Other studies have also demonstrated that A. manihot ameliorates renal inflammation by reducing the expression of transforming growth factor (TGF)-α and TGF-β1 and by modulating the p38 MAPK signaling pathway [ 27 ]. This study had several limitations. First, it was a retrospective clinical study, and the data utilized were derived from past medical records. This inevitably introduced inaccuracies and incompleteness, potentially impacting the reliability of the analysis. Second, the study did not include DKD patients with low urinary protein levels who were not eligible for renal biopsy, an invasive procedure. Third, our study had a relatively small sample size and did not conduct subgroup analysis on pathology type, urinary protein, or eGFR changes. Finally, no in vitro studies have been conducted to validate the mechanism of hsCRP and IR in DKD patients; further research is needed to elucidate its exact detailed mechanism. Conclusion In biopsy-proven DKD patients with elevated hsCRP, A. manihot may enhance the effectiveness of standard care, as evidenced by significant improvements in urinary protein levels, a slowing of eGFR decline, and an improvement in IR. Our results provide valuable direction for further research on A. manihot in DKD, including large-scale cohort studies and in vitro investigations. Abbreviations DKD diabetic kidney disease IR insulin resistance A. Manihot Abelmoschus Manihot HOMA-IR Homeostatic Model Assessment of Insulin Resistance hsCRP high-sensitivity C-reactive protein eGFR estimated glomerular filtration rate Declarations Acknowledgements The authors would like to thank all of the participants for their time and effort. Disclosure statement No potential conflict of interest was reported by the authors. Author Contributions Conceptualization, W.L. and S.J.; methodology, S.J.; software, X.W.; validation, S.J. and H.G.; formal analysis, X.W and J.Z.; investigation, X.W and J.Z. and H.G; resources, X.G and H.G.; data curation, S.J.; writing—original draft preparation, X.W and J.Z.; writing—review and editing, S.J and J.L.; visualization, X.W.; supervision, W.L.; project administration, W.L.; funding acquisition, W.L and S.J. All authors have read and agreed to the published version of the manuscript. Funding This work was supported by grants from the National High Level Hospital Clinical Research Funding and Elite Medical Professionals Project of China-Japan Friendship Hospital (ZRJY2023-GG06), and National Natural Science Foundation of China (82300815). Data availability The datasets used and/or analyzed the current study available from the corresponding author on reasonable request. Ethics approval and consent to participate The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of China-Japan Friendship Hospital (2021-113-K71-1). All methods were carried out in accordance with relevant guidelines and regulations. Due to the retrospective retrieval of the patients data, the informed consent was waived. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Zhang L, Long J, Jiang W, et al. Trends in Chronic Kidney Disease in China. 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Efficacy and safety of Abelmoschus manihot capsule combined with ACEI/ARB on diabetic kidney disease: a systematic review and meta analysis. Front Pharmacol. 2023;14:1288159. 10.3389/fphar.2023.1288159 . Han W, Ma Q, Liu Y et al. Huangkui capsule alleviates renal tubular epithelial-mesenchymal transition in diabetic nephropathy via inhibiting NLRP3 inflammasome activation and TLR4/NF-κB signaling. Phytomedicine.2019;57:203–14. 10.1016/j.phymed.2018.12.021 Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28(7):412–9. 10.1007/BF00280883 . Tervaert TW, Mooyaart AL, Amann K, et al. Pathologic classification of diabetic nephropathy. J Am Soc Nephrol. 2010;21(4):556–63. 10.1681/ASN.2010010010 . Zhu H, Chen Y, Ding D, Chen H. Association between different insulin resistance indices and all-cause mortality in patients with diabetic kidney disease: a prospective cohort study. Front Endocrinol. 2024;15:1427727. 10.3389/fendo.2024.1427727 . Wang T, Li M, Zeng T, et al. Association Between Insulin Resistance and Cardiovascular Disease Risk Varies According to Glucose Tolerance Status: A Nationwide Prospective Cohort Study. Diabetes Care. 2022;45(8):1863–72. 10.2337/dc22-0202 . Parvanova AI, Trevisan R, Iliev IP, et al. Insulin resistance and microalbuminuria: a cross-sectional, case-control study of 158 patients with type 2 diabetes and different degrees of urinary albumin excretion. Diabetes. 2006;55(5):1456–62. 10.2337/db05-1484 . Ostergaard MV, Pinto V, Stevenson K, Worm J, Fink LN, Coward RJ. DBA2J db/db mice are susceptible to early albuminuria and glomerulosclerosis that correlate with systemic insulin resistance. Am J Physiol-Renal. 2017;312(2):F312–21. 10.1152/ajprenal.00451.2016 . Wu H, Ballantyne CM. Skeletal muscle inflammation and insulin resistance in obesity. J Clin Invest. 2017;127(1):43–54. 10.1172/JCI88880 . Rayego-Mateos S, Rodrigues-Diez RR, Fernandez-Fernandez B, et al. Targeting inflammation to treat diabetic kidney disease: the road to 2030. Kidney Int. 2023;103(2):282–96. 10.1016/j.kint.2022.10.030 . Li N, Tang H, Wu L, et al. Chemical constituents, clinical efficacy and molecular mechanisms of the ethanol extract of Abelmoschus manihot flowers in treatment of kidney diseases. Phytother Res. 2021;35(1):198–206. 10.1002/ptr.6818 . Zhao J, Tostivint I, Xu L, et al. Efficacy of Combined Abelmoschus manihot and Irbesartan for Reduction of Albuminuria in Patients With Type 2 Diabetes and Diabetic Kidney Disease: A Multicenter Randomized Double-Blind Parallel Controlled Clinical Trial. Diabetes Care. 2022;45(7):e113–5. 10.2337/dc22-0607 . McCarthy WC, Sherlock LG, Grayck MR, et al. Innate Immune Zonation in the Liver: NF-κB (p50) Activation and C-Reactive Protein Expression in Response to Endotoxemia Are Zone Specific. J Immunol. 2023;210(9):1372–85. 10.4049/jimmunol.2200900 . Rangan G, Wang Y, Harris D. NF-kappaB signalling in chronic kidney disease. Front Biosci-Landmrk. 2009;14(9):3496–522. 10.2741/3467 . Xi L, Xiao C, Bandsma RH, Naples M, Adeli K, Lewis GF. C-reactive protein impairs hepatic insulin sensitivity and insulin signaling in rats: role of mitogen-activated protein kinases. Hepatology. 2011;53(1):127–35. 10.2741/3467 . McLaughlin T, Abbasi F, Lamendola C et al. Differentiation between obesity and insulin resistance in the association with C-reactive protein.Circulation.2002;106(23):2908–12. 10.1161/01.cir.0000041046.32962.86 Kaur G, Rao LV, Agrawal A, Pendurthi UR. Effect of wine phenolics on cytokine-induced C-reactive protein expression. J Thromb Haemost. 2007;5(6):1309–17. 10.1111/j.1538-7836.2007.02527.x . Hu Y, Gui Z, Zhou Y, Xia L, Lin K, Xu Y. Quercetin alleviates rat osteoarthritis by inhibiting inflammation and apoptosis of chondrocytes, modulating synovial macrophages polarization to M2 macrophages. Free Radic Biol Med. 2019;145:146–60. 10.1016/j.freeradbiomed.2019.09.024 . Wang W, Wu QH, Sui Y, Wang Y, Qiu X. Rutin protects endothelial dysfunction by disturbing Nox4 and ROS-sensitive NLRP3 inflammasome. Biomed Pharmacother. 2017;86:32–40. 10.1016/j.biopha.2016.11.134 . Gu L, Hong F, Fan K, et al. Integrated Network Pharmacology Analysis and Pharmacological Evaluation to Explore the Active Components and Mechanism of Abelmoschus manihot (L.) Medik. on Renal Fibrosis. Drug Des Devel Ther. 2020;14:4053–67. 10.2147/DDDT.S264898 . Mao Z, Shen S, Wan Y, et al. Huangkui capsule attenuates renal fibrosis in diabetic nephropathy rats through regulating oxidative stress and p38MAPK/Akt pathways, compared to α-lipoic acid. J ETHNOPHARMACOL. 2015;173:256–65. 10.1016/j.jep.2015.07.036 . Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7003564","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":485954911,"identity":"cd7066ab-9339-42a5-9ccf-cb8433fe7631","order_by":0,"name":"Xiansen Wei","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiansen","middleName":"","lastName":"Wei","suffix":""},{"id":485954913,"identity":"88a7f3b1-a231-43e5-b5cc-d9756c2e4b65","order_by":1,"name":"Shimin Jiang","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shimin","middleName":"","lastName":"Jiang","suffix":""},{"id":485954914,"identity":"f78854e4-0845-46c8-93ea-4b933fda0061","order_by":2,"name":"Jiao Zhang","email":"","orcid":"","institution":"Beijing University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jiao","middleName":"","lastName":"Zhang","suffix":""},{"id":485954915,"identity":"e67ebcbe-f479-4e00-ac5d-882c01c8a951","order_by":3,"name":"Xia Gu","email":"","orcid":"","institution":"Chinese Academy of Medical Sciences \u0026 Peking Union Medical College","correspondingAuthor":false,"prefix":"","firstName":"Xia","middleName":"","lastName":"Gu","suffix":""},{"id":485954916,"identity":"38f1da28-7c7f-4175-b0a3-e49e2163e2a6","order_by":4,"name":"Hongmei Gao","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hongmei","middleName":"","lastName":"Gao","suffix":""},{"id":485954917,"identity":"54026d5a-c163-4639-8679-e9e40d40df77","order_by":5,"name":"Jian Lu","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Lu","suffix":""},{"id":485954918,"identity":"38befd20-8586-4153-bf99-3e6cd8cdc903","order_by":6,"name":"Wenge Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYBACPmYILQflMxPWwgZVY0yCFiid2EC8FnYew8cFv2zSt0tkJ35gqLBObGA/e4CAw3iMjWf2peXunJG7WYLhTHpiA09eAgEtvNukeXsO5264kbuNgbHtcGKDBI8BIS3bf/P2/E83AGv5R5yWbcw8Pw4kQLQ0EKWF/7M0b0Oy4c6et5slEo6lG7fx5ODXws9/LPEzzx87eXP23I0fPtRYy/azn8GvBQwY2xgYwMoSGBAxRQD8gWoZBaNgFIyCUYANAACKbD5JP0r1GgAAAABJRU5ErkJggg==","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":true,"prefix":"","firstName":"Wenge","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2025-06-29 15:23:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7003564/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7003564/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12882-025-04531-3","type":"published","date":"2025-11-26T15:57:01+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87033644,"identity":"1583d8f4-7938-4c81-8073-4bebb77333ba","added_by":"auto","created_at":"2025-07-18 13:07:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1493317,"visible":true,"origin":"","legend":"\u003cp\u003eStudy population flowchart. DKD, diabetic kidney disease; HOMA-IR,homeostatic model assessment of insulin resistance; hsCRP, high-sensitivity C-reactive protein; Manihot, Abelmoschus manihot.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7003564/v1/00f540de25c2404eb485558f.png"},{"id":87035623,"identity":"d2009dce-7237-4e8b-b8e2-927956bfcef5","added_by":"auto","created_at":"2025-07-18 13:15:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":7618558,"visible":true,"origin":"","legend":"\u003cp\u003eDemonstration of Laboratory Analyses between two groups. (A) Changes of 24-hour urine protein excretion (24-h-UPE), Δ24-h-UPE = 24-h-UPE (Follow-up) - 24-h-UPE (Baseline); (B) Changes of estimated Glomerular Filtration Rate (eGFR), ΔeGFR = eGFR (Follow-up) - eGFR (Baseline); (C) 24-h-UPE during follow up; (D) eGFR during follow up. Manihot, Abelmoschus manihot. Values are presented as mean ± standard deviation. \u003csup\u003e*\u003c/sup\u003ebetween-group comparison with P \u0026lt; 0.01. \u003csup\u003e\u0026amp;\u003c/sup\u003ewithin-group comparison (compared to 3 months ago) with P \u0026lt; 0.05. \u003csup\u003e#\u003c/sup\u003ewithin-group comparison (compared to 6 months ago) with P \u0026lt; 0.05. \u003csup\u003e##\u003c/sup\u003ewithin-group comparison (compared to 6 months ago) with P\u0026lt;0.01\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7003564/v1/5a352fe062d914fc7acdf30a.png"},{"id":87035619,"identity":"be5e563d-7040-4da4-b920-048f3a435be3","added_by":"auto","created_at":"2025-07-18 13:15:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":720355,"visible":true,"origin":"","legend":"\u003cp\u003eChanges of HOMA-IR and hsCRP. HOMA-IR, homeostatic model assessment of insulin resistance; hsCRP, high-sensitivity C-reactive protein. Values are presented as median (interquartile range). \u003csup\u003e*\u003c/sup\u003eintergroup comparison with P\u0026lt;0.05; \u003csup\u003e##\u003c/sup\u003ewithin-group comparison (compared to 6 months ago) with P \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7003564/v1/538b6e3877607672ef7fb505.png"},{"id":87037340,"identity":"9d2fd735-95f4-4725-9d4f-fffdc52e5450","added_by":"auto","created_at":"2025-07-18 13:23:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1412459,"visible":true,"origin":"","legend":"\u003cp\u003ePositive correlations of the changes in HOMA with the changes of hs-CRP. HOMA-IR, homeostatic model assessment of insulin resistance; hsCRP, high-sensitivity C-reactive protein.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7003564/v1/fe4be2c65072076c0089dfd3.png"},{"id":97178772,"identity":"0d4174d3-24ce-4f6e-ac92-57baabbeff52","added_by":"auto","created_at":"2025-12-01 16:13:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":10931020,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7003564/v1/532a652d-f803-4d57-aab0-10bef961dbea.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Abelmoschus manihot alleviates insulin resistance in biopsy-proven diabetic kidney disease through attenuation of inflammation","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eDiabetic kidney disease (DKD) is the leading cause of end-stage kidney failure, accounting for 45% of cases requiring dialysis [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Its increasing prevalence poses a significant and growing threat to patient well-being and exacerbates the strain on healthcare systems.\u003c/p\u003e\u003cp\u003eThe standard care recommended by the American Diabetes Association includes the use of renin-angiotensin system inhibitors (RASi), non-steroidal mineralocorticoid receptor antagonists (MRAs), and sodium-glucose cotransporter-2 (SGLT2) inhibitors to reduce proteinuria and slow the progression of renal function deterioration. Despite improving blood glucose control and renal protection, a residual risk of chronic kidney disease progression remains [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eInsulin resistance (IR) is a key characteristic of type 2 diabetes and one of its fundamental pathological mechanisms, closely associated with the development of both macrovascular and microvascular complications (including DKD). IR is affected by genetic predisposition, lifestyle factors [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], as well as chronic microinflammation [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], which is also considered a contributing factor to the residual risk of DKD. In the renal tissues of diabetic individuals, nuclear factor kappa B (NF-κB) is activated, leading to the overexpression of chemotactic factors including monocyte chemoattractant protein-1 (MCP-1) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAlthough previous studies have shown that the combination of \u003cem\u003eAbelmoschus Manihot (A. Manihot)\u003c/em\u003e and irbesartan is effective in reducing proteinuria [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], and animal experiments have demonstrated its potential to modulate the inflammatory response by inhibiting the TLR4/NF-κB pathway [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], there is currently a lack of research on the effects of \u003cem\u003eA. manihot\u003c/em\u003e on IR and chronic microinflammation in patients with DKD. Therefore, the primary objective of this retrospective analysis is to evaluate the impact of combining \u003cem\u003eA. manihot\u003c/em\u003e with standard treatment on IR and hs-CRP levels in DKD patients.\u003c/p\u003e"},{"header":"2 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study Design\u003c/h2\u003e\u003cp\u003eThis was a retrospective study involving 511 biopsy-proven DKD patients recruited from the Department of Nephrology at China-Japan Friendship Hospital. The inclusion criteria and grouping were (1) Patients aged 18\u0026ndash;75 years involved between January 1, 2012, and December 31, 2023. (2) Patients diagnosed with DKD, confirmed by renal pathology. (3) Patients receiving \u003cem\u003eA. manihot\u003c/em\u003e treatment were allocated to the \u003cem\u003emanihot\u003c/em\u003e group, whereas those with comparable eGFR and proteinuria levels who did not receive \u003cem\u003eA. manihot\u003c/em\u003e treatment were assigned to the control group. The date of the initial prescription of \u003cem\u003eA. manihot\u003c/em\u003e or standard care medications following renal biopsy was taken as the baseline for both cohorts. (4) All patients had an estimated glomerular filtration rate (eGFR)\u0026thinsp;\u0026gt;\u0026thinsp;30 mL/min/1.73 m\u003csup\u003e2\u003c/sup\u003e, 24-hour urine protein excretion (24-h-UPE)\u0026thinsp;\u0026gt;\u0026thinsp;1 g. (5) Homeostatic Model Assessment of Insulin Resistance (HOMA-IR)\u0026thinsp;\u0026ge;\u0026thinsp;5 and high-sensitivity C-reactive protein (hsCRP)\u0026thinsp;\u0026ge;\u0026thinsp;1 mg/L. All measurements were obtained within 2 weeks of the study baseline. (6) The patients were monitored during the follow-up period, with at least four 24-h-UPE and eGFR measurements and at least one HOMA-IR and hsCRP measurement. Exclusion criteria were (1) Type 1 diabetes. (2) Coexisting non-DKDs. (3) Tumors or chronic infectious diseases. (4) the treatment regimen involving insulin or its analogues (5) Acute diseases occurring within 4 weeks prior to baseline and up to 4 weeks after the conclusion of follow-up assessments.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Treatment Regimen\u003c/h2\u003e\u003cp\u003eBoth patient groups were free of contraindications and underwent a standard care regimen comprising RASi, SGLT2 inhibitors, and MRAs. Patients in the \u003cem\u003emanihot\u003c/em\u003e group took five Huangkui capsules (Suzhong Pharmaceutical Group Co., Ltd., Taizhou, China) thrice daily (6.45 g/day). Prescription details were recorded throughout the follow-up period, ensuring a maximum interval of 2 months between consecutive prescriptions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Data Collection\u003c/h2\u003e\u003cp\u003eThe pooled medical history data included date of birth, sex, height, weight ,blood pressure, duration of diabetes, presence of retinopathy, concomitant medications (SGLT2 inhibitors, RASi, sacubitril/valsartan, or MRAs), comorbidities (hypertension, cardiovascular and cerebrovascular diseases, or peripheral arterial disease), medication adverse reactions during the follow-up period and acute diseases occurring within 4 weeks prior to baseline and up to 4 weeks after the conclusion of follow-up assessments .\u003c/p\u003e\u003cp\u003eLaboratory test results were collected at baseline, 2\u0026ndash;4 months, 5\u0026ndash;7 months, 8\u0026ndash;10 months, and 11\u0026ndash;13 months. These included serum creatinine, 24-h-UPE, serum albumin, and glycated hemoglobin, as well as items from blood routine and liver function tests. The CKD-EPI equation, adjusted for sex, age, and serum creatinine, was used to calculate eGFR. The HOMA-IR was calculated as (fasting insulin [\u0026micro;IU/mL] \u0026times; fasting glucose [mmol/L])/22.5 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAccording to the classification criteria for DKD pathology published in the American Journal of Kidney Diseases [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], the following parameters were evaluated: global and segmental glomerulosclerosis, interstitial fibrosis and tubular atrophy (IFTA), interstitial inflammation, arteriolar hyalinosis, and arteriosclerosis. The scoring for glomerulosclerosis and IFTA was based on the proportion of tissue affected by each lesion, categorized as follows: 0 for 0\u0026ndash;10%, 1 for 10\u0026ndash;25%, 2 for 26\u0026ndash;50%, and 3 for \u0026gt;\u0026thinsp;50%. Interstitial inflammation was graded as 0 for absent, 1 for infiltration only related to IFTA, and 2 for infiltration in areas without IFTA. Arteriolar hyalinosis was scored as 0 when absent and 1 when at least one area was affected. Arteriosclerosis was scored based on the thickness of intima compared to media, as follows: 0 for intimal thickening less than media and 1 for intimal thickening equal to or greater than media. The scores of these components were summed to derive the total chronicity score, categorized as minimal for a score of 0\u0026ndash;1, mild for 2\u0026ndash;4, moderate for 5\u0026ndash;7, and severe for 8\u0026ndash;10. Scoring was completed by two renal pathology experts, with discrepancies resolved through consensus. The patients\u0026rsquo; final outcomes were not known at the time of scoring.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Outcomes\u003c/h2\u003e\u003cp\u003eThe primary outcomes were the changes of HOMA-IR, hsCRP,24-h-UPE and eGFR compared to baseline at different time points. The formulas for calculating these changes were as follows:\u003c/p\u003e\u003cp\u003eΔ24-h-UPE\u0026thinsp;=\u0026thinsp;24-h-UPE (follow-up)\u0026thinsp;\u0026minus;\u0026thinsp;24-h-UPE (baseline)\u003c/p\u003e\u003cp\u003eΔeGFR\u0026thinsp;=\u0026thinsp;eGFR (follow-up)\u0026thinsp;\u0026minus;\u0026thinsp;eGFR (baseline)\u003c/p\u003e\u003cp\u003eΔHOMA-IR\u0026thinsp;=\u0026thinsp;HOMA-IR (follow-up)\u0026thinsp;\u0026minus;\u0026thinsp;HOMA-IR (baseline)\u003c/p\u003e\u003cp\u003eΔhsCRP\u0026thinsp;=\u0026thinsp;hsCRP (follow-up)\u0026thinsp;\u0026minus;\u0026thinsp;hsCRP (baseline)\u003c/p\u003e\u003cp\u003eThe secondary outcomes included comparisons of 24-h-UPE, eGFR, and major cardiovascular and cerebrovascular events (MACE) before and after treatment between the groups. Safety indicators were assessed based on comparisons of voluntarily reported adverse events and various laboratory parameters, including blood routine and liver function tests.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Statistical Analysis\u003c/h2\u003e\u003cp\u003eContinuous variables were assessed for normality of distribution using the Shapiro-Wilk test. Data conforming to a normal distribution are reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. For data with skewed distributions, descriptive statistics are presented, including the median, first quartile, and third quartile. Qualitative data are presented as percentages or composition ratios. Continuous variables with a normal distribution were compared using the \u003cem\u003et\u003c/em\u003e-test, while the Wilcoxon signed-rank test or Mann-Whitney U test was applied to non-normally distributed variables, depending on whether the comparison was within or between groups. Correlation between changes in hs-CRP and HOMA-IR was assessed using Spearman's rank correlation test. Composition ratios were compared using the chi-square or Fisher\u0026rsquo;s exact test. All tests were two-tailed, with statistical significance set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. All analyses were conducted using SPSS Statistics for Windows (version 27.0; IBM Corp., Armonk, NY, USA).\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Demographic and Clinical Characteristics\u003c/h2\u003e\u003cp\u003eBetween January 1, 2012, and December 31, 2023, 511 patients were diagnosed with DKD through renal biopsy. After applying the exclusion criteria, 170 patients were included at baseline, comprising 84 females and 86 males. Among them, 81 patients received standard care, while 89 patients took \u003cem\u003eA. manihot\u003c/em\u003e in addition to receiving standard care. However, 29 patients had incomplete laboratory results, and 14 patients developed acute infectious diseases. 26 patients were excluded due to irregular medication intake. Eventually, a total of 94 patients completed 12 months of treatment (49 in the \u003cem\u003emanihot\u003c/em\u003e group and 45 in the control group), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAt baseline, there were no statistically significant differences in age, duration of diabetes, retinopathy, or macrovascular disease between the groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Similarly, comparisons of the renal protective medications revealed no statistical differences between the two groups. In terms of histopathological findings, there were no statistically significant differences in glomerular, tubule-interstitial, or vascular lesions between the two groups. Detailed baseline characteristics of renal histopathological data are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBaseline clinical features of the two groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eManihot group (n\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl group (n\u0026thinsp;=\u0026thinsp;45)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTest statistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e58.4\u0026thinsp;\u0026plusmn;\u0026thinsp;7.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e57.6\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28 (57.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 (48.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21 (42.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (51.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBody Weight Index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSystolic BP (mmHg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e137\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e136\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiastolic BP (mmHg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e76.3\u0026thinsp;\u0026plusmn;\u0026thinsp;12.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.8\u0026thinsp;\u0026plusmn;\u0026thinsp;11.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of diabetes\u003c/p\u003e\u003cp\u003e(months)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e54 (36, 68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e55 (40, 68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetic retinopathy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30 (61.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33 (73.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMacrovascular complication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35 (71.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35 (77.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum albumin (g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.22\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.66\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHemoglobin A1c (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.2 (6.7, 7.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.3 (6.8, 7.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1154\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eeGFR (ml/min/1.73m2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e59.0\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.77\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e24-h-UPE (mg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2642\u0026thinsp;\u0026plusmn;\u0026thinsp;484\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2669\u0026thinsp;\u0026plusmn;\u0026thinsp;461\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ehsCRP (mg/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.7 (6.2, 18.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.6 (6.1, 16.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1096\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDL-C (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriacylglycerol (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum uric acid (\u0026micro;mol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e391\u0026thinsp;\u0026plusmn;\u0026thinsp;102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e396\u0026thinsp;\u0026plusmn;\u0026thinsp;84.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDPP-4i\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (26.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (20.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGLP-1RA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10 (20.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (24.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSGLT2i\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20 (40.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (33.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsulin analogs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34 (69.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33 (73.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACEIs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10 (20.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (26.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eARBs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21 (42.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (35.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSacubitril valsartan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (34.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (40.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFinerenone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (24.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (31.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiuretics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28 (57.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 (53.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eData are expressed in mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or mean (25th percentile, 75th percentile). Manihot, Abelmoschus Manihot; eGFR, estimated Glomerular Filtration Rate; 24-h-UPE, 24-hour urine protein excretion; hsCRP,high-sensitivity C-reactive protein; LDL-C, Low-density Lipoprotein Cholesterol; GLP-1RA, glucagon-like peptide-1 (GLP-1) receptor agonists; DPP-4i, Dipeptidyl peptidase-4 inhibitors; SGLT2i,Sodium-glucose cotransporter 2 inhibitors; ACEIs, angiotensin-converting enzyme inhibitors; ARBs, angiotensin II receptor blockers.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBaseline histopathological features of the two groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eManihot group\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl group (n\u0026thinsp;=\u0026thinsp;45)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTest statistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003cp\u003eof intact glomeruli\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (10, 27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17 (8, 20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1386\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlobal and segmental glomerulosclerosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIIa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (26.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (28.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIIb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27 (55.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21 (46.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIII\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (18.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (24.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInterstitial fibrosis and tubular atrophy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (14.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (10.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20 (40.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 (48.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (34.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (22.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (10.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (8.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInterstitial inflammation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (24.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (31.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34 (69.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27 (60.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (6.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (8.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArteriolar hyalinosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (24.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (33.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24 (48.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (42.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (26.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (24.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArteriosclerosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28 (57.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (42.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (36.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 (48.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (6.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (8.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal chronicity score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMild\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (28.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (31.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24 (48.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25 (55.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSevere\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (22.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (13.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eManihot, Abelmoschus manihot.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Changes in 24-h-UPE\u003c/h2\u003e\u003cp\u003eAt baseline, the 24-h-UPE values for the standard care and \u003cem\u003eA. manihot\u003c/em\u003e groups were 2,640\u0026thinsp;\u0026plusmn;\u0026thinsp;390 mg and 2,673\u0026thinsp;\u0026plusmn;\u0026thinsp;368 mg, respectively, with no significant difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.66). After 3 months of treatment, no statistically significant differences were observed between the groups. However, by the 6-month follow-up, a significant decrease in urinary protein was observed in the \u003cem\u003eA. manihot\u003c/em\u003e group (\u0026minus;\u0026thinsp;232.9\u0026thinsp;\u0026plusmn;\u0026thinsp;206.5 mg \u003cem\u003evs\u003c/em\u003e \u0026minus;\u0026thinsp;145.8\u0026thinsp;\u0026plusmn;\u0026thinsp;210.6 mg, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04). The differences between the two groups became more pronounced at the 9- and 12-month follow-ups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). These findings suggested that supplementing standard care with \u003cem\u003eA. manihot\u003c/em\u003e could lead to a further reduction in urinary protein, with a progressively greater impact over time.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWithin-group comparisons revealed a significant decrease in urinary protein for the \u003cem\u003eA. manihot\u003c/em\u003e group compared to baseline (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04). In the group, the rate of urinary protein reduction was fastest during the initial 3 months of treatment, and there was a statistically significant difference between the 6- and 3-month time points. Similar differences were also observed at 9 months compared to 3 months.\u003c/p\u003e\u003cp\u003eIn the \u003cem\u003eA. manihot\u003c/em\u003e group, the rate of urinary protein reduction was fastest during the initial 3 months of treatment. Statistically significant differences were also observed between the 3rd and 6th months (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), as well as between the 3rd and 9th months (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In the control group, a significant decrease in urinary protein was observed only when comparing the values at the 3rd and 9th month (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003eComparison of 24-h-UPE between the two groups showed statistically significant differences at 9 and 12 months (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Changes in eGFR\u003c/h2\u003e\u003cp\u003eAt baseline, the eGFRs for the \u003cem\u003eA. manihot\u003c/em\u003e and control groups were 59.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8 and 59.0\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2 mL/min/1.73 m\u003csup\u003e2\u003c/sup\u003e, respectively, showing no significant difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.77). Throughout the follow-up period, the \u003cem\u003eA. manihot\u003c/em\u003e group showed a slower decline in eGFR compared to the control group, with the difference becoming increasingly evident over time and reaching statistical significance at 9 and 12 months (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003eIn the control group, there was a notable decline in eGFR between consecutive time points. However, in the \u003cem\u003eA. manihot\u003c/em\u003e group, statistically significant differences were only observed when comparing alternating adjacent time points.\u003c/p\u003e\u003cp\u003eThe eGFR levels in the two groups are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD. At 12 months, the eGFR in the \u003cem\u003eA. manihot\u003c/em\u003e group was higher than that in the control group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.035, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Changes in HOMA-IR\u003c/h2\u003e\u003cp\u003eAt baseline, there was no significant difference in HOMA-IR levels between the two groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.93). By 12 months, both groups exhibited a decline in HOMA-IR levels. Wilcoxon signed-rank test revealed the reduction in HOMA-IR levels among patients in the \u003cem\u003eA. manihot\u003c/em\u003e group a statistic of 211.5 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03), indicating a significant difference between pre- and post-treatment measurements.\u003c/p\u003e\u003cp\u003eWilcoxon signed-rank test revealed a statistic of 211.5 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating a significant reduction in HOMA-IR levels between pre- and post-treatment measurements in the \u003cem\u003eA. manihot\u003c/em\u003e group, while no significant change was observed in the control group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.21, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). At 12 months, the \u003cem\u003eA. manihot\u003c/em\u003e group exhibited a significantly greater decrease in HOMA-IR levels than the control group, as evidenced by a Mann-Whitney U statistic of 895.5 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Changes in hsCRP\u003c/h2\u003e\u003cp\u003eAt baseline, there was no significant difference in hsCRP levels between the two groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.80). By 12 months, both groups exhibited a decline in hsCRP levels. The reduction in hsCRP among patients in the \u003cem\u003eA. manihot\u003c/em\u003e group was statistically significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while that in the control group did not reach statistical significance (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.10). At 12 months, the decrease in hsCRP levels was significantly more pronounced in the \u003cem\u003eA. manihot\u003c/em\u003e group compared to the control group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003eSpearman's rank correlation test was employed to explore the relationship between the changes in hsCRP and HOMA-IR. In the \u003cem\u003eA. manihot\u003c/em\u003e group, a positive correlation was observed between the decrease in hsCRP and the decrease in HOMA-IR, with a ρ of 0.48 and P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, indicating statistical significance. In contrast, no such correlation was observed in the control group, where the ρ was 0.25 and the P-value was 0.1, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.6 MACEs\u003c/h2\u003e\u003cp\u003eIR is an important risk factor for macrovascular complications in diabetes. We evaluated the occurrence of MACE during the follow-up period. A total of 3 MACEs were recorded, with 1 patient in the \u003cem\u003eA. manihot\u003c/em\u003e group experiencing acute myocardial infarction, and 2 patients in the control group, who developed acute myocardial infarction and cerebral infarction, respectively. Fisher's exact test was performed, yielding a p-value of 0.605, indicating no statistically significant difference\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.7 Adverse Events\u003c/h2\u003e\u003cp\u003eAccording to the patients' medical records, there were four individuals in the \u003cem\u003eA. manihot\u003c/em\u003e group who developed gastric distension, and three patients in the control group who experienced mild dizziness and/or fatigue. All of them had mild symptoms and were able to continue treatment after receiving symptomatic treatment. Laboratory examinations indicated no significant differences in complete blood counts, serum electrolytes, coagulation parameters, or liver function tests between the two groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), indicating that \u003cem\u003eA. manihot\u003c/em\u003e did not result in any abnormalities in the safety indicators (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of safety parameters following treatment in both groups.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eManihot group\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl group (n\u0026thinsp;=\u0026thinsp;45)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003et\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhite blood cells (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRed blood cells (\u0026times;10\u003csup\u003e12\u003c/sup\u003e/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePlatelets (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e-12.6\u0026thinsp;\u0026plusmn;\u0026thinsp;108\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e-35.0\u0026thinsp;\u0026plusmn;\u0026thinsp;96.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlanine aminotransferase (U/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.92\u0026thinsp;\u0026plusmn;\u0026thinsp;18.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e8.68\u0026thinsp;\u0026plusmn;\u0026thinsp;15.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum total bilirubin (\u0026micro;mol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e3.56\u0026thinsp;\u0026plusmn;\u0026thinsp;3.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e2.84\u0026thinsp;\u0026plusmn;\u0026thinsp;3.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum total protein (g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e-4.02\u0026thinsp;\u0026plusmn;\u0026thinsp;3.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e-4.21\u0026thinsp;\u0026plusmn;\u0026thinsp;2.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlkaline phosphatase (U/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e12.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e13.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFibrinogen (g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum potassium (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHemoglobin A1c (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e-0.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e-0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDL-C (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e-0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e-0.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriacylglycerol (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e-0.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e-0.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum uric acid (\u0026micro;mol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e36.2\u0026thinsp;\u0026plusmn;\u0026thinsp;78.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.1\u0026thinsp;\u0026plusmn;\u0026thinsp;75.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eLDL-C, low-density lipoprotein cholesterol\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis retrospective study is the first to evaluate the effects of the extract from the flowers of \u003cem\u003eA. manihot\u003c/em\u003e on IR and hsCRP in patients with DKD, to the best of our knowledge. In combination with standard care, \u003cem\u003eA. manihot\u003c/em\u003e treatment over 12 months resulted in additional reductions in urinary protein levels and preservation of renal function, while also reducing hsCRP and improving IR, with a favorable safety profile.\u003c/p\u003e\u003cp\u003eOur study population exhibited notable differences compared to previous investigations. We identified patients with DKD through renal biopsy, a method that not only reduced selection bias but also ensured the inclusion of individuals who required targeted management. In our cohort, the mean 24-h-UPE was approximately 2,600 mg, and the mean eGFR was 59 mL/min/1.73 m\u0026sup2;.\u003c/p\u003e\u003cp\u003eIR is a critical underlying pathological change in diabetes. The gold standard for assessing its severity is the hyperinsulinemic euglycemic clamp, although this method is technically complex and difficult to implement. Consequently, other reliable biomarkers, such as HOMA-IR, are frequently used in clinical research, with higher HOMA-IR values indicating more pronounced IR. A 2025 study demonstrated an L-shaped relationship between HOMA-IR and DKD, with HOMA-IR showing strong predictive performance [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In a cohort of Chinese diabetic patients, those with HOMA-IR\u0026thinsp;\u0026ge;\u0026thinsp;5, falling within the highest quartile, exhibited a higher degree of IR [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Given that our study population already presents with proteinuria, a microvascular complication of diabetes, we have also selected HOMA-IR\u0026thinsp;\u0026ge;\u0026thinsp;5 as our inclusion criterion.\u003c/p\u003e\u003cp\u003eThe studies have shown that IR is closely associated with the onset and progression of DKD. In patients with type 2 diabetes, more severe IR is independently associated with microalbuminuria [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. DBA2J db/db mice have been confirmed to have early albuminuria and glomerulosclerosis that correlate with systemic IR [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In diabetic patients with IR, elevated levels of inflammatory factors, such as Interleukin 1, Interleukin 6 and tumor necrosis factor (TNF) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], not only exacerbate IR but also promote the progression of DKD [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], thereby forming a self-perpetuating cycle.\u003c/p\u003e\u003cp\u003eThe treatment of IR primarily involves two strategies: reducing body weight and using pharmacological interventions. For DKD patients, it is essential to avoid high-intensity calorie expenditure to prevent further strain on the kidneys. Although some anti-diabetic medications can improve IR, their effectiveness in slowing the progression of DKD remains unsatisfactory. Traditional Chinese medicine offers a novel approach through its ability to simultaneously target multiple pathways.\u003c/p\u003e\u003cp\u003eThe major pharmacologically active components in the flower extract of \u003cem\u003eA. manihot\u003c/em\u003e are seven flavonoids, including Rutin, Hyperoside, Hibifolin, Isoquercetin, Myricetin, Quercetin, and Quercetin-3-O-robinobioside, as confirmed by modern pharmacological studies [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. It has been approved by the China State Food and Drug Administration for chronic kidney disease treatment since 1999.Consistent with the results of Zhao et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], Our findings indicated that patients taking \u003cem\u003eA. manihot\u003c/em\u003e experienced a greater reduction in urinary protein at 6 months and exhibited protection of renal function with prolonged use. In addition, we also observed that patients taking \u003cem\u003eA. manihot\u003c/em\u003e showed a significant decrease in hsCRP levels and an improvement in HOMA-IR, with a positive correlation between the changes in both.\u003c/p\u003e\u003cp\u003eAs a marker of systemic inflammation, hsCR can be upregulated through the transcription factor subunit p50 of NF-κB, as demonstrated \u003cem\u003ein vitro\u003c/em\u003e studies [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. NF-κB is a ubiquitously expressed transcription factor, and its activation is modulated by various stimuli, including TNF receptors and TLRs [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This indicates that hsCRP synthesis is regulated through multiple inflammatory pathways. Furthermore, CRP has been shown to play an active role in inducing hepatic IR in rat models [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In human subjects, CRP levels are typically elevated in individuals who are obese and IR, and these levels decrease in parallel with improvements in insulin sensitivity following weight loss. Notably, the relationship between CRP concentrations and IR is independent of obesity [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This suggests that CRP contributes to the pathophysiology of insulin resistance.\u003c/p\u003e\u003cp\u003eQuercetin, a key component of \u003cem\u003eA. manihot\u003c/em\u003e, has been shown in vitro to significantly inhibit CRP expression [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and suppress the expression of other inflammatory mediators, such as inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Additionally, rutin, another component, has been demonstrated to inhibit Nox4-induced oxidative stress and ROS-sensitive NLRP3 inflammasome activation, thereby protecting endothelial cell function [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Furthermore, \u003cem\u003eA. manihot\u003c/em\u003e has been shown to modulate inflammatory responses in a 5/6 nephrectomy mouse model [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Oral administration of the drug significantly reduced the phosphorylation levels of PI3K, Akt, and ERK1/2, as well as the expression of endothelial nitric oxide synthase (eNOS), while decreasing renal fibrosis markers such as α-SMA, vimentin, and fibronectin. Other studies have also demonstrated that \u003cem\u003eA. manihot\u003c/em\u003e ameliorates renal inflammation by reducing the expression of transforming growth factor (TGF)-α and TGF-β1 and by modulating the p38 MAPK signaling pathway [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study had several limitations. First, it was a retrospective clinical study, and the data utilized were derived from past medical records. This inevitably introduced inaccuracies and incompleteness, potentially impacting the reliability of the analysis. Second, the study did not include DKD patients with low urinary protein levels who were not eligible for renal biopsy, an invasive procedure. Third, our study had a relatively small sample size and did not conduct subgroup analysis on pathology type, urinary protein, or eGFR changes. Finally, no in vitro studies have been conducted to validate the mechanism of hsCRP and IR in DKD patients; further research is needed to elucidate its exact detailed mechanism.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn biopsy-proven DKD patients with elevated hsCRP, \u003cem\u003eA. manihot\u003c/em\u003e may enhance the effectiveness of standard care, as evidenced by significant improvements in urinary protein levels, a slowing of eGFR decline, and an improvement in IR. Our results provide valuable direction for further research on \u003cem\u003eA. manihot\u003c/em\u003e in DKD, including large-scale cohort studies and in vitro investigations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eDKD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; diabetic kidney disease\u003c/p\u003e\n\u003cp\u003eIR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;insulin resistance\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eA. Manihot\u003c/em\u003e\u003cem\u003e\u0026nbsp;Abelmoschus Manihot\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHOMA-IR \u0026nbsp; \u0026nbsp; Homeostatic Model Assessment of Insulin Resistance\u003c/p\u003e\n\u003cp\u003ehsCRP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;high-sensitivity C-reactive protein\u003c/p\u003e\n\u003cp\u003eeGFR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; estimated glomerular filtration rate\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank all of the participants for their time and effort.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo potential conflict of interest was reported by the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, W.L. and S.J.; methodology, S.J.; software, X.W.; validation, S.J. and H.G.; formal analysis, X.W and J.Z.; investigation, X.W and J.Z. and H.G; resources, X.G and H.G.; data curation, S.J.; writing\u0026mdash;original draft preparation, X.W and J.Z.; writing\u0026mdash;review and editing, S.J and J.L.; visualization, X.W.; supervision, W.L.; project administration, W.L.; funding acquisition, W.L and S.J. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the National High Level Hospital Clinical Research Funding and Elite Medical Professionals Project of China-Japan Friendship Hospital (ZRJY2023-GG06), and National Natural Science Foundation of China (82300815).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of China-Japan Friendship Hospital (2021-113-K71-1). All methods were carried out in accordance with relevant guidelines and regulations. Due to the retrospective retrieval of the patients data, the informed consent was waived.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZhang L, Long J, Jiang W, et al. Trends in Chronic Kidney Disease in China. 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Huangkui capsule attenuates renal fibrosis in diabetic nephropathy rats through regulating oxidative stress and p38MAPK/Akt pathways, compared to α-lipoic acid. J ETHNOPHARMACOL. 2015;173:256\u0026ndash;65. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jep.2015.07.036\u003c/span\u003e\u003cspan address=\"10.1016/j.jep.2015.07.036\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Abelmoschus manihot, diabetic kidney disease, insulin resistance, high-sensitivity C-reactive protein, proteinuria, glomerular filtration rate","lastPublishedDoi":"10.21203/rs.3.rs-7003564/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7003564/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Research is lacking on the effects of \u003cem\u003eAbelmoschus Manihot \u003c/em\u003eon insulin resistance (IR) and chronic microinflammation in patients with diabetic kidney disease (DKD). This study aims to explore the effects of \u003cem\u003eAbelmoschus Manihot \u003c/em\u003eon\u003cem\u003e \u003c/em\u003eIR and high-sensitivity C-reactive protein (hs-CRP) levels in DKD, as well as to analyze the relationship between the two factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eBiopsy-proven DKD patients with a homeostatic model assessment of IR (HOMA-IR) ≥ 5 and hsCRP ≥ 1 mg/L were recruited from the Department of Nephrology at China-Japan Friendship Hospital between January 2012 and December 2023. All patients received standard care medications, and those in the \u003cem\u003eManihot\u003c/em\u003e group were treated with \u003cem\u003eAbelmoschus Manihot\u003c/em\u003e for 12 months. Participants were followed up every 3 months for a total of 1 year. Changes in HOMA-IR, hsCRP, 24-hour urine protein excretion (24-h-UPE), and estimated glomerular filtration rate (eGFR) from baseline during follow-up were assessed. Additionally, differences in 24-h-UPE, eGFR, and major cardiovascular and cerebrovascular events between the groups after treatment were evaluated. Adverse events and laboratory test abnormalities were also recorded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eA total of 94 biopsy-proven DKD patients were included. Among them, 45 patients received standard care (control group), while 49 additionally took standard care plus \u003cem\u003eAbelmoschus Manihot\u003c/em\u003e. The results revealed a statistically significant reduction in 24-h-UPE in the \u003cem\u003emanihot\u003c/em\u003e group compared to the control group at 6 months (−232.9 \u003cem\u003evs \u003c/em\u003e−145.8 mg, \u003cem\u003eP\u003c/em\u003e = 0.04) and beyond. Since the 9-month follow-ups, the \u003cem\u003emanihot\u003c/em\u003e group exhibited a significantly slower eGFR decline (-3.2\u003cem\u003e vs \u003c/em\u003e-4.7 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e, P \u0026lt; 0.05). Additionally, IR in the \u003cem\u003emanihot\u003c/em\u003e group was significantly reduced in both within- and between-groups (compared to the control), and hsCRP also exhibited analogous findings. In the \u003cem\u003emanihot\u003c/em\u003e group, a significant positive correlation was observed between the decrease in hsCRP and the decrease in HOMA-IR, with P-value \u0026lt; 0.01. In contrast, no such significant correlation was observed in the control group, where the P-value was 0.1. No significant adverse events or laboratory test abnormalities were observed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThis study demonstrates that in biopsy-confirmed DKD patients, \u003cem\u003eA. manihot \u003c/em\u003enot only enhances the clinical outcomes of standard care,but also significantly alleviaties IR, potentially through its anti-inflammatory effects.\u003c/p\u003e","manuscriptTitle":"Abelmoschus manihot alleviates insulin resistance in biopsy-proven diabetic kidney disease through attenuation of inflammation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-18 13:07:36","doi":"10.21203/rs.3.rs-7003564/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-28T08:17:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-24T12:31:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"187561679355199135861723123377069842648","date":"2025-07-24T11:27:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-23T11:56:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-22T18:58:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-21T13:03:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"108563831468879138489913801334638095059","date":"2025-07-16T02:31:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-15T19:55:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-15T07:23:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"75065129857046498147106762975452193598","date":"2025-07-14T13:36:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"106808407959064468147773512739125784374","date":"2025-07-14T12:42:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"89954836017191336471380209941073484310","date":"2025-07-14T11:39:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"214803365742251559702569709918851544691","date":"2025-07-14T03:49:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-14T02:27:01+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-03T14:32:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-02T12:23:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-02T12:21:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nephrology","date":"2025-06-29T15:10:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b741ff18-3e5f-42cc-89c0-2da7f9820583","owner":[],"postedDate":"July 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-01T16:07:04+00:00","versionOfRecord":{"articleIdentity":"rs-7003564","link":"https://doi.org/10.1186/s12882-025-04531-3","journal":{"identity":"bmc-nephrology","isVorOnly":false,"title":"BMC Nephrology"},"publishedOn":"2025-11-26 15:57:01","publishedOnDateReadable":"November 26th, 2025"},"versionCreatedAt":"2025-07-18 13:07:36","video":"","vorDoi":"10.1186/s12882-025-04531-3","vorDoiUrl":"https://doi.org/10.1186/s12882-025-04531-3","workflowStages":[]},"version":"v1","identity":"rs-7003564","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7003564","identity":"rs-7003564","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}