Effect of Glomerular Filtration Rate on Uric Acid Metabolism in a Retrospective Cohort of Type-2 Diabetes Mellitus Patients on Sglt-2 Inhibitor Therapy

Effect of Glomerular Filtration Rate on Uric Acid Metabolism in a Retrospective Cohort of Type-2 Diabetes Mellitus Patients on Sglt-2 Inhibitor Therapy | 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 Effect of Glomerular Filtration Rate on Uric Acid Metabolism in a Retrospective Cohort of Type-2 Diabetes Mellitus Patients on Sglt-2 Inhibitor Therapy Emre Vuraloglu, Altug Kut, Özlem Turhan İyidir This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4112142/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose The study aims to investigate the effect of different glomerular filtration rates (GFR) on serum uric acid (SUA) level changes in Type-2 DM patients receiving SGLT-2 inhibitor therapy. Methods We investigated 3004 patients on SGLT-2 inhibitor treatment between January-2017 and September-2022. Patients who were taking irregular medication, did not attend follow-up visits, were taking medications that affected SUA levels, and were receiving gout treatment were excluded, leaving 410 patients in the sample after exclusions. Patients underwent measurement of blood and urine biochemical markers before SGLT-2 inhibitor treatment and at months 3 and 12. We divided the study group into 3 subgroups (GFR≥90, 60-89, 30-59 ml/min/1.73m2) according to the Kidney Disease Foundation for Improving Global Outcomes and analyzed the effects of SGLT-2 inhibitors on SUA levels according to GFR. Results The study group had a male:female ratio of 1.24:1 with a mean age of 59.1±11.55 years. When comparing before and after treatment, HbA1C, fasting blood glucose, creatinine, low-density lipoprotein cholesterol, triglycerides and SUA levels decreased significantly, while high-density lipoprotein cholesterol and urine glucose levels increased significantly. In patients with GFR between 30-59 ml/min/1.73m 2 , no significant difference was found between the SUA values at pre-drug, 3rd, and 12th month drug therapy (p=0.368), and the effect on SUA levels differed according to GFR. This effect was not depending on the active substance and we considered it as a group effect of SGLT-2 inhibitors. The uric acid lowering effect of SGLT-2 inhibitors tends to increase as GFR increases. Conclusion We demonstrated that SGLT-2 inhibitors are not only anti-diabetic drugs, but may also have a protective role against diseases associated with hyperlipidemia and hyperuricemia in patients with preserved GFR, while no such effect should be expected in patients with low GFR. Diabetes Mellitus Glomerular Filtration Rate Sodium-Glucose Cotransporter 2 Inhibitors Uric Acid Chronic Kidney Diseases Figures Figure 1 INTRODUCTION The prognosis and course of Type-2 Diabetes Mellitus (Type-2 DM) is closely related to high uric acid levels as well as many other related factors. Especially chronic renal failure (CRF) and cardiovascular diseases are the leading complications associated with hyperuricemia [ 1 ]. Laboratory studies have shown that uric acid impairs endothelial function, reduces nitric oxide production, induces oxidative stress and stimulates vascular smooth muscle proliferation [ 2 ]. Therefore, prevention of hyperuricemia in the treatment of diabetes has become increasingly important in recent years to prevent nephrological complications for clinicians dealing with diabetes treatment [ 3 , 4 ]. Studies have shown that the use of Sodium-Glucose Cotransporter-2 (SGLT-2) inhibitors in Type-2 DM patients improves long-term major cardiovascular events and renal function, which is progressively deteriorating because of diabetes [ 2 , 5 – 7 ]. Studies start to recognize that these effects are partly independent of the glucose-lowering effects of SGLT-2 inhibitors [ 2 ]. Although evidence is lacking, one of the potential causes of renoprotective effects is the reduction of elevated uric acid levels in the bloodstream [ 8 , 9 ]. Due to mechanism of serum uric acid (SUA) lowering effect of SGLT-2 inhibitors, this impact may be attenuated in patients with lower glomerular filtration rate (GFR) [ 10 ]. Following the existing literature, previous meta-analyses of randomized controlled trials (RCTs) have suggested that the amount of reduction in SUA levels decreases with restricted GFR [ 8 , 11 ]. Thus, the effects of SGLT-2 inhibition appear to be blunted in patients with chronic kidney disease (CKD) [ 8 , 11 ]. However, some RCTs that examined the association of SUA level with glomerular filtration rate reported controversial results [ 12 – 14 ]. Although randomized clinical trials have predicted reductions in SUA levels relative to glomerular filtration rate and presented these in meta-analyses, conflicting reports and limited support from real-life data suggest that the issue requires further investigation. This study aimed to show how uric acid excretion changes in different glomerular filtration rates in a group of diabetic patients receiving continuous SGLT-2 inhibitor therapy for at least 12 months (52 weeks), monitored in real-time at a university hospital, and to contribute to the positioning of the active substance in patients with inadequate renal function. METHODS The investigators performed the study retrospectively on a cohort and Başkent University Medical and Health Sciences Research Board approved the study with project number KA 22/494. In 2017, clinical use of SGLT-2 inhibitors began in Turkey, with the introduction of first dapagliflozin and then empagliflozin. No other new member of the SGLT-2 family became available in Turkey during the time we conducted the study. We recruited the study group from patients diagnosed with type 2 DM who applied to the Endocrinology and Metabolic Diseases Outpatient Clinics of Başkent University, Turkey, between 1 January 2017 and 30 September 2022. Patients were required to be on SGLT-2 inhibitors (empagliflozin or dapagliflozin) continuously for at least 12 months and be over 18 years of age. We did not randomize the patient recruitment; we collected data from all patients who met the criteria during the study period. The total number of patients with type 2 diabetes evaluated in this way and registered in the database was 83,295. After the elimination of duplicate enrolments, the remaining number of patients with type 2 diabetes was 25,112. Of these diabetics, 3004 individuals who started treatment with an SGLT-2 inhibitor and used it for the prescribed period formed the study population. Exclusion criteria for this study population were discontinued use of SGLT-2 inhibitors, failure to attend the 3-month and/or 12-month follow-up visits, using drugs that reduce serum uric acid levels, using drugs that reduce uric acid production (allopurinol and febuxostat), using uricolytic drugs (pegloticase), uricosuric drugs (probenecid, sulphinpyrazone, fenofibrate, and losartan), drugs that increase the serum uric acid level (diuretics, cyclosporine, tacrolimus, levodopa, pyrazinamide, and ethambutol) and being treated for acute gout. On the other hand, the inclusion criteria were: To have applied to Başkent University Endocrinology and Metabolic Diseases Outpatient Clinic between 1 January 2017 and 30 September 2022, to have received a SGLT-2 inhibitor drug use report or prescription and to have used this drug for at least 12 months, to have come for the control examination visit in the 3rd and 12th month after starting the drug. It was also required that serum glycated hemoglobin (HbA1C), fasting plasma glucose (FBG), creatinine, glomerular filtration rate (GFR), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides, uric acid and urine glucose levels were measured and recorded completely at each visit. After applying the inclusion and exclusion criteria, the remaining 410 patients from the study population constituted the sample of the study. The parameters evaluated in the study were age, gender, type of SGLT-2 inhibitor active substance used (empagliflozin or dapagliflozin), serum HbA 1 C, FBG, creatinine, GFR, HDL-C, LDL-C, triglyceride, uric acid, and urine glucose levels. The independent variable of the study was SGLT-2 inhibitor treatment. The modulatory variable of the study is GFR. The dependent variable of the study is the SUA level. GFR, which is the regulatory variable of the study, was analyzed in three groups following the Kidney Disease Improving Global Outcomes (KDIGO) guideline [ 15 ]. These were categorized into three main groups GFR ≥ 90 ml/min/1.73m 2 (normal or high), GFR = 60–89 ml/min/1.73m 2 (mildly decreased), and GFR = 30–59 ml/min/1.73m 2 (moderately decreased). We used data scanned from the hospital's electronic medical information system as the data source for the laboratory values measured before receiving the SGLT-2 inhibitor and the laboratory values measured at month 3 and month 12 of SGLT-2 inhibitor treatment in patients who met the inclusion criteria. To prevent bias, the investigators did not interfere with the file information in any way during the data collection and patient evaluation process. We present means, standard deviations, medians, minimums and maximums in descriptive statistics for continuous data; numbers and percentages for discrete data. To examine the conformity of continuous data to normal distribution, we used Kolmogorov Smirnov test. Missing data and marginal values were not intervened. As the study was retrospective and based on routine follow-up data, there were no cases of exclusion or loss of data in the analysis process among the patients included in the study group. We started the study cohort retrospectively with 410 patients and completed it with the same number of patients. To compare serum HbA1C, FBG, creatinine, HDL-C, LDL-C, triglycerides, uric acid and urine glucose measurements of patients before SGLT-2 inhibitor treatment, 3 months on treatment and 12 months on treatment we used the Friedman test. We also applied the Friedman's multiple comparison test to analyze which measurements were different. We grouped the patients according to their GFR levels before SGLT-2 inhibitor treatment, and changes in SUA levels between the groups before SGLT-2 inhibitor treatment, after 3 months, and after 12 months of treatment were analyzed using the Mann-Whitney U test. IBM SPSS version 20 (Statistical Package for Social Sciences; v.20; Chicago, IL, USA) program was used in all evaluations and p < 0.05 was accepted as the limit of statistical significance at 95% confidence interval. RESULTS Of the 3004 patients who made up the study population, 2594 were excluded from the study according to various exclusion and inclusion criteria. During the exclusion process, 2119 patients were excluded because they did not attend the 3rd month and/or 12th month visits regularly, and 2119 patients were excluded because of missing data in any of the HbA 1 C, FBG, creatinine, GFR, HDL-C, LDL-C, triglyceride, uric acid, and urine glucose values. Thus, the sample size decreased to 885 patients. Among these patients, 206 (7.9%), 137 (5.3%), 70 (2.7%), 58 (2.6%), and 58 (2.6%) patients were excluded because they were receiving diuretic, allopurinol, losartan and fenofibrate treatment, respectively. In addition, 3 patients (0.1%) were excluded because they did not use continuous SGLT-2 inhibitor treatment, and 1 patient (0.03%) was excluded because he received an acute gout attack treatment. The number of patients accepted as the sample for the analyses was thus determined as 410. Among the subjects, 55.4% (n = 227) were male and 44.6% (n = 183) were female, with a male-to-female ratio of 1:0.8. The mean age was 59.1 ± 11.55 years (20–87 years) (Male: 59.30 ± 11.16; Female: 58.79 ± 12.03; p = 0.680). The entire group was receiving SGLT-2 during the period analyzed and 54.9% (n = 225) were taking dapagliflozin and 45.1% (n = 185) were taking empagliflozin. Regardless of whether the drugs were used alone or in combinations, the distribution of the active substances used by the patients in addition to SGLT-2 was as follows: 88.5% (n = 363) metformin, 43.2% (n = 177) dipeptidyl peptidase 4 inhibitors (DPP-4 inh.), 18.5% (n = 76) insulin, 18.1% (n = 74) sulphonilurea, 15.1% (n = 62) thiazolidinediones (TZD), 4.9% (n = 20) glucagon-like peptide-1 agonists (GLP-1 agonist) and 0.5% (n = 2) glinides. When the glomerular filtration rates of the study group patients were analyzed, 43.2% (n = 177) were 90 mL/min/1.73m 2 and above, 50.7% (n = 208) were 60–89 mL/min/1.73m 2 and 6.1% (n = 25) were 30–59 mL/min/1.73m 2 , respectively. Table-1 shows the comparison of serum and urine findings of the 410 patients who constituted the sample of the study between the period before receiving SGLT-2 inhibitor therapy, the 3rd month, and the 12th month of drug treatment. There was a statistically significant difference between the study group's serum HbA1C, FBG, creatinine, HDL-C, LDL-C, triglycerides, uric acid and urine glucose levels measured before SGLT-2 inhibitor therapy and those measured at month 3 and month 12 on SGLT-2 inhibitor therapy. HDL-C and urine glucose levels increased under SGLT-2 inhibitor treatment, while all other values decreased. We also analyzed the effect of SGLT-2 inhibitors on decreasing SUA levels at different GFRs (Table-2). Based on the information in Table 2, we can say that if the GFR is within normal limits or mildly reduced, and the duration of treatment with SGLT-2 inhibitors is prolonged, the reduction in uric acid levels progressively increases and this effect is significant. However, when GFR falls below 60 ml/min/1.73m2, serum uric acid levels decrease again to a certain extent, but the strength of this effect becomes statistically insignificant. The effect of the length of treatment duration on SUA reduction at normal and mildly decreased GFR levels was also analyzed (Table-3). We found that the uric acid-lowering effect was greater at higher GFR levels and that longer treatment with SGLT-2 inhibitors significantly increased this effect. Thus, we can say that a significant effect of SGLT-2 inhibitors on uric acid started as early as month 3 and gradually increased. In addition, we also examined whether the effects of different SGLT-2 inhibitors on lowering SUA were different from each other (Table-4). We found that different active substances showed similar effects at varying treatment durations and GFR and caused a significant decrease in SUA levels. DISCUSSION Our study indicates that SGLT-2 inhibitors not only reduce blood glucose levels but also significantly impact uric acid levels, while this reduction is diminished in patients with lower GFR rates. Patients with type-2 DM typically have greater uric acid concentrations than people without the disease. Although these levels are typically within the normal laboratory range, they are acting as independent factors associated with an increased risk of cardiovascular (CV) and renal disease. SGLT-2 inhibitor treatment is frequently observed in large randomized controlled trials in type-2 DM to reduce CV risk and improve renal functions [ 7 ]. One of the potential mechanisms through which SGLT-2 inhibitors influence the cardiovascular and renal risk might be via reduction of SUA levels in diabetic patients. Corroboratively, in two metaanalysis of 62 and 43 clinical trials, SGLT-2 inhibitors decreased SUA concentrations when baseline uric acid levels were within normal range and this effect was constant over two years [ 8 , 11 ]. In our study, SUA levels were mostly within normal range especially with normal GFR rates and decline in uric acid levels continued during the treatment and was still significant at 12th month of therapy. There is still uncertainty about the effects and the optimal dose of different SGLT-2 inhibitors on SUA levels in patients with CKD. In a recent meta-analysis, researchers showed that SGLT-2 inhibitors were able to significantly reduce SUA in participants in CKD stage 1–2, but had no significant effect on CKD stage 3–4 [ 16 ]. In contrast to this meta-analysis, the DERİVE Study conducted by Fioretto et al in 2018 in patients with stage 3a chronic kidney disease with a GFR between 45–59 ml/min/1.73m2 reported a statistically significant decrease in SUA levels at the end of week 24 in the dapagliflozin group compared with the placebo group [ 14 ]. In addition, a study by Pollock et al in 2019 compared baseline SUA levels in type 2 DM patients with a GFR between 25–75 ml/min/1.73m2 with SUA levels in patients treated with dapagliflozin and the placebo group at week 24 [ 13 ]. In this study, it was reported that SUA level increased in the group receiving SGLT-2 inhibitor treatment, but this was not statistically significant [ 13 ]. On the other hand, Yale et al. reached a result that supports our findings and showed that serum uric acid level did not change statistically at the end of the 52nd week in Type2DM patients with chronic kidney disease receiving Canagliflozin [ 12 ]. Based on these results, it can be said that the decrease in SUA level may show variable results in different studies in patients with glomerular filtration rate below 60 mL/min/1.73m2, but it is generally seen to remain at the same level. This suggests the possibility of a group effect rather than the type of SGLT-2 group active substance used in various studies. Novikov A, et al [ 10 ] found that for uric acid to be excreted more efficiently, two specific transporters, Urate Transporter-1 (URAT-1) and Glucose Transporter-9 (GLUT-9), play crucial roles. URAT-1, which helps in the transport of uric acid, is found in the part of the kidney called the proximal renal tubule. On the other hand, GLUT-9, which can transport both glucose and urate, is situated on the side of the cells in the proximal renal tubules that face the bloodstream. Their research also highlighted those inhibitors of SGLT-2, a protein involved in glucose reabsorption in the kidney, can decrease the activity of GLUT-9. This reduction in GLUT-9 activity could lead to a decrease in uric acid reabsorption by a specific version of GLUT-9 found in the kidney's collecting ducts, thereby raising the amount of uric acid released through urine. Therefore, the effectiveness of SGLT-2 inhibitors in increasing uric acid excretion is linked to the kidney function, which might clarify why their ability to lower uric acid levels diminishes as kidney function worsens. In our study, there was no difference between empagliflozin and dapagliflozin in terms of SUA lowering effect in lower GFR rates. In EMPEROR study, the authors found that the magnitude of uric acid lowering effect of empagliflozin was consistent in patients with impaired renal function [ 17 ]. Even though there is no study that directly compares empagliflozin and dapagliflozin, Zhang, et al found 10 mg dapagliflozin may be optimal in patients with chronic renal failure [ 16 ]. Regarding the glucose and lipid-lowering effects of SGLT-2 inhibitors, at the end of one year, SGLT-2 inhibitors were still beneficial for glucose control and lipid reduction in all patients included in this study. In particular, there is growing evidence of the benefits of SGLT-2 inhibitors in people with diabetes. Our study therefore provides important information in this regard, as it is a real-life study. In addition to its many strengths, this study also has some limitations. First of all, the fact that the study had a rigorously restricted sample and included all patients, not a randomized sample that met the inclusion and exclusion criteria listed in our database, is a strength. Unfortunately, these restrictions led us to a smaller and non-homogeneously distributed sample size, which forced us to use non-parametric tests. Another strength is that, contrary to the literature, we were able to test the hypothesis of the study on the basis of both SGLT-2 inhibitor active substances available in Turkey. However, the fact that the patients were collected from a center where high prevalence medicine is practiced and that they reflect tertiary health care services (university outpatient clinic) limits the clinical reflections of the active substances, albeit to a small extent. CONCLUSION It is clear that the effects of SGLT-2 inhibitors, which are one of the most popular therapies nowadays, both for their use in the treatment of diabetes and for their cardio-renoprotective effects, will require more randomized controlled trials or many more studies based on real-life data such as this study. However, the antihyperuricemic effect of SGLT-2 inhibitors, which is well documented in several meta-analyses and is thought to strengthen the role of SGLT-2 inhibitors in the treatment of diabetes, appears to be GFR dependent. In other words, we demonstrate that the expected effect is not seen in patients with very low GFR, such as those with end-stage renal disease. While the antidiabetic efficacy of SGLT-2 inhibitors continues even at low GFR values, the decreased efficacy on hyperuricemia and the limitation of their renoprotective properties in this sense is a result that needs to be supported by further studies. Our study also raises the question of whether SGLT-2 inhibitors may be an effective treatment for hyperuricemia and related diseases among non-diabetic patients, which may be another issue that should be investigated in the future. Declarations Author Contribution All authors contributed to the study conception and design. Contribution taxonomy was made according to CrediT. Conceptualization, Investigation, Formal Analysis, Methodology, Writing – Original Draft [Emre Vuraloglu], Conceptualization, Methodology, Writing-Review & Editing, Supervision, Project administration [Altug Kut] and Conceptualization, Formal Analysis, Writing-Review & Editing, Supervision [Özlem Turhan İyidir]. All authors read and approved the final manuscript. ACKNOWLEDGEMENT This study was approved by Başkent University Institutional Review Board (Project No: KA22/494) and supported by Başkent University Research Fund. References Johnson, R. J., Bakris, G. L., Borghi, C., Chonchol, M. B., Feldman, D., Lanaspa, M. A., Merriman, T. R., Moe, O. W., Mount, D. B., Sanchez Lozada, L. G., Stahl, E., Weiner, D. E., & Chertow, G. M. (2018). Hyperuricemia, Acute and Chronic Kidney Disease, Hypertension, and Cardiovascular Disease: Report of a Scientific Workshop Organized by the National Kidney Foundation. 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Comparison of pre-drug, 3rd month and 12th month Serum and Urine Findings of Selected Study Group Patients in the "Effect of Glomerular Filtration Rate on Uric Acid Metabolism in a Retrospective Cohort of Type 2 Diabetes Mellitus Patients on SGLT-2 Inhibitor Therapy" Study.(2023) SGLT-2 use (N=410) Pre-drug 3rd Month of Therapy 12th Month of Therapy P* Median (Min-Max) Median (Min-Max) Median (Min-Max) HbA 1 C 6.9 (4.5-14.6) 6.4 (4.5-12.6) 6.2 (4.0-12.6) <0.001 a FBG 140 (77-441) 121.5 (61-376) 112 (70-360) <0.001 a Creatinine 0.86 (0.54-1.88) 0.84 (0.51-1.79) 0.82 (0.40-2.03) 0.002 a Uric Acid 5.7 (2.7-9.2) 5 (2.3-8.3) 4.8 (2.1-8.2) <0.001 a HDL-C 44 (18-94) 46.2 (22-93) 48 (27-91) <0.001 a LDL-C 134 (52-357) 116 (42-216) 114 (34-222) <0.001 a Triglyceride 152 (37-1342) 135 (30-745) 125 (35-769) <0.001 a Urine Glucose 0 (0-2000) 1000 (0-2000) 1000 (0-2000) <0.001 a HbA 1 c; glycated haemoglobin, FBG; fasting blood glucose, HDL-C; High-density lipoprotein cholesterol, LDL-C; Low-density lipoprotein cholesterol. SD; Standart deviation. * p<0.05 was accepted as the limit of statistical significance at a 95% confidence interval. a The Friedman one-way repeated measures analysis of variance by ranks test results. Table-2. The Effect of Sodium-Glucose Transporter-2 Inhibitor Therapy on Serum Uric Acid Levels According to Different Glomerular Filtration Rates in Patients of the Study Group Selected in the "Effect of Glomerular Filtration Rate on Uric Acid Metabolism in a Retrospective Cohort of Type 2 Diabetes Mellitus Patients on SGLT-2 Inhibitor Therapy" Study (2023) GFR Levels ( mL/min/1.73m 2 ) Uric Acid Levels P* Pre-drug 3rd Month of Therapy 12th Month of Therapy Median (Min-Max) Median (Min-Max) Median (Min-Max) ≥90 5.5 (2.7-9.0) 4.7 (2.5-8.3) 4.3 (2.1-8.2) <0.001 a 60-89 5.8 (3.0-9.1) 5.2 (2.3-8.0) 5 (2.7-7.4) <0.001 a 30-59 6.4 (3.2-9.2) 6 (2.9-7.7) 5.9 (3.4-8.1) 0.368 a GFR; Glomerular Filtration Rate, SD; Standart deviation. * p<0.05 was accepted as the limit of statistical significance at a 95% confidence interval. a The Friedman one-way repeated measures analysis of variance by ranks test results. Table-3. Comparison of the Serum Uric Acid Lowering Effect of Sodium Glucose Transporter-2 Inhibitors at Normal and Mildly Decreased GFR Levels in the "Effect of Glomerular Filtration Rate on Uric Acid Metabolism in a Retrospective Cohort of Type 2 Diabetes Mellitus Patients on SGLT-2 Inhibitor Therapy" Study (2023) Treatment Status Uric Acid Levels P* GFR ≥90 GFR 60-89 Median (Min-Max) Median (Min-Max) Difference between Pre-Drug / Drug Therapy at 3rd Month -0.60 (-4.80)- (2.0) -0.45 (-3.70)- (2.40) 0.063 a Difference between Pre-Drug / Drug Therapy at 12th Month -1.0 (-4.60)- (1.40) -0.70 (-4.10)- (2.50) 0.007 a Difference between Drug Therapy at 3rd Month / 12th Month -0.3 (-3.60)- (2.40) -0.3 (-2.30)- (2.0) 0.069 a GFR; Glomerular Filtration Rate, SD; Standart deviation. * p<0.05 was accepted as the limit of statistical significance at a 95% confidence interval. a Mann-Whitney U test Table 4. The Effect of Different Active Substances on Serum Uric Acid Levels According to Different Glomerular Filtration Rates in Patients of the Study Group Selected in the "Effect of Glomerular Filtration Rate on Uric Acid Metabolism in a Retrospective Cohort of Type 2 Diabetes Mellitus Patients on SGLT-2 Inhibitor Therapy" Study (2023) GFR Levels ( mL/min/1.73m 2 ) AS Uric Acid Levels p Pre-drug 3rd Month of Therapy 12th Month of Therapy Median (Min-Max) Median (Min-Max) Median (Min-Max) ≥90 DAPA (n=103) 5.8 (3.0-9.0) 4.9 (2.7-8.3) 4.4 (2.5-8.2) <0.001 a EMPA (n=74) 5.2 (2.7-8.6) 4.5 (2.5-8.3) 4.0 (2.1-7.6) <0.001 a 60-89 DAPA (n=112) 5.81 (3.0-8.4) 5.1 (2.3-8.0) 5 (2.7-7.4) <0.001 a EMPA (n=96) 5.77 (3.2-9.1) 5.30 (2.9-8.0) 5.0 (3.0-7.4) <0.001 a 30-59 DAPA (n=10) 6.5 (4.8-7.5) 6.05 (5.2-7.0) 5.9 (4.2-7.1) 0.614 a EMPA (n=15) 5.9 (3.2-9.2) 5.9 (2.9-7.7) 5.9 (3.4-8.1) 0.584 a GFR; Glomerular Filtration Rate, AS; Active Substance, SD; Standart deviation, DAPA; Dapagliflozin, EMPA; Empagliflozin * p<0.05 was accepted as the limit of statistical significance at a 95% confidence interval. a The Friedman one-way repeated measures analysis of variance by ranks test results. 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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-4112142","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":280900350,"identity":"8f4888aa-5828-459f-9d7d-7f0d71d353dc","order_by":0,"name":"Emre Vuraloglu","email":"","orcid":"","institution":"Baskent University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Emre","middleName":"","lastName":"Vuraloglu","suffix":""},{"id":280900351,"identity":"6e3b95f1-fd29-43f4-929b-519dd2a99761","order_by":1,"name":"Altug Kut","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYDACdhBxgIGBH0QnFBCjhZkZrEVCsgGkxYAULQYHQDxitPA38x+T/HLmcJ3x+dWJHx4YMMjzix3Ar0XiMDObtMyNwxJmN95ulgA6zHDm7AQC1oC0SHwAaTm7AaQlweA2AS3yMC3GM85u/kGUFgOgFskPQIcZ8PduI84Ww8PMxtYMZ9IlZ9zg3WaRYCBB2C9yxxsf3vxxzJqfv//s5ps/Kmzk+aUJaAEBZh4QKQFWKUFYOQgw/gCR/AeIUz0KRsEoGAUjDwAA+HpDiOGZpdIAAAAASUVORK5CYII=","orcid":"","institution":"Baskent University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Altug","middleName":"","lastName":"Kut","suffix":""},{"id":280900352,"identity":"45c7dc26-b3f3-424b-a9d0-de30120757b6","order_by":2,"name":"Özlem Turhan İyidir","email":"","orcid":"","institution":"Baskent University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Özlem","middleName":"Turhan","lastName":"İyidir","suffix":""}],"badges":[],"createdAt":"2024-03-16 08:44:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4112142/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4112142/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53184541,"identity":"b5c1e0b3-cd8d-4cf9-a907-233f2efc76b2","added_by":"auto","created_at":"2024-03-21 16:05:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":59094,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the “Effect of Glomerular Filtration Rate on Uric Acid Metabolism in a Retrospective Cohort of Type-2 Diabetes Mellitus Patients on SGLT-2 İnhibitor Therapy” study.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4112142/v1/2bab47caf97d4d4a8ee1b347.png"},{"id":53185993,"identity":"4981e59d-4597-44bd-8789-73cb8222da7f","added_by":"auto","created_at":"2024-03-21 16:13:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":296893,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4112142/v1/3a4db8b1-e410-4dd1-9e17-9e5ef6c3067c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eEffect of Glomerular Filtration Rate on Uric Acid Metabolism in a Retrospective Cohort of Type-2 Diabetes Mellitus Patients on Sglt-2 Inhibitor Therapy\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe prognosis and course of Type-2 Diabetes Mellitus (Type-2 DM) is closely related to high uric acid levels as well as many other related factors. Especially chronic renal failure (CRF) and cardiovascular diseases are the leading complications associated with hyperuricemia [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Laboratory studies have shown that uric acid impairs endothelial function, reduces nitric oxide production, induces oxidative stress and stimulates vascular smooth muscle proliferation [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Therefore, prevention of hyperuricemia in the treatment of diabetes has become increasingly important in recent years to prevent nephrological complications for clinicians dealing with diabetes treatment [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eStudies have shown that the use of Sodium-Glucose Cotransporter-2 (SGLT-2) inhibitors in Type-2 DM patients improves long-term major cardiovascular events and renal function, which is progressively deteriorating because of diabetes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Studies start to recognize that these effects are partly independent of the glucose-lowering effects of SGLT-2 inhibitors [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Although evidence is lacking, one of the potential causes of renoprotective effects is the reduction of elevated uric acid levels in the bloodstream [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Due to mechanism of serum uric acid (SUA) lowering effect of SGLT-2 inhibitors, this impact may be attenuated in patients with lower glomerular filtration rate (GFR) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFollowing the existing literature, previous meta-analyses of randomized controlled trials (RCTs) have suggested that the amount of reduction in SUA levels decreases with restricted GFR [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Thus, the effects of SGLT-2 inhibition appear to be blunted in patients with chronic kidney disease (CKD) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, some RCTs that examined the association of SUA level with glomerular filtration rate reported controversial results [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Although randomized clinical trials have predicted reductions in SUA levels relative to glomerular filtration rate and presented these in meta-analyses, conflicting reports and limited support from real-life data suggest that the issue requires further investigation.\u003c/p\u003e \u003cp\u003eThis study aimed to show how uric acid excretion changes in different glomerular filtration rates in a group of diabetic patients receiving continuous SGLT-2 inhibitor therapy for at least 12 months (52 weeks), monitored in real-time at a university hospital, and to contribute to the positioning of the active substance in patients with inadequate renal function.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eThe investigators performed the study retrospectively on a cohort and Başkent University Medical and Health Sciences Research Board approved the study with project number KA 22/494. In 2017, clinical use of SGLT-2 inhibitors began in Turkey, with the introduction of first dapagliflozin and then empagliflozin. No other new member of the SGLT-2 family became available in Turkey during the time we conducted the study. We recruited the study group from patients diagnosed with type 2 DM who applied to the Endocrinology and Metabolic Diseases Outpatient Clinics of Başkent University, Turkey, between 1 January 2017 and 30 September 2022. Patients were required to be on SGLT-2 inhibitors (empagliflozin or dapagliflozin) continuously for at least 12 months and be over 18 years of age. We did not randomize the patient recruitment; we collected data from all patients who met the criteria during the study period. The total number of patients with type 2 diabetes evaluated in this way and registered in the database was 83,295. After the elimination of duplicate enrolments, the remaining number of patients with type 2 diabetes was 25,112. Of these diabetics, 3004 individuals who started treatment with an SGLT-2 inhibitor and used it for the prescribed period formed the study population.\u003c/p\u003e \u003cp\u003eExclusion criteria for this study population were discontinued use of SGLT-2 inhibitors, failure to attend the 3-month and/or 12-month follow-up visits, using drugs that reduce serum uric acid levels, using drugs that reduce uric acid production (allopurinol and febuxostat), using uricolytic drugs (pegloticase), uricosuric drugs (probenecid, sulphinpyrazone, fenofibrate, and losartan), drugs that increase the serum uric acid level (diuretics, cyclosporine, tacrolimus, levodopa, pyrazinamide, and ethambutol) and being treated for acute gout.\u003c/p\u003e \u003cp\u003eOn the other hand, the inclusion criteria were: To have applied to Başkent University Endocrinology and Metabolic Diseases Outpatient Clinic between 1 January 2017 and 30 September 2022, to have received a SGLT-2 inhibitor drug use report or prescription and to have used this drug for at least 12 months, to have come for the control examination visit in the 3rd and 12th month after starting the drug. It was also required that serum glycated hemoglobin (HbA1C), fasting plasma glucose (FBG), creatinine, glomerular filtration rate (GFR), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides, uric acid and urine glucose levels were measured and recorded completely at each visit. After applying the inclusion and exclusion criteria, the remaining 410 patients from the study population constituted the sample of the study.\u003c/p\u003e \u003cp\u003eThe parameters evaluated in the study were age, gender, type of SGLT-2 inhibitor active substance used (empagliflozin or dapagliflozin), serum HbA\u003csub\u003e1\u003c/sub\u003eC, FBG, creatinine, GFR, HDL-C, LDL-C, triglyceride, uric acid, and urine glucose levels. The independent variable of the study was SGLT-2 inhibitor treatment. The modulatory variable of the study is GFR. The dependent variable of the study is the SUA level. GFR, which is the regulatory variable of the study, was analyzed in three groups following the Kidney Disease Improving Global Outcomes (KDIGO) guideline [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. These were categorized into three main groups GFR\u0026thinsp;\u0026ge;\u0026thinsp;90 ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e (normal or high), GFR\u0026thinsp;=\u0026thinsp;60\u0026ndash;89 ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e (mildly decreased), and GFR\u0026thinsp;=\u0026thinsp;30\u0026ndash;59 ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e (moderately decreased).\u003c/p\u003e \u003cp\u003eWe used data scanned from the hospital's electronic medical information system as the data source for the laboratory values measured before receiving the SGLT-2 inhibitor and the laboratory values measured at month 3 and month 12 of SGLT-2 inhibitor treatment in patients who met the inclusion criteria. To prevent bias, the investigators did not interfere with the file information in any way during the data collection and patient evaluation process.\u003c/p\u003e \u003cp\u003eWe present means, standard deviations, medians, minimums and maximums in descriptive statistics for continuous data; numbers and percentages for discrete data. To examine the conformity of continuous data to normal distribution, we used Kolmogorov Smirnov test. Missing data and marginal values were not intervened. As the study was retrospective and based on routine follow-up data, there were no cases of exclusion or loss of data in the analysis process among the patients included in the study group. We started the study cohort retrospectively with 410 patients and completed it with the same number of patients.\u003c/p\u003e \u003cp\u003eTo compare serum HbA1C, FBG, creatinine, HDL-C, LDL-C, triglycerides, uric acid and urine glucose measurements of patients before SGLT-2 inhibitor treatment, 3 months on treatment and 12 months on treatment we used the Friedman test. We also applied the Friedman's multiple comparison test to analyze which measurements were different. We grouped the patients according to their GFR levels before SGLT-2 inhibitor treatment, and changes in SUA levels between the groups before SGLT-2 inhibitor treatment, after 3 months, and after 12 months of treatment were analyzed using the Mann-Whitney U test. IBM SPSS version 20 (Statistical Package for Social Sciences; v.20; Chicago, IL, USA) program was used in all evaluations and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was accepted as the limit of statistical significance at 95% confidence interval.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eOf the 3004 patients who made up the study population, 2594 were excluded from the study according to various exclusion and inclusion criteria. During the exclusion process, 2119 patients were excluded because they did not attend the 3rd month and/or 12th month visits regularly, and 2119 patients were excluded because of missing data in any of the HbA\u003csub\u003e1\u003c/sub\u003eC, FBG, creatinine, GFR, HDL-C, LDL-C, triglyceride, uric acid, and urine glucose values. Thus, the sample size decreased to 885 patients. Among these patients, 206 (7.9%), 137 (5.3%), 70 (2.7%), 58 (2.6%), and 58 (2.6%) patients were excluded because they were receiving diuretic, allopurinol, losartan and fenofibrate treatment, respectively. In addition, 3 patients (0.1%) were excluded because they did not use continuous SGLT-2 inhibitor treatment, and 1 patient (0.03%) was excluded because he received an acute gout attack treatment. The number of patients accepted as the sample for the analyses was thus determined as 410.\u003c/p\u003e \u003cp\u003eAmong the subjects, 55.4% (n\u0026thinsp;=\u0026thinsp;227) were male and 44.6% (n\u0026thinsp;=\u0026thinsp;183) were female, with a male-to-female ratio of 1:0.8. The mean age was 59.1\u0026thinsp;\u0026plusmn;\u0026thinsp;11.55 years (20\u0026ndash;87 years) (Male: 59.30\u0026thinsp;\u0026plusmn;\u0026thinsp;11.16; Female: 58.79\u0026thinsp;\u0026plusmn;\u0026thinsp;12.03; p\u0026thinsp;=\u0026thinsp;0.680). The entire group was receiving SGLT-2 during the period analyzed and 54.9% (n\u0026thinsp;=\u0026thinsp;225) were taking dapagliflozin and 45.1% (n\u0026thinsp;=\u0026thinsp;185) were taking empagliflozin. Regardless of whether the drugs were used alone or in combinations, the distribution of the active substances used by the patients in addition to SGLT-2 was as follows: 88.5% (n\u0026thinsp;=\u0026thinsp;363) metformin, 43.2% (n\u0026thinsp;=\u0026thinsp;177) dipeptidyl peptidase 4 inhibitors (DPP-4 inh.), 18.5% (n\u0026thinsp;=\u0026thinsp;76) insulin, 18.1% (n\u0026thinsp;=\u0026thinsp;74) sulphonilurea, 15.1% (n\u0026thinsp;=\u0026thinsp;62) thiazolidinediones (TZD), 4.9% (n\u0026thinsp;=\u0026thinsp;20) glucagon-like peptide-1 agonists (GLP-1 agonist) and 0.5% (n\u0026thinsp;=\u0026thinsp;2) glinides.\u003c/p\u003e \u003cp\u003eWhen the glomerular filtration rates of the study group patients were analyzed, 43.2% (n\u0026thinsp;=\u0026thinsp;177) were 90 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e and above, 50.7% (n\u0026thinsp;=\u0026thinsp;208) were 60\u0026ndash;89 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e and 6.1% (n\u0026thinsp;=\u0026thinsp;25) were 30\u0026ndash;59 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e, respectively.\u003c/p\u003e \u003cp\u003eTable-1 shows the comparison of serum and urine findings of the 410 patients who constituted the sample of the study between the period before receiving SGLT-2 inhibitor therapy, the 3rd month, and the 12th month of drug treatment. There was a statistically significant difference between the study group's serum HbA1C, FBG, creatinine, HDL-C, LDL-C, triglycerides, uric acid and urine glucose levels measured before SGLT-2 inhibitor therapy and those measured at month 3 and month 12 on SGLT-2 inhibitor therapy. HDL-C and urine glucose levels increased under SGLT-2 inhibitor treatment, while all other values decreased.\u003c/p\u003e \u003cp\u003eWe also analyzed the effect of SGLT-2 inhibitors on decreasing SUA levels at different GFRs (Table-2). Based on the information in Table\u0026nbsp;2, we can say that if the GFR is within normal limits or mildly reduced, and the duration of treatment with SGLT-2 inhibitors is prolonged, the reduction in uric acid levels progressively increases and this effect is significant. However, when GFR falls below 60 ml/min/1.73m2, serum uric acid levels decrease again to a certain extent, but the strength of this effect becomes statistically insignificant.\u003c/p\u003e \u003cp\u003eThe effect of the length of treatment duration on SUA reduction at normal and mildly decreased GFR levels was also analyzed (Table-3). We found that the uric acid-lowering effect was greater at higher GFR levels and that longer treatment with SGLT-2 inhibitors significantly increased this effect. Thus, we can say that a significant effect of SGLT-2 inhibitors on uric acid started as early as month 3 and gradually increased.\u003c/p\u003e \u003cp\u003eIn addition, we also examined whether the effects of different SGLT-2 inhibitors on lowering SUA were different from each other (Table-4). We found that different active substances showed similar effects at varying treatment durations and GFR and caused a significant decrease in SUA levels.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur study indicates that SGLT-2 inhibitors not only reduce blood glucose levels but also significantly impact uric acid levels, while this reduction is diminished in patients with lower GFR rates.\u003c/p\u003e \u003cp\u003ePatients with type-2 DM typically have greater uric acid concentrations than people without the disease. Although these levels are typically within the normal laboratory range, they are acting as independent factors associated with an increased risk of cardiovascular (CV) and renal disease. SGLT-2 inhibitor treatment is frequently observed in large randomized controlled trials in type-2 DM to reduce CV risk and improve renal functions [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. One of the potential mechanisms through which SGLT-2 inhibitors influence the cardiovascular and renal risk might be via reduction of SUA levels in diabetic patients. Corroboratively, in two metaanalysis of 62 and 43 clinical trials, SGLT-2 inhibitors decreased SUA concentrations when baseline uric acid levels were within normal range and this effect was constant over two years [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In our study, SUA levels were mostly within normal range especially with normal GFR rates and decline in uric acid levels continued during the treatment and was still significant at 12th month of therapy. There is still uncertainty about the effects and the optimal dose of different SGLT-2 inhibitors on SUA levels in patients with CKD. In a recent meta-analysis, researchers showed that SGLT-2 inhibitors were able to significantly reduce SUA in participants in CKD stage 1\u0026ndash;2, but had no significant effect on CKD stage 3\u0026ndash;4 [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn contrast to this meta-analysis, the DERİVE Study conducted by Fioretto et al in 2018 in patients with stage 3a chronic kidney disease with a GFR between 45\u0026ndash;59 ml/min/1.73m2 reported a statistically significant decrease in SUA levels at the end of week 24 in the dapagliflozin group compared with the placebo group [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In addition, a study by Pollock et al in 2019 compared baseline SUA levels in type 2 DM patients with a GFR between 25\u0026ndash;75 ml/min/1.73m2 with SUA levels in patients treated with dapagliflozin and the placebo group at week 24 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In this study, it was reported that SUA level increased in the group receiving SGLT-2 inhibitor treatment, but this was not statistically significant [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. On the other hand, Yale et al. reached a result that supports our findings and showed that serum uric acid level did not change statistically at the end of the 52nd week in Type2DM patients with chronic kidney disease receiving Canagliflozin [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Based on these results, it can be said that the decrease in SUA level may show variable results in different studies in patients with glomerular filtration rate below 60 mL/min/1.73m2, but it is generally seen to remain at the same level. This suggests the possibility of a group effect rather than the type of SGLT-2 group active substance used in various studies.\u003c/p\u003e \u003cp\u003eNovikov A, et al [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] found that for uric acid to be excreted more efficiently, two specific transporters, Urate Transporter-1 (URAT-1) and Glucose Transporter-9 (GLUT-9), play crucial roles. URAT-1, which helps in the transport of uric acid, is found in the part of the kidney called the proximal renal tubule. On the other hand, GLUT-9, which can transport both glucose and urate, is situated on the side of the cells in the proximal renal tubules that face the bloodstream. Their research also highlighted those inhibitors of SGLT-2, a protein involved in glucose reabsorption in the kidney, can decrease the activity of GLUT-9. This reduction in GLUT-9 activity could lead to a decrease in uric acid reabsorption by a specific version of GLUT-9 found in the kidney's collecting ducts, thereby raising the amount of uric acid released through urine. Therefore, the effectiveness of SGLT-2 inhibitors in increasing uric acid excretion is linked to the kidney function, which might clarify why their ability to lower uric acid levels diminishes as kidney function worsens.\u003c/p\u003e \u003cp\u003eIn our study, there was no difference between empagliflozin and dapagliflozin in terms of SUA lowering effect in lower GFR rates. In EMPEROR study, the authors found that the magnitude of uric acid lowering effect of empagliflozin was consistent in patients with impaired renal function [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Even though there is no study that directly compares empagliflozin and dapagliflozin, Zhang, et al found 10 mg dapagliflozin may be optimal in patients with chronic renal failure [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRegarding the glucose and lipid-lowering effects of SGLT-2 inhibitors, at the end of one year, SGLT-2 inhibitors were still beneficial for glucose control and lipid reduction in all patients included in this study. In particular, there is growing evidence of the benefits of SGLT-2 inhibitors in people with diabetes. Our study therefore provides important information in this regard, as it is a real-life study.\u003c/p\u003e \u003cp\u003eIn addition to its many strengths, this study also has some limitations. First of all, the fact that the study had a rigorously restricted sample and included all patients, not a randomized sample that met the inclusion and exclusion criteria listed in our database, is a strength. Unfortunately, these restrictions led us to a smaller and non-homogeneously distributed sample size, which forced us to use non-parametric tests. Another strength is that, contrary to the literature, we were able to test the hypothesis of the study on the basis of both SGLT-2 inhibitor active substances available in Turkey. However, the fact that the patients were collected from a center where high prevalence medicine is practiced and that they reflect tertiary health care services (university outpatient clinic) limits the clinical reflections of the active substances, albeit to a small extent.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIt is clear that the effects of SGLT-2 inhibitors, which are one of the most popular therapies nowadays, both for their use in the treatment of diabetes and for their cardio-renoprotective effects, will require more randomized controlled trials or many more studies based on real-life data such as this study. However, the antihyperuricemic effect of SGLT-2 inhibitors, which is well documented in several meta-analyses and is thought to strengthen the role of SGLT-2 inhibitors in the treatment of diabetes, appears to be GFR dependent. In other words, we demonstrate that the expected effect is not seen in patients with very low GFR, such as those with end-stage renal disease.\u003c/p\u003e \u003cp\u003eWhile the antidiabetic efficacy of SGLT-2 inhibitors continues even at low GFR values, the decreased efficacy on hyperuricemia and the limitation of their renoprotective properties in this sense is a result that needs to be supported by further studies. Our study also raises the question of whether SGLT-2 inhibitors may be an effective treatment for hyperuricemia and related diseases among non-diabetic patients, which may be another issue that should be investigated in the future.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study conception and design. Contribution taxonomy was made according to CrediT. Conceptualization, Investigation, Formal Analysis, Methodology, Writing \u0026ndash; Original Draft [Emre Vuraloglu], Conceptualization, Methodology, Writing-Review \u0026amp; Editing, Supervision, Project administration [Altug Kut] and Conceptualization, Formal Analysis, Writing-Review \u0026amp; Editing, Supervision [\u0026Ouml;zlem Turhan İyidir]. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eACKNOWLEDGEMENT\u003c/h2\u003e \u003cp\u003e This study was approved by Başkent University Institutional Review Board (Project No: KA22/494) and supported by Başkent University Research Fund.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJohnson, R. J., Bakris, G. L., Borghi, C., Chonchol, M. B., Feldman, D., Lanaspa, M. A., Merriman, T. R., Moe, O. W., Mount, D. B., Sanchez Lozada, L. G., Stahl, E., Weiner, D. E., \u0026amp; Chertow, G. M. (2018). 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European heart journal, 43(36), 3435\u0026ndash;3446. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/eurheartj/ehac320\u003c/span\u003e\u003cspan address=\"10.1093/eurheartj/ehac320\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eComparison of pre-drug, 3rd month and 12th month Serum and Urine Findings of Selected Study Group Patients in the \u0026quot;Effect of Glomerular Filtration Rate on Uric Acid Metabolism in a Retrospective Cohort of Type 2 Diabetes Mellitus Patients on SGLT-2 Inhibitor Therapy\u0026quot; Study.(2023)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"596\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.939597315436242%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSGLT-2 use\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(N=410)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.14765100671141%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePre-drug\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.335570469798657%\"\u003e\n \u003cp\u003e\u003cstrong\u003e3rd Month of Therapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.174496644295303%\"\u003e\n \u003cp\u003e\u003cstrong\u003e12th Month of Therapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.40268456375839%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eP*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.068337129840547%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian (Min-Max)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.39635535307517%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian (Min-Max)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.535307517084284%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian (Min-Max)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.939597315436242%\" valign=\"top\"\u003e\n \u003cp\u003eHbA\u003csub\u003e1\u003c/sub\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.14765100671141%\" valign=\"top\"\u003e\n \u003cp\u003e6.9 (4.5-14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.335570469798657%\" valign=\"top\"\u003e\n \u003cp\u003e6.4 (4.5-12.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.174496644295303%\" valign=\"top\"\u003e\n \u003cp\u003e6.2 (4.0-12.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.40268456375839%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.939597315436242%\" valign=\"top\"\u003e\n \u003cp\u003eFBG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.14765100671141%\" valign=\"top\"\u003e\n \u003cp\u003e140 (77-441)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.335570469798657%\" valign=\"top\"\u003e\n \u003cp\u003e121.5 (61-376)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.174496644295303%\" valign=\"top\"\u003e\n \u003cp\u003e112 (70-360)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.40268456375839%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.939597315436242%\" valign=\"top\"\u003e\n \u003cp\u003eCreatinine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.14765100671141%\" valign=\"top\"\u003e\n \u003cp\u003e0.86 (0.54-1.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.335570469798657%\" valign=\"top\"\u003e\n \u003cp\u003e0.84 (0.51-1.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.174496644295303%\" valign=\"top\"\u003e\n \u003cp\u003e0.82 (0.40-2.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.40268456375839%\" valign=\"top\"\u003e\n \u003cp\u003e0.002 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.939597315436242%\" valign=\"top\"\u003e\n \u003cp\u003eUric Acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.14765100671141%\" valign=\"top\"\u003e\n \u003cp\u003e5.7 (2.7-9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.335570469798657%\" valign=\"top\"\u003e\n \u003cp\u003e5 (2.3-8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.174496644295303%\" valign=\"top\"\u003e\n \u003cp\u003e4.8 (2.1-8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.40268456375839%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.939597315436242%\" valign=\"top\"\u003e\n \u003cp\u003eHDL-C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.14765100671141%\" valign=\"top\"\u003e\n \u003cp\u003e44 (18-94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.335570469798657%\" valign=\"top\"\u003e\n \u003cp\u003e46.2 (22-93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.174496644295303%\" valign=\"top\"\u003e\n \u003cp\u003e48 (27-91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.40268456375839%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.939597315436242%\" valign=\"top\"\u003e\n \u003cp\u003eLDL-C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.14765100671141%\" valign=\"top\"\u003e\n \u003cp\u003e134 (52-357)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.335570469798657%\" valign=\"top\"\u003e\n \u003cp\u003e116 (42-216)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.174496644295303%\" valign=\"top\"\u003e\n \u003cp\u003e114 (34-222)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.40268456375839%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.939597315436242%\" valign=\"top\"\u003e\n \u003cp\u003eTriglyceride\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.14765100671141%\" valign=\"top\"\u003e\n \u003cp\u003e152 (37-1342)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.335570469798657%\" valign=\"top\"\u003e\n \u003cp\u003e135 (30-745)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.174496644295303%\" valign=\"top\"\u003e\n \u003cp\u003e125 (35-769)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.40268456375839%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.939597315436242%\" valign=\"top\"\u003e\n \u003cp\u003eUrine Glucose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.14765100671141%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0-2000)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.335570469798657%\" valign=\"top\"\u003e\n \u003cp\u003e1000 (0-2000)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.174496644295303%\" valign=\"top\"\u003e\n \u003cp\u003e1000 (0-2000)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.40268456375839%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eHbA\u003csub\u003e1\u003c/sub\u003ec; glycated haemoglobin, FBG; fasting blood glucose, HDL-C; High-density lipoprotein cholesterol, LDL-C; Low-density lipoprotein cholesterol. SD; Standart deviation.\u003c/p\u003e\n \u003cp\u003e*\u0026nbsp;p\u0026lt;0.05 was accepted as the limit of statistical significance at a 95% confidence interval.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e The Friedman\u0026nbsp;one-way repeated measures analysis of variance by ranks test results.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable-2.\u003c/strong\u003e The Effect of Sodium-Glucose Transporter-2 Inhibitor Therapy on Serum Uric Acid Levels According to Different Glomerular Filtration Rates in Patients of the Study Group Selected in the \u0026quot;Effect of Glomerular Filtration Rate on Uric Acid Metabolism in a Retrospective Cohort of Type 2 Diabetes Mellitus Patients on SGLT-2 Inhibitor Therapy\u0026quot; Study (2023)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"603\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.754560530679933%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eGFR Levels\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003c/strong\u003emL/min/1.73m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"73.6318407960199%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eUric Acid Levels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.613598673300165%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eP*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.17977528089887%\"\u003e\n \u003cp\u003ePre-drug\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.910112359550563%\"\u003e\n \u003cp\u003e3rd Month of Therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.910112359550563%\"\u003e\n \u003cp\u003e12th Month of Therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.17977528089887%\"\u003e\n \u003cp\u003eMedian (Min-Max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.910112359550563%\"\u003e\n \u003cp\u003eMedian (Min-Max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.910112359550563%\"\u003e\n \u003cp\u003eMedian (Min-Max)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.728476821192054%\"\u003e\n \u003cp\u003e\u0026ge;90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.655629139072847%\"\u003e\n \u003cp\u003e5.5 (2.7-9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.509933774834437%\"\u003e\n \u003cp\u003e4.7 (2.5-8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.509933774834437%\"\u003e\n \u003cp\u003e4.3 (2.1-8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.596026490066226%\"\u003e\n \u003cp\u003e\u0026lt;0.001 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.728476821192054%\"\u003e\n \u003cp\u003e60-89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.655629139072847%\"\u003e\n \u003cp\u003e5.8 (3.0-9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.509933774834437%\"\u003e\n \u003cp\u003e5.2 (2.3-8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.509933774834437%\"\u003e\n \u003cp\u003e5 (2.7-7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.596026490066226%\"\u003e\n \u003cp\u003e\u0026lt;0.001 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.728476821192054%\"\u003e\n \u003cp\u003e30-59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.655629139072847%\"\u003e\n \u003cp\u003e6.4 (3.2-9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.509933774834437%\"\u003e\n \u003cp\u003e6 (2.9-7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.509933774834437%\"\u003e\n \u003cp\u003e5.9 (3.4-8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.596026490066226%\"\u003e\n \u003cp\u003e0.368 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eGFR; Glomerular Filtration Rate,\u0026nbsp;SD; Standart deviation.\u003c/p\u003e\n \u003cp\u003e*\u0026nbsp;p\u0026lt;0.05 was accepted as the limit of statistical significance at a 95% confidence interval.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e The Friedman\u0026nbsp;one-way repeated measures analysis of variance by ranks test results.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable-3.\u003c/strong\u003e Comparison of the Serum Uric Acid Lowering Effect of Sodium Glucose Transporter-2 Inhibitors at Normal and Mildly Decreased GFR Levels in the \u0026quot;Effect of Glomerular Filtration Rate on Uric Acid Metabolism in a Retrospective Cohort of Type 2 Diabetes Mellitus Patients on SGLT-2 Inhibitor Therapy\u0026quot; Study (2023)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"582\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.192439862542955%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52.92096219931271%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUric Acid Levels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88659793814433%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eP*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.64935064935065%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGFR \u0026ge;90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.35064935064935%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGFR 60-89\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.64935064935065%\" valign=\"top\"\u003e\n \u003cp\u003eMedian (Min-Max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.35064935064935%\" valign=\"top\"\u003e\n \u003cp\u003eMedian (Min-Max)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.192439862542955%\"\u003e\n \u003cp\u003eDifference between Pre-Drug / Drug Therapy at 3rd Month\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e-0.60 (-4.80)- (2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.116838487972508%\"\u003e\n \u003cp\u003e-0.45 (-3.70)- (2.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88659793814433%\"\u003e\n \u003cp\u003e0.063 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.192439862542955%\"\u003e\n \u003cp\u003eDifference between Pre-Drug / Drug Therapy at 12th Month\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e-1.0 (-4.60)- (1.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.116838487972508%\"\u003e\n \u003cp\u003e-0.70 (-4.10)- (2.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88659793814433%\"\u003e\n \u003cp\u003e0.007\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.192439862542955%\"\u003e\n \u003cp\u003eDifference between Drug Therapy at 3rd Month / 12th Month\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e-0.3 (-3.60)- (2.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.116838487972508%\"\u003e\n \u003cp\u003e-0.3 (-2.30)- (2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88659793814433%\"\u003e\n \u003cp\u003e0.069 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\"\u003e\n \u003cp\u003eGFR; Glomerular Filtration Rate,\u0026nbsp;SD; Standart deviation.\u003c/p\u003e\n \u003cp\u003e*\u0026nbsp;p\u0026lt;0.05 was accepted as the limit of statistical significance at a 95% confidence interval.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Mann-Whitney U test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eThe Effect of Different Active Substances on Serum Uric Acid Levels According to Different Glomerular Filtration Rates in Patients of the Study Group Selected in the \u0026quot;Effect of Glomerular Filtration Rate on Uric Acid Metabolism in a Retrospective Cohort of Type 2 Diabetes Mellitus Patients on SGLT-2 Inhibitor Therapy\u0026quot; Study (2023)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.702479338842975%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eGFR Levels\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003c/strong\u003emL/min/1.73m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.909090909090908%\" rowspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"62.47933884297521%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUric Acid Levels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.909090909090908%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.176781002638524%\" valign=\"top\"\u003e\n \u003cp\u003ePre-drug\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.35620052770449%\" valign=\"top\"\u003e\n \u003cp\u003e3rd Month of Therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.46701846965699%\" valign=\"top\"\u003e\n \u003cp\u003e12th Month of Therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.176781002638524%\" valign=\"top\"\u003e\n \u003cp\u003eMedian (Min-Max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.35620052770449%\" valign=\"top\"\u003e\n \u003cp\u003eMedian (Min-Max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.46701846965699%\" valign=\"top\"\u003e\n \u003cp\u003eMedian (Min-Max)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.676567656765677%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026ge;90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.891089108910892%\" valign=\"top\"\u003e\n \u003cp\u003eDAPA (n=103)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.996699669966997%\"\u003e\n \u003cp\u003e5.8 (3.0-9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.112211221122113%\"\u003e\n \u003cp\u003e4.9 (2.7-8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.432343234323433%\"\u003e\n \u003cp\u003e4.4 (2.5-8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.891089108910892%\"\u003e\n \u003cp\u003e\u0026lt;0.001 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.915851272015656%\" valign=\"top\"\u003e\n \u003cp\u003eEMPA (n=74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.15655577299413%\"\u003e\n \u003cp\u003e5.2 (2.7-8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.223091976516635%\"\u003e\n \u003cp\u003e4.5 (2.5-8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e4.0 (2.1-7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.915851272015656%\"\u003e\n \u003cp\u003e\u0026lt;0.001 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.676567656765677%\" rowspan=\"2\"\u003e\n \u003cp\u003e60-89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.891089108910892%\" valign=\"top\"\u003e\n \u003cp\u003eDAPA (n=112)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.996699669966997%\"\u003e\n \u003cp\u003e5.81 (3.0-8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.112211221122113%\"\u003e\n \u003cp\u003e5.1 (2.3-8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.432343234323433%\"\u003e\n \u003cp\u003e5 (2.7-7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.891089108910892%\"\u003e\n \u003cp\u003e\u0026lt;0.001 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.915851272015656%\" valign=\"top\"\u003e\n \u003cp\u003eEMPA (n=96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.15655577299413%\"\u003e\n \u003cp\u003e5.77 (3.2-9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.223091976516635%\"\u003e\n \u003cp\u003e5.30 (2.9-8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e5.0 (3.0-7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.915851272015656%\"\u003e\n \u003cp\u003e\u0026lt;0.001 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.676567656765677%\" rowspan=\"2\"\u003e\n \u003cp\u003e30-59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.891089108910892%\" valign=\"top\"\u003e\n \u003cp\u003eDAPA (n=10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.996699669966997%\"\u003e\n \u003cp\u003e6.5 (4.8-7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.112211221122113%\"\u003e\n \u003cp\u003e6.05 (5.2-7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.432343234323433%\"\u003e\n \u003cp\u003e5.9 (4.2-7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.891089108910892%\"\u003e\n \u003cp\u003e0.614 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.915851272015656%\" valign=\"top\"\u003e\n \u003cp\u003eEMPA (n=15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.15655577299413%\"\u003e\n \u003cp\u003e5.9 (3.2-9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.223091976516635%\"\u003e\n \u003cp\u003e5.9 (2.9-7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e5.9 (3.4-8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.915851272015656%\"\u003e\n \u003cp\u003e0.584 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\"\u003e\n \u003cp\u003eGFR; Glomerular Filtration Rate,\u0026nbsp;AS; Active Substance, SD; Standart deviation, DAPA; Dapagliflozin, EMPA; Empagliflozin\u003c/p\u003e\n \u003cp\u003e*\u0026nbsp;p\u0026lt;0.05 was accepted as the limit of statistical significance at a 95% confidence interval.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e The Friedman one-way repeated measures analysis of variance by ranks test results.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Diabetes Mellitus, Glomerular Filtration Rate, Sodium-Glucose Cotransporter 2 Inhibitors, Uric Acid, Chronic Kidney Diseases","lastPublishedDoi":"10.21203/rs.3.rs-4112142/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4112142/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study aims to investigate the effect of different glomerular filtration rates (GFR) on serum uric acid (SUA) level changes in Type-2 DM patients receiving SGLT-2 inhibitor therapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe investigated 3004 patients on SGLT-2 inhibitor treatment between January-2017 and September-2022.\u0026nbsp; Patients who were taking irregular medication, did not attend follow-up visits, were taking medications that affected SUA levels, and were receiving gout treatment were excluded, leaving 410 patients in the sample after exclusions. Patients underwent measurement of blood and urine biochemical markers before SGLT-2 inhibitor treatment and at months 3 and 12. We divided the study group into 3 subgroups (GFR≥90, 60-89, 30-59 ml/min/1.73m2) according to the Kidney Disease Foundation for Improving Global Outcomes and analyzed the effects of SGLT-2 inhibitors on SUA levels according to GFR.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study group had a male:female ratio of 1.24:1 with a mean age of 59.1±11.55 years. When comparing before and after treatment, HbA1C, fasting blood glucose, creatinine, low-density lipoprotein cholesterol, triglycerides and SUA levels decreased significantly, while high-density lipoprotein cholesterol and urine glucose levels increased significantly. In patients with GFR between 30-59 ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e, no significant difference was found between the SUA values at pre-drug, 3rd, and 12th month drug therapy (p=0.368), and the effect on SUA levels differed according to GFR. This effect was not depending on the active substance and we considered it as a group effect of SGLT-2 inhibitors. The uric acid lowering effect of SGLT-2 inhibitors tends to increase as GFR increases.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe demonstrated that SGLT-2 inhibitors are not only anti-diabetic drugs, but may also have a protective role against diseases associated with hyperlipidemia and hyperuricemia in patients with preserved GFR, while no such effect should be expected in patients with low GFR.\u003c/p\u003e","manuscriptTitle":"Effect of Glomerular Filtration Rate on Uric Acid Metabolism in a Retrospective Cohort of Type-2 Diabetes Mellitus Patients on Sglt-2 Inhibitor Therapy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-21 16:05:29","doi":"10.21203/rs.3.rs-4112142/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9def8f96-862d-4969-862f-006e5531f75a","owner":[],"postedDate":"March 21st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-21T16:05:36+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-21 16:05:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4112142","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4112142","identity":"rs-4112142","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}