Sodium-glucose cotransporter 2 (SGLT2) inhibitors can cause a reversible decline in glomerular filtration rate (GFR), which may influence dosing recommendations for renally excreted medications. In practice, GFR is typically estimated by serum creatinine concentration, but creatinine may not be a reliable indicator of GFR decline in the setting of SGLT2 inhibitor use. Alternative filtration markers such as cystatin C, β-trace protein (BTP), and β2-microglobulin (B2M) may be more appropriate, but little is known about how these markers are affected by SGLT2 inhibitor use. Therefore, we determined creatinine, cystatin C, BTP, and B2M concentration in a crossover study of 35 people with type 2 diabetes receiving 12 weeks of dapagliflozin treatment or placebo. Estimated GFR (eGFR) based on creatinine (eGFRcre), cystatin C (eGFRcys), their combination (eGFRcomb), or a panel of all four markers (eGFRpanel) was compared with measured GFR (mGFR) based on plasma clearance of chromium-51 labeled ethylenediamine tetraacetic acid (51Cr-EDTA). Dapagliflozin treatment was associated with a significant decrease in mGFR (-9 mL/min/1.73 m2, P < 0.001) but not a corresponding increase in concentration of any filtration marker. No eGFR equation accurately predicted change in mGFR between treatment periods, but eGFRcomb and eGFRpanel yielded the highest overall accuracy relative to mGFR across both treatment periods. These findings highlight the stability in performance gained by combining multiple filtration markers but suggest that eGFR in general is not an ideal metric for assessing short-term GFR decline in people initiating SGLT2 inhibitor therapy.

Background: Sodium-glucose cotransporter 2 (SGLT- 2) inhibitors exert cardiovascular and kidney-protective effects in people with diabetes. Attenuation of inflammation could be important for systemic protection. The lectin pathway of complement system activation is linked to diabetic nephropathy. We hypothesized that SGLT-2 inhibitors lower the circulating level of pattern-recognition molecules of the lectin cascade and attenuate systemic complement activation. Methods: Analysis of paired plasma samples from the DapKid crossover intervention study where patients with type 2 diabetes mellitus (T2DM) and albuminuria were treated with dapagliflozin and placebo for 12 weeks (10 mg/day, n=36). ELISA was used to determine concentrations of collectin kidney 1 (CL-K1), collectin liver 1 (CL-L1), mannose-binding lectin (MBL), MBL-associated serine protease 2 (MASP-2), the anaphylatoxin complement factor 3a (C3a), the stable C3 split product C3dg and the membrane attack complex (sC5b-9). Results: As published before, dapagliflozin treatment lowered Hba(1C) from 74 (14.9) mmol/mol to 66 (13.9) mmol/mol (p<0.0001), and the urine albumin/creatinine ratio from 167.8 mg/g to 122.5 mg/g (p<0.0001). Plasma concentrations of CL-K1, CL-L1, MBL, and MASP-2 did not change significantly after dapagliflozin treatment (P>0.05) compared to placebo treatment. The plasma levels of C3a (P<0.05) and C3dg (P<0.01) increased slightly but significantly, 0.6 [0.2] units/mL and 76 [52] units/mL respectively, after dapagliflozin treatment. The C9-associated neoepitope in C5b-9 did not change in plasma concentration by dapagliflozin (P>0.05). Conclusion: In patients with type 2 diabetes and albuminuria, SGLT-2 inhibition resulted in modest C3 activation in plasma, likely not driven by primary changes in circulating collectins and not resulting in changes in membrane attack complex. Based on systemic analyses, organ-specific local protective effects of gliflozins against complement activation cannot be excluded.

Chronic kidney disease (CKD) is a common complication of type 2 diabetes (T2D) characterized by albuminuria and a progressive decline in the glomerular filtration rate (GFR).1 CKD in the setting of T2D can be the result of diabetic nephropathy, non-diabetic renal disease, or a combination of these factors.2 Regardless of the aetiology, early diagnosis of CKD enables interventions to slow GFR decline, including the discontinuation of nephrotoxic medications and the initiation of renoprotective medications.3, 4 Reduced GFR also necessitates dose adjustments for renally excreted medications, including several antidiabetic agents.5 Improper dose adjustment can lead to adverse drug reactions, which are a common but largely preventable cause of hospitalization.6 Therefore, accurate GFR assessment is crucial for effective diagnosis and management of CKD in people with T2D. Kidney Disease Improving Global Outcomes (KDIGO) guidelines from 2012 recommend using estimated GFR (eGFR) equations based on creatinine and/or cystatin C for evaluation and management of CKD.7 Creatinine is the least expensive option and the biomarker of choice in most clinical settings. Cystatin C is less common, but some clinical settings (notably Sweden) have incorporated it into routine care. The main limitation of these endogenous filtration markers is that their concentration is influenced by factors other than kidney function. As these 'non-renal factors' are unique to each filtration marker, combining multiple markers in a single equation reduces the influence of non-renal factors. Unsurprisingly, eGFR equations that combine creatinine and cystatin C have been shown to outperform equations based on either filtration marker alone in the general population,8 although this may not be true for people with T2D.9 The most common eGFR equations in clinical practice are those developed by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI). The original CKD-EPI equations based on creatinine (2009 CKD-EPIcre), cystatin C (2012 CKD-EPIcys), or their combination (2012 CKD-EPIcomb) have largely replaced alternative equations in both the United States and Europe.10, 11 In response to criticisms of including race as a variable, the CKD-EPI group revised their equations to exclude race, yielding 2021 CKD-EPIcre and 2021 CKD-EPIcomb.12 Similarly, the 2012 CKD-EPIcys equation was revised to exclude sex as a variable, yielding 2023 CKD-EPIcys.13 National renal societies in the United States now recommend 2021 CKD-EPIcre and 2021 CKD-EPIcomb over their earlier counterparts.14 However, there is an ongoing debate about whether this recommendation is appropriate for European populations, and most clinical settings in Europe continue to use 2009 CKD-EPIcre. Given the apparent success of combining creatinine and cystatin C, it has been suggested that incorporating additional filtration markers could further reduce the impact of non-renal factors. In 2020, the CKD-EPI group developed an equation based on a panel of filtration markers (2020 CKD-EPIpanel), which includes creatinine, cystatin C, β-trace protein (BTP) and β2-microglobulin (B2M).15 Importantly, the authors found that the inclusion of BTP and B2M resulted in strong performance across patient subgroups without the explicit inclusion of race. The purpose of the present study was to compare the performance of these different CKD-EPI equations to identify the most accurate equation(s) among European adults with T2D. This was a post-hoc analysis of two clinical trials ('DapKid' and 'LIRALBU') performed at the Steno Diabetes Center Copenhagen, Herlev, Denmark.16, 17 Both trials enrolled non-Black adults (age ≥18 years) with T2D, and participants who completed the original trials were included in the current analysis. The most relevant difference between cohorts is that the DapKid trial included adults with eGFR ≥45 ml/min/1.73 m2, whereas the LIRALBU trial included adults with eGFR ≥30 ml/min/1.73 m2. A full list of inclusion and exclusion criteria and other information about each study's purpose and design can be found at ClinicalTrials.gov (NCT02914691 and NCT02545738). In both studies, participants underwent GFR measurements before any planned interventions. GFR was measured at the Steno Diabetes Center Copenhagen by plasma clearance of chromium-51-labelled ethylenediamine tetraacetic acid using four-point sampling (180, 200, 220 and 240 min after injection). Demographic information and blood samples were collected immediately before GFR measurement, and laboratory markers were measured using standard assays. Creatinine was measured by a traceable enzymatic assay [coefficient of variation (CV): 4%], cystatin C was measured by a traceable immunoturbidimetric assay (CV: 5%), BTP was measured by nephelometry (CV: 5%) and B2M was measured by immunoturbidimetry (CV: 4%). GFR was estimated using equations from CKD-EPI based on creatinine (2009 and 2021 CKD-EPIcre), cystatin C (2012 and 2023 CKD-EPIcys), the combination of creatinine and cystatin C (2012 and 2021 CKD-EPIcomb), or a panel of creatinine, cystatin C, BTP and B2M (2020 CKD-EPIpanel) (Table S1). Continuous variables are presented as a median with the interquartile range, and differences between cohorts were evaluated by the Wilcoxon rank-sum test. Categorical variables are presented as a number with the percentage of study participants, and differences between cohorts were evaluated by Fisher's exact test. Performance of each CKD-EPI equation relative to measured GFR (mGFR) was assessed by bias [median value of (eGFR-mGFR)] and the percentage of eGFR values within ±30% (P30) or ± 20% (P20) of the mGFR values. Bland-Altman plots were generated to represent bias at different levels of mGFR. Based on visual inspection of these plots, a sensitivity analysis was performed to evaluate performance of each CKD-EPI equation relative to mGFR among study participants with mGFR <120 ml/min/1.73 m2. In total, 36 participants completed the DapKid trial and 27 completed the LIRALBU trial, for a combined sample size of 63 (Figure S1). Nine individuals participated in but did not complete the original clinical trials, and the available clinical characteristics for these individuals were similar to those of the final study population (data not shown). Clinical characteristics for each clinical trial and the combined cohort are shown in Table 1. The combined cohort had a median age of 66 years, body mass index of 31 kg/m2, mGFR of 76 ml/min/1.73 m2, glycated haemoglobin of 65 mmol/mol, and 14.3% were female. Compared with participants in the LIRALBU trial, those from the DapKid trial had a higher median mGFR (81 vs. 69 ml/min/1.73 m2, p = .09) and glycated haemoglobin (68 vs. 58 mmol/mol, p = .001). Otherwise, there were no substantial differences in characteristics between cohorts. The performance of each CKD-EPI equation relative to mGFR is shown in Table 2. Bias was positive for 2009 and 2021 CKD-EPIcre and negative for all other equations. Bias was smallest (closest to 0) for 2009 CKD-EPIcre (+0.4 ml/min/1.73 m2) and 2021 CKD-EPIcomb (−0.7 ml/min/1.73 m2); P30 was highest for 2012 CKD-EPIcomb (90.5%) and 2020 CKD-EPIpanel (93.7%); and P20 was highest for 2021 CKD-EPIcomb (74.6%) and 2020 CKD-EPIpanel (79.4%). Bias of each CKD-EPI equation according to mGFR is shown in Figure S2. Seven individuals had mGFR ≥120 ml/min/1.73 m2, and the performance of each CKD-EPI equation relative to mGFR for the remaining 56 study participants (mGFR <120 ml/min/1.73 m2) is shown in Table S2. The impact of switching from 2009 CKD-EPIcre to an alternative CKD-EPI equation is shown in Table S3. Switching to 2021 CKD-EPIcre would result in a higher mean eGFR, whereas switching to any other CKD-EPI equation would result in a lower mean eGFR. In conclusion, we found that the 2009 CKD-EPIcre equation had the smallest bias but also relatively low P30 and P20, indicating a high overall accuracy but large interindividual variation. Both cystatin C-based equations yielded a large negative bias, probably because of non-renal factors in this population, such as obesity and inflammation, that contribute to increased cystatin C concentration.18, 19 Removal of the race variable in 2021 CKD-EPIcre resulted in a higher (more positive) bias and worse P30, whereas removal of the sex variable in 2023 CKD-EPIcys resulted in a lower (more negative) bias and worse P30. Despite the poor performance of cystatin C-based equations, the 2012 and 2021 CKD-EPIcomb equations had a small (close to 0) bias and higher P30 and P20 than equations based on creatinine or cystatin C alone, demonstrating the strength of combining filtration markers. The performance of 2021 CKD-EPIcomb was largely unaffected by the removal of the race variable, which could be explained by the reweighting of the creatinine coefficient. The 2020 CKD-EPIpanel equation yielded the most consistent performance (highest P30 and P20), but it did not substantially outperform either of the CKD-EPIcomb equations. Interestingly, all CKD-EPI equations yielded a large negative bias in study participants with mGFR >120 ml/min/1.73 m2. These cases may represent individuals in the early stages of renal damage who are experiencing glomerular hyperfiltration, which could explain the lag between increased mGFR and decreased filtration marker concentrations (increased eGFR). Excluding these individuals from the analysis resulted in similar performance metrics, but readers should be aware of this phenomenon when interpreting eGFR (or mGFR) in people with T2D. Based on these findings, we recommend using a creatinine-cystatin C combination equation for routine clinical use in European adults with T2D or 2009 CKD-EPIcre if cystatin C measurements are unavailable. Providers should also recognize that switching from 2009 CKD-EPIcre to an alternative equation would probably impact the diagnosis and management of CKD in people with T2D. However, these conclusions are drawn from a relatively small cohort of non-Black, primarily male adults with advanced T2D and eGFR >30 ml/min/1.73 m2. We also did not test the performance of other eGFR equations, such as those from the European Kidney Function Consortium (EKFC), which may be more accurate than CKD-EPI in European populations.20 The most appropriate eGFR equation for individuals will always depend on the specific clinical scenario and the presence of non-renal factors. All authors have accepted responsibility for the content of this manuscript and approved its submission. The authors have no conflicts of interest to declare. The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer-review/10.1111/dom.15536. De-identified data can be made available upon reasonable request. Those submitting a request will be required to send a protocol, plan for statistical analysis, and data access agreement to ensure appropriate use of the study data. Figure S1. Flow diagram for participant completion of the DapKid and LIRALBU clinical trials and inclusion in the present study. Figure S2. Bland-Altman plots of eGFR-mGFR versus mGFR for each eGFR equation. Table S1. List of CKD-EPI equations to estimate glomerular filtration rate. Table S2. Performance of CKD-EPI equations relative to mGFR among 56 European adults with T2D and mGFR <120 ml/min/1.73 m2. Table S3. Mean change in eGFR when switching from 2009 CKD-EPIcre to an alternative equation. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Introduction: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have emerged as novel therapeutics to treat diabetic kidney disease (DKD). Although the beneficial effects of SGLT2i have been demonstrated, their target mechanisms on kidney function are unknown. The current study aimed to elucidate these mechanisms by studying SGLT2i-induced changes in the urinary proteome of persons with type 2 diabetes (T2D) and DKD. Methods: A total of 40 participants with T2D were enrolled in a double -blinded randomized cross -over trial at the Steno Diabetes Center Copenhagen, Denmark. They were treated with 10 mg of dapagliflozin for 12 weeks. Thirty-two participants with complete urinary proteomics measures before and after the trial were included. All participants received renin-angiotensin system blockade and had albuminuria, (urine albumin-to-creatinine ratio [UACR] >= 30 mg/g). A type 1 diabetes (T1D) cohort consisting of healthy controls and persons with DKD was included for validation. Urinary proteome changes were analyzed using Wilcoxon signed-rank test. Functional enrichment analysis was conducted to discover affected biological processes. Results: Dapagliflozin treatment significantly (P-adjusted < 0.05) affected 36 urinary peptide fragments derived from 19 proteins. Eighteen proteins were correspondingly reflected in the validation cohort. A multifold change in peptide abundance was observed in many proteins (A1BG, urinary albumin [ALB], Caldesmon 1, COLCRNN, heat shock protein 90-beta [HSP90AB1], IGLL5, peptidase inhibitor 16 [PI16], prostaglandin-H2-D-isomerase [PTGDS], SERPINA1). These also included urinary biomarkers of kidney fibrosis and function (type I and III collagens and albumin). Biological processes relating to inflammation, wound healing, and kidney fibrosis were enriched. Conclusion: The current study discovers the urinary proteome impacted by the SGLT2i, thereby providing new potential target sites and pathways, especially relating to wound healing and inflammation.

Animal studies have shown that SGLT2 inhibition decreases oxidative stress, which may explain the cardiovascular protective effects observed following SGLT2 inhibition treatment. Thus, we investigated the effects of two and twelve weeks SGLT2 inhibition on DNA and RNA oxidation. Individuals with type 2 diabetes (n = 31) were randomized to two weeks of treatment with the SGLT2 inhibitor empagliflozin treatment (25 mg once daily) or placebo. The primary outcome was changes in DNA and RNA oxidation measured as urinary excretion of 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodG) and 8-oxo-7,8-dihydroguanosine (8-oxoGuo), respectively. In another trial, individuals with type 2 diabetes (n = 35) were randomized to twelve weeks of dapagliflozin treatment (10 mg once daily) or placebo in a crossover study. Changes in urinary excretion of 8-oxodG and 8-oxoGuo were investigated as a posthoc analysis. Compared with placebo treatment, two weeks of empagliflozin treatment did not change urinary excretion of 8-oxodG (between-group difference: 0.3 nmol/24-hour (95% CI: -4.2 to 4.8)) or 8-oxoGuo (1.3 nmol/24-hour (95% CI: -4.7 to 7.3)). From a mean baseline 8-oxodG/creatinine urinary excretion of 1.34 nmol/mmol, dapagliflozin-treated individuals changed 8-oxodG/creatinine by -0.17 nmol/mmol (95% CI: -0.29 to -0.04) following twelve weeks of treatment, whereas placebo-treated individuals did not change 8-oxodG/creatinine (within-group effect: 0.10 nmol/mmol (95% CI: -0.02 to 0.22)) resulting in a significant between-group difference (p = 0.01). Urinary excretion of 8-oxoGuo was unaffected by dapagliflozin treatment. In conclusion, two weeks of empagliflozin treatment did not change DNA or RNA oxidation. However, a posthoc analysis revealed that longer-term dapagliflozin treatment decreased DNA oxidation. Clinicaltrials.gov: NCT02890745 and NCT02914691.

Objective: To evaluate the effect of the sodium-glucose co-transporter 2 inhibitor dapagliflozin, on the kidney risk urinary proteomic classifier (CKD273), in persons with type 2 diabetes and albuminuria. Research Design and Methods: In a double-blind randomized controlled crossover trial we assigned participants with type 2 diabetes and urinary albumin-creatinine ratio (UACR) ≥30 mg/g to receive dapagliflozin or matching placebo added to guideline recommended treatment (NCT02914691). Treatment periods lasted 12 weeks at which crossover to opposing treatment occurred. The primary outcome was change in CKD273 score. Secondary outcomes include regression from high-risk to low-risk CKD273 pattern using the pre-specified cut-off score of 0.154. The primary outcome was assessed using paired t-test between end-to-end CKD273 levels after dapagliflozin and placebo treatment. McNemar’s test was used to assess regression in risk category. Results: A total of 40 participants were randomized and 32 completed the trial with intact proteomic measurements. Twenty-eight (88%) were male, the baseline mean (standard deviation) age was 63.0 (8.3) years, mean diabetes duration was 15.4 (4.5) years, mean HbA1c was 73 (14) mmol/mol (8.8 (1.3) %) and median (inter-quartile range) UACR was 154 (94, 329) mg/g. Dapagliflozin significantly lowered CKD273 score compared to placebo (-0.221, 95%CI: -0.356, -0.087, p=0.002). Fourteen participants exhibited a high-risk pattern after dapagliflozin treatment compared to 24 after placebo (p=0.021). Conclusions: Dapagliflozin added to renin-angiotensin system inhibition reduced the urinary proteomic classifier CKD273 in persons with type 2 diabetes and albuminuria paving the way for the further investigation of CKD273 as a modifiable kidney risk factor.

Background: Elevated soluble urokinase plasminogen activator receptor (suPAR) is highly associated with increased risk of diabetic complications. Dapagliflozin is a drug inhibiting the sodium-glucose co-transporter 2 in the kidney to decrease blood glucose, while also decreasing risk of kidney disease, heart failure, and death. Therefore, we have investigated suPAR as a monitor for treatment effect with dapagliflozin in diabetes. Methods: suPAR was measured in two double-blinded randomized clinical cross-over trials. The first trial investigated the effect of a single dose dapagliflozin 50 mg or placebo 12 h after intake, in individuals with type 1 diabetes and albuminuria. The second trial investigated the effect of a daily dose dapagliflozin 10 mg or placebo for 12 weeks, in individuals with type 2 diabetes and albuminuria. suPAR was measured in serum samples taken, in the acute trial, after treatment with dapagliflozin and placebo, and in the long-term trial, before and after treatment with dapagliflozin and placebo. Effect of dapagliflozin on suPAR levels were assessed using paired t -test. Results: 15 participants completed the acute trial and 35 completed the long-term trial. Mean difference in suPAR between dapagliflozin and placebo in the acute trial after 12 h was 0.70 ng/ml (95% CI: 0.66; 1.33, p = 0.49). In the long-term trial the mean difference was 0.06 ng/ml (95% CI -0.15; 0.27, p = 0.57). Conclusion: Based on our findings we conclude that suPAR is not a feasible marker to monitor the effect of treatment with dapagliflozin. Thus, a further search of suitable markers must continue.

Aims: Sodium glucose transport inhibitors (SGLT2i) can reduce risk of heart failure (HF) and cardiovascular death in people with type 2 diabetes (T2D) and existing cardiovascular disease. Our aim was to examine the effect of the SGLT2i dapagliflozin on cardiac function in people with T2D and albuminuria. Methods: A secondary analysis of a double-blind, randomized, cross-over study of 12 weeks treatment with dapagliflozin 10 mg versus placebo. Myocardial function was assessed by echocardiography and biomarkers of cardiac risk were measured. An exploratory diastolic composite of echocardiographic variables was computed. Results: Of the 36 participants completing the study 89% were male, mean age 64 = 8 years, diabetes duration 16.4 +/- 4.7 years and HbA(1c) 73 +/- 15 mmol/mol (8.9 = 1.4%), 30.6% had former cardiovascular events and 32% had macroalbuminuria. Mean left ventricular ejection fraction (LVEF) was 55.4% after placebo and 54.3% after dapagliflozin (p = 0.15), global longitudinal strain -16.1 vs. -15.9, (p = 0.64), E/e' 7.6 vs. 7.6 (p = 0.082), and tissue Doppler velocity e' 10.0 vs. 10.6 (p = 0.05). The composite score showed diastolic function improvement of 19.8% (p = 0.021). No other significant changes were observed. Conclusions: Dapagliflozin may have minor effects on diastolic function in people with T2D, albuminuria and preserved LVEF. (C) 2020 Elsevier Inc. All rights reserved.

Background The glycocalyx is an extracellular layer lining the lumen of the vascular endothelium, protecting the endothelium from shear stress and atherosclerosis and contributes to coagulation, immune response and microvascular perfusion. The GlycoCheck system estimates glycocalyx’ thickness in vessels under the tongue from perfused boundary region (PBR) and microvascular perfusion (red blood cell (RBC) filling) via a camera and dedicated software. Objectives Evaluating reproducibility and influence of examination conditions on measurements with the GlycoCheck system. Methods Open, randomised, controlled study including 42 healthy smokers investigating day-to-day, side-of-tongue, inter-investigator variance, intraclass-correlation (ICC) and influence of examination conditions at intervals from 0–180 minutes on PBR and RBC filling. Results Mean (SD) age was 24.9 (6.1) years, 52% were male. There was no significant intra- or inter-investigator variation for PBR or RBC filling nor for PBR for side-of-tongue. A small day-to-day variance was found for PBR (0.012μm, p = 0.007) and RBC filling (0.003%, p = 0.005) and side-of-tongue, RBC filling (0.025%, p = 0.009). ICC was modest but highly improved by increasing measurements. Small significant influence of cigarette smoking (from 40–180 minutes), high calorie meal intake and coffee consumption was found. The latter two peaking immediately and tapering off but remained significant up to 180 minutes, highest PBR changes for the three being 0.042μm (p<0.05), 0.183μm (p<0.001) and 0.160μm (p<0.05) respectively. Conclusions Measurements with the GlycoCheck system have a moderate reproducibility, but highly increases with multiple measurements and a small day-to-day variability. Smoking, meal and coffee intake had effects up to 180 minutes, abstinence is recommended at least 180 minutes before GlycoCheck measurements. Future studies should standardise conditions during measurements.

Sodium glucose co-transporter 2 (SGLT2) inhibitors reduce the risk of heart and kidney failure in patients with type 2 diabetes, possibly due to diuretic effects. Previous non-placebo-controlled studies with SGLT2 inhibitors observed changes in volume markers in healthy individuals and in patients with type 2 diabetes with preserved kidney function. It is unclear whether patients with type 2 diabetes and signs of kidney damage show similar changes. Therefore, a post hoc analysis was performed on two randomized controlled trials (n = 69), assessing effects of dapagliflozin 10 mg/day when added to renin–angiotensin system inhibition in patients with type 2 diabetes and urinary albumin-to-creatinine ratio ≥30 mg/g. Blood and 24-h urine was collected at the start and the end of treatment periods lasting six and 12 weeks. Effects of dapagliflozin compared to placebo on various markers of volume status were determined. Fractional lithium excretion, a marker of proximal tubular sodium reabsorption, was assessed in 33 patients. Dapagliflozin increased urinary glucose excretion by 217.2 mmol/24 h (95% confidence interval (CI): from 155.7 to 278.7, p < 0.01) and urinary osmolality by 60.4 mOsmol/kg (from 30.0 to 90.9, p < 0.01), compared to placebo. Fractional lithium excretion increased by 19.6% (from 6.7 to 34.2; p < 0.01), suggesting inhibition of sodium reabsorption in the proximal tubule. Renin and copeptin increased by 46.9% (from 21.6 to 77.4, p < 0.01) and 33.0% (from 23.9 to 42.7, p < 0.01), respectively. Free water clearance (FWC) decreased by −885.3 mL/24 h (from −1156.2 to −614.3, p < 0.01). These changes in markers of volume status suggest that dapagliflozin exerts both osmotic and natriuretic diuretic effects in patients with type 2 diabetes and kidney damage, as reflected by increased urinary osmolality and fractional lithium excretion. As a result, compensating mechanisms are activated to retain sodium and water.

Objective: Evaluating effect of the sodium-glucose cotransporter 2 inhibitor dapagliflozin on the urinary CKD273 proteomic score in patients with type 2 diabetes (T2D) and albuminuria. Methods: A double-blinded, randomized, placebo-controlled, crossover trial of 12 weeks dapagliflozin (10 mg) or matching placebo added to standard care. Patients included (n=40) had T2D and albuminuria (UACR≥30 mg/g). At baseline and end of treatment periods HbA1C was measured, spot urine for urinary proteomics and three consecutive morning spot urines for albuminuria were collected and 24h blood pressure and 51Cr-EDTA (GFR) were performed. Urine proteomic patterns was evaluated using the CKD273 score. To determine high-risk or low risk of diabetic kidney disease a previously defined cut off of 0.154 was used. Results were compared using mixed model analysis adjusted for age, sex, systolic blood pressure, HbA1c, albuminuria and GFR. Chi-square analysis was used to examine change in risk category based on proteomics. Results: Baseline values for the 36 participants completing the study: Geometric mean urinary albumin creatinine ratio (UACR) = 147 (IQR 82-330) mg/g, mean eGFR = 84 ml/minute/1.73 m2 (SD±19.3), HbA1c = 73 mmol/mol (SD±15) and 24h blood pressure = 147/82 mmHg (SD±12.0/8.1). Dapagliflozin reduced UACR by 44% (95% CI 17-78%, p<0.01), GFR by 10.6 (6-15) ml/minute/1.73m2 (p<0.01), HbA1c by 7.4 (5-10) mmol/mol (p<0.01) and 24h blood pressure by 4.1/2.9 mmHg (p=0.058/p<0.01). The CKD273 proteomic score improved from mean 0.457 with -0.217 (p<0.01) and renal risk category improved from 72% at high risk to 47% after dapagliflozin (p=0.032). Conclusions: Dapagliflozin added to standard care in T2D patients with albuminuria significantly reduced the urinary CKD273 proteomic score and renal risk. This indicates a possible direct beneficial effect on the kidneys, which may explain part of the renal benefit of SGLT2i seen in clinical trials. Disclosure F. Persson: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Novo Nordisk A/S. Research Support; Self; AstraZeneca, Sanofi. Speaker's Bureau; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi. M.K. Eickhoff: None. H. Mischak: Stock/Shareholder; Self; Mosaiques Diagnostics. M. Frimodt-Moller: None. P. Rossing: Advisory Panel; Self; AstraZeneca, Bayer AG, Boehringer Ingelheim Pharmaceuticals, Inc. Speaker's Bureau; Self; Eli Lilly and Company, Merck Sharp & Dohme Corp. Other Relationship; Self; Novartis AG, Novo Nordisk A/S. Funding AstraZeneca

Urinary levels of kidney injury molecule 1 (u-KIM-1) and neutrophil gelatinase-associated lipocalin (u-NGAL) reflect proximal tubular pathophysiology and have been proposed as risk markers for development of complications in patients with type 2 diabetes (T2D). We clarify the predictive value of u-KIM-1 and u-NGAL for decline in eGFR, cardiovascular events (CVE) and all-cause mortality in patients with T2D and persistent microalbuminuria without clinical cardiovascular disease.

RESULTS: 523 patients included 391 men(74.8%),mean age 62612 years, mean serum creatinine 2.762.2mg/ dl, glycosylated hemoglobin 761.7% and proteinuria 3.2 (1.5-6) gr/24h.In the renal biopsy, 36% had DN, 53% NDN and 11% DN and NDN.35.2% (n¼184) of patients needed RRT, of them47.3%presented DN, 38.6% NDN and 14.1% ND and NDN.One patient from the DN group and two patients from the NDN group initiated RRT before the renal biopsy.The overall mortality of the studied patients was 18.7% (n¼98), of them 42% presented DN, 46% NDN and 12% DN and NDN.We performed the analysis of renal survival and prognosis using the Kaplan-Meier curves: We observed that patients with ND or ND þ NDN presented worse renal prognosis than NDN patients(p<0.001).We did not observe differences between the three groups when we analyzed patient survival.(seefigure).In the multivariate analysis of Cox adjusting by variable sex, age, renal function, glycosylated hemoglobin, proteinuria, ischemic heart disease, peripheral vasculopathy and treatment with RAASB, DN is a risk factor for RRT(see table ).CONCLUSIONS: In diabetics with renal biopsy, patients with DN have worse renal prognosis.The histological diagnosis of renal involvement in the diabetic can facilitate an effective treatment and an improvement in the renal prognosis.

Background The upper age limit to receive a kidney transplant has progressively risen, but the outcomes of elderly (ages ≥65 years) transplant recipients remain understudied. We therefore evaluated mortality, graft failure, and predictors of these outcomes in this population. Methods Three cohorts of recipients transplanted between 1963 and 2012 (ages <50 years [n=2900], 50–64 years [n=1218], and ≥65 years [n=364] at transplantation) were compared for allograft and patient outcomes. Three similar age cohorts transplanted after 2000 (n=1410) were studied separately to address era effect. Results Death-censored graft survival was higher in recipients ages ≥65 years: 5, 10, and 15 years was 90.7%, 80.4%, and 73.7%; for ages 50–64 years, it was 87.2%, 77.6%, and 71.5%; and for ages <50 years was 79.8%, 70.3%, and 60.8%. Risk factors for graft failure in those ages ≥65 years included panel-reactive antibody >10%, congestive heart failure (CHF), delayed graft function, and cellular rejection. The 5-, 10-, and 15-year patient survival rate was 69.7%, 36.0%, and 14.0% for those ages ≥65 years; 76.4%, 54.8%, and 34.0% for those ages 50–64 years; and 81.7%, 66.7%, and 52.2% for those ages <50 years. For the entire cohort of elderly recipients, coronary artery disease and CHF were associated with mortality, and in those recipients transplanted after 2000, the risk factors for mortality were coronary artery disease, graft failure, peripheral vascular disease, and cause of end-stage renal disease listed as other. For graft failure, only CHF and cellular rejection were associated with this outcome. Conclusions The overall outcomes of transplantation in elderly kidney transplant recipients ages ≥65 years are excellent, but the risk factors for mortality and graft failure are distinctly different than those observed in younger recipients.