74 research outputs found

    Safety of Empagliflozin in Patients With Type 2 Diabetes and Chronic Kidney Disease: Pooled Analysis of Placebo-Controlled Clinical Trials

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    OBJECTIVE: To assess the safety of empagliflozin in patients with type 2 diabetes and moderate to severe chronic kidney disease (CKD) (category G3-4) enrolled in clinical trials. RESEARCH DESIGN AND METHODS: This analysis pooled data from 19 randomized, placebo-controlled, phase 1-4 clinical trials and 1 randomized, placebo-controlled extension study in which patients received empagliflozin 10 mg or 25 mg daily. Time to first occurrence of adverse events (AEs) was evaluated using Kaplan-Meier analysis and multivariable Cox regression models. RESULTS: Among a total of 15,081 patients who received at least one study drug dose, 1,522, 722, and 123 were classified as having G3A, G3B, and G4 CKD, respectively, at baseline. Demographic and clinical characteristics were similar between treatment groups across CKD categories. Rates of serious AEs, AEs leading to discontinuation, and events of special interest (including lower limb amputations and acute renal failure [ARF]) were also similar between empagliflozin and placebo across CKD subgroups. In adjusted Cox regression analyses, risks for volume depletion and ARF were similar for empagliflozin and placebo in the combined group with CKD categories G3B and G4 and the G3A group. Notably lower risks were observed in both groups for hyperkalemia (hazard ratio 0.59 [95% CI 0.37-0.96, P = 0.0323] and 0.48 [0.26-0.91, P = 0.0243], respectively) and edema (0.47 [0.33-0.68, P < 0.0001] and 0.44 [0.28-0.68, P = 0.0002], respectively). CONCLUSIONS: Use of empagliflozin in patients with type 2 diabetes and advanced CKD raised no new safety concerns and may have beneficial effects on the development of hyperkalemia and edema

    Plasma Uromodulin Correlates With Kidney Function and Identifies Early Stages in Chronic Kidney Disease Patients

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    Uromodulin, released from tubular cells of the ascending limb into the blood, may be associated with kidney function. This work studies the relevance of plasma uromodulin as a biomarker for kidney function in an observational cohort of chronic kidney disease (CKD) patients and subjects without CKD (CKD stage 0). It should be further evaluated if uromodulin allows the identification of early CKD stages. Plasma uromodulin, serumcreatinine, cystatin C, blood-urea-nitrogen (BUN) concentrations, and estimated glomerular filtration rate (eGFR CKD-EPIcrea-cystatin) were assessed in 426 individuals of whom 71 were CKD stage 0 and 355 had CKD. Besides descriptive statistics, univariate correlations between uromodulin and biomarkers/eGFR were calculated using Pearson-correlation coefficient. Multiple linear regression modeling was applied to establish the association between uromodulin and eGFR adjusted for demographic parameters and pharmacologic treatment. Receiver-operating-characteristic (ROC) analysis adjusted for demographic parameters was performed to test if uromodulin allows differentiation of subjects with CKD stage 0 and CKD stage I. Mean uromodulin plasma levels were 85.7 +/- 60.5 ng/mL for all CKD stages combined. Uromodulin was correlated with all biomarkers/eGFR in univariate analysis (eGFR: r = 0.80, creatinine: r = +/- 0.76, BUN: r = +/- 0.72, and cystatin C: r = +/- 0.79). Multiple linear regression modeling showed significant association between uromodulin and eGFR (coefficient estimate beta = 0.696, 95% confidence interval [CI] 0.603-0.719, P<0.001). In ROC analysis uromodulin was the only parameter that significantly improved a model containing demographic parameters to differentiate between CKD 0 degrees and I degrees (area under the curve [AUC] 0.831, 95% CI 0.746-0.915, P = 0.008) compared to creatinine, cystatin C, BUN, and eGFR (AUC for creatinine: 0.722, P = 0.056, cystatin C: 0.668, P = 0.418, BUN: 0.653, P = 0.811, and eGFR: 0.634, P = 0.823). Plasma uromodulin serves as a robust biomarker for kidney function and uniquely allows the identification of early stages of CKD. As a marker of tubular secretion it might represent remaining nephron mass and therefore intrinsic "kidney function'' rather than just glomerular filtration, the latter only being of limited value to represent kidney function as a whole. It therefore gives substantial information on the renal situation in addition to glomerular filtration and potentially solves the problem of creatinine-blind range of CKD, in which kidney impairment often remains undetected

    Plasma Uromodulin Correlates With Kidney Function and Identifies Early Stages in Chronic Kidney Disease Patients

    Get PDF
    Uromodulin, released from tubular cells of the ascending limb into the blood, may be associated with kidney function. This work studies the relevance of plasma uromodulin as a biomarker for kidney function in an observational cohort of chronic kidney disease (CKD) patients and subjects without CKD (CKD stage 0). It should be further evaluated if uromodulin allows the identification of early CKD stages. Plasma uromodulin, serumcreatinine, cystatin C, blood-urea-nitrogen (BUN) concentrations, and estimated glomerular filtration rate (eGFR CKD-EPIcrea-cystatin) were assessed in 426 individuals of whom 71 were CKD stage 0 and 355 had CKD. Besides descriptive statistics, univariate correlations between uromodulin and biomarkers/eGFR were calculated using Pearson-correlation coefficient. Multiple linear regression modeling was applied to establish the association between uromodulin and eGFR adjusted for demographic parameters and pharmacologic treatment. Receiver-operating-characteristic (ROC) analysis adjusted for demographic parameters was performed to test if uromodulin allows differentiation of subjects with CKD stage 0 and CKD stage I. Mean uromodulin plasma levels were 85.7 +/- 60.5 ng/mL for all CKD stages combined. Uromodulin was correlated with all biomarkers/eGFR in univariate analysis (eGFR: r = 0.80, creatinine: r = +/- 0.76, BUN: r = +/- 0.72, and cystatin C: r = +/- 0.79). Multiple linear regression modeling showed significant association between uromodulin and eGFR (coefficient estimate beta = 0.696, 95% confidence interval [CI] 0.603-0.719, P<0.001). In ROC analysis uromodulin was the only parameter that significantly improved a model containing demographic parameters to differentiate between CKD 0 degrees and I degrees (area under the curve [AUC] 0.831, 95% CI 0.746-0.915, P = 0.008) compared to creatinine, cystatin C, BUN, and eGFR (AUC for creatinine: 0.722, P = 0.056, cystatin C: 0.668, P = 0.418, BUN: 0.653, P = 0.811, and eGFR: 0.634, P = 0.823). Plasma uromodulin serves as a robust biomarker for kidney function and uniquely allows the identification of early stages of CKD. As a marker of tubular secretion it might represent remaining nephron mass and therefore intrinsic "kidney function'' rather than just glomerular filtration, the latter only being of limited value to represent kidney function as a whole. It therefore gives substantial information on the renal situation in addition to glomerular filtration and potentially solves the problem of creatinine-blind range of CKD, in which kidney impairment often remains undetected

    Worsening calcification propensity precedes all-cause and cardiovascular mortality in haemodialyzed patients

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    A novel in-vitro test (T-50-test) assesses ex-vivo serum calcification propensity which predicts mortality in HD patients. The association of longitudinal changes of T-50 with all-cause and cardiovascular mortality has not been investigated. We assessed T-50 in paired sera collected at baseline and at 24 months in 188 prevalent European HD patients from the ISAR cohort, most of whom were Caucasians. Patients were followed for another 19 [interquartile range: 11-37] months. Serum T-50 exhibited a significant decline between baseline and 24 months (246 +/- 64 to 190 +/- 68 minutes;p < 0.001). With serum Delta-phosphate showing the strongest independent association with declining T-50 (r = -0.39;p < 0.001) in multivariable linear regression. The rate of decline of T-50 over 24 months was a significant predictor of all-cause (HR = 1.51 per 1SD decline, 95% CI: 1.04 to 2.2;p = 0.03) and cardiovascular mortality (HR = 2.15;95% CI: 1.15 to 3.97;p = 0.02) in Kaplan Meier and multivariable Cox-regression analysis, while cross-sectional T-50 at inclusion and 24 months were not. Worsening serum calcification propensity was an independent predictor of mortality in this small cohort of prevalent HD patients. Prospective larger scaled studies are needed to assess the value of calcification propensity as a longitudinal parameter for risk stratification and monitoring of therapeutic interventions

    Pretransplant Serum Uromodulin and Its Association with Delayed Graft Function Following Kidney Transplantation—A Prospective Cohort Study

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    Delayed graft function (DGF) following kidney transplantation is associated with increased risk of graft failure, but biomarkers to predict DGF are scarce. We evaluated serum uromodulin (sUMOD), a potential marker for tubular integrity with immunomodulatory capacities, in kidney transplant recipients and its association with DGF. We included 239 kidney transplant recipients and measured sUMOD pretransplant and on postoperative Day 1 (POD1) as independent variables. The primary outcome was DGF, defined as need for dialysis within one week after transplantation. In total, 64 patients (27%) experienced DGF. In multivariable logistic regression analysis adjusting for recipient, donor and transplant associated risk factors each 10 ng/mL higher pretransplant sUMOD was associated with 47% lower odds for DGF (odds ratio (OR) 0.53, 95% confidence interval (95%-CI) 0.30–0.82). When categorizing pretransplant sUMOD into quartiles, the quartile with the lowest values had 4.4-fold higher odds for DGF compared to the highest quartile (OR 4.41, 95%-CI 1.54–13.93). Adding pretransplant sUMOD to a model containing established risk factors for DGF in multivariable receiver-operating-characteristics (ROC) curve analysis, the area-under-the-curve improved from 0.786 [95%-CI 0.723–0.848] to 0.813 [95%-CI 0.755–0.871, p = 0.05]. SUMOD on POD1 was not associated with DGF. In conclusion, higher pretransplant sUMOD was independently associated with lower odds for DGF, potentially serving as a non-invasive marker to stratify patients according to their risk for developing DGF early in the setting of kidney transplantation

    Cardiovascular Mortality Can Be Predicted by Heart Rate Turbulence in Hemodialysis Patients

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    Background: Excess mortality in hemodialysis patients is mostly of cardiovascular origin. We examined the association of heart rate turbulence (HRT), a marker of baroreflex sensitivity, with cardiovascular mortality in hemodialysis patients. Methods: A population of 290 prevalent hemodialysis patients was followed up for a median of 3 years. HRT categories 0 (both turbulence onset [TO] and slope [TS] normal), 1 (TO or TS abnormal), and 2 (both TO and TS abnormal) were obtained from 24 h Holter recordings. The primary end-point was cardiovascular mortality. Associations of HRT categories with the endpoints were analyzed by multivariable Cox regression models including HRT, age, albumin, and the improved Charlson Comorbidity Index for hemodialysis patients. Multivariable linear regression analysis identified factors associated with TO and TS. Results: During the follow-up period, 20 patients died from cardiovascular causes. In patients with HRT categories 0, 1 and 2, cardiovascular mortality was 1, 10, and 22%, respectively. HRT category 2 showed the strongest independent association with cardiovascular mortality with a hazard ratio of 19.3 (95% confidence interval: 3.69-92.03;P < 0.001). Age, calcium phosphate product, and smoking status were associated with TO and TS. Diabetes mellitus and diastolic blood pressure were only associated with TS. Conclusion: Independent of known risk factors, HRT assessment allows identification of hemodialysis patients with low, intermediate, and high risk of cardiovascular mortality. Future prospective studies are needed to translate risk prediction into risk reduction in hemodialysis patients
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