Hyperphosphatemia is present in most patients with end‐stage renal disease (ESRD) and has been associated with increased cardiovascular mortality. Phosphate binders (calcium‐based and calcium free) are the mainstay pharmacologic treatment to lower phosphorus levels in patients with ESRD. We evaluated biochemical markers of vascular calcification, inflammation, and endothelial dysfunction in patients with chronic kidney disease (CKD) treated with sevelamer carbonate (SC) versus calcium acetate (CA). Fifty patients with CKD (stages 3 and 4) were enrolled and assigned to treatment with SC and CA for 12 weeks. At the end of the study the biomarkers of vascular calcification, inflammation, and endothelial dysfunction were analyzed. A significant increase in HDL‐cholesterol was observed with SC but not with CA in patients with CKD. Treatment with SC reduced serum phosphate, calcium phosphate, and FGF‐23 levels and there was no change with CA treatment. The inflammatory markers IL‐8, IFN‐γ, and TNFα decreased with response to both treatments. The levels of IL‐6 significantly increased with CA treatment and no change was observed in the SC treatment group. SC showed favorable effects on anti‐inflammatory and vascular calcification biomarkers compared to CA treatment in patients with CKD stages 3 and 4 with normal phosphorous values.
Purpose: Prior literature shows that survival of waitlist patients is improved on axial continuous flow left ventricular assist devices (CF-LVAD). This study attempts to generate a risk prediction model for survival using the UNOS database population. Methods: UNOS database was queried to extract patients (≥ 18 years of age) listed for heart transplantation between 2010 and 2015 with an axial CF-LVAD (Heartmate II(HMII)) while on the waiting list. The multivariate model was used to predict the probability of survival at 3,6 and 12 months after listing. Patients were divided into derivation (80%) and validation (20%) groups. Derivation group was used to develop the multivariate model and validation group was used for model validation. The model accuracy was assessed using Receiver Operating Characteristics (ROC) curves and Area Under Curves (AUCs). Kaplan Meier survival curves were generated to show the impact of different risk factors on waiting list survival. All the analysis was performed using MATLAB software from the MathWorks, Inc. Results: Significant risk factors on multivariate analyses were diabetes type1 (HR = 2.5,p=0.018), presence of inotropes (HR = 1.6,p=0.005), creatinine at listing (HR = 1.2,p=0.00016). No significant differences were observed between the derivation and validation groups for all variables. The ROC curves generated using these risk factors showed AUC at 3, 6 and 12 months on the wait list of 0.7, 0.65, 0.63 respectively in the training set and 0.71, 0.65, 0.6 respectively in the validation set (figure 1). Survival analyses showed that patients implanted with HMII before listing had a better survival than those who did after being on the wait list (p-value <0.001, HR = 0.259) Conclusion: This is the first time a risk prediction model has been generated for wait list survival of HMII patients. A significant difference in survival was noted between patients who received their HMII prior to listing versus those who had it while waiting on the list.
Objective:The pharmacokinetic implications of direct-acting antiviral (DAA) use on tacrolimus posttransplant are unknown. This study sought to investigate the effects of glecaprevir/pibrentasvir (G/P), a CYP3A4 substrate and inhibitor, on weight-adjusted tacrolimus (FK) trough/dose ratio (T/D) following heart or kidney transplantation. Material and methods:This was a single-center, retrospective analysis of hepatitis C virus (HCV) viremic donors to HCV negative heart or kidney transplant recipients who received 12 weeks of G/P therapy. Weight-adjusted T/D was assessed while patients were at steady-state before, during, and after G/P treatment. Forty-one HCV negative recipients (three heart, 38 kidney) were evaluated. Results:The weight-adjusted T/D significantly increased during G/P treatment (119.31, IQR 88-173.8) compared to before G/P treatment (67.4, IQR 53.4-115.9) (p < 0.01), but decreased after completion of treatment (90.1, IQR 52.9-122.7) (p < 0.01). There was no difference in weight-adjusted T/D before and after G/P treatment (p = 0.42). Four patients experienced acute rejection. Conclusion:Initiation of G/P in heart or kidney transplant recipients induces a reversible change in tacrolimus metabolism. A 33%-50% tacrolimus dose reduction may be considered at the time of G/P initiation. Regardless of tacrolimus dose adjustment, tacrolimus trough levels should be monitored 3 days after initiation of G/P. No clear relationship between HCV viremic organ transplantation and rejection risk was found. Larger studies are warranted to validate these findings
Background:Vitamin D deficiency has been associated with a multitude of diseases, ranging from fractures to cancer. Nearly 99% of vitamin D metabolites are bound to proteins, altering the relationship between concentration and activity.Methods & results:Normalized concentrations were calculated and validated using published data regarding the correlation of 25-hydroxyvitamin D with bone mineral density. In addition, healthy and kidney disease subjects were recruited for preliminary investigations. Use of the normalizing equations resulted in statistically significant improvements in the relationship between vitamin D metabolites and several markers of health status.Conclusion:Normalized concentrations are similar to clinically reported values and are easier to interpret than free or bioavailable concentrations, since their values match the range of measured total concentrations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.