Background: Previous observational studies have shown that there is a controversial association between selenium levels and chronic kidney disease (CKD). Our aim was to assess the causal relationship between selenium levels and CKD using Mendelian randomization (MR) analysis. Methods: We used the two-sample Mendelian randomization (MR) method to analyze the causal role of selenium levels on CKD risk. The variants associated with selenium levels were extracted from a large genome-wide association study (GWAS) meta-analysis of circulating selenium levels (n = 5477) and toenail selenium levels (n = 4162) in the European population. Outcome data were from the largest GWAS meta-analysis of European-ancestry participants for kidney function to date. Inverse variance weighted (IVW) method was used as the main analysis and a series of sensitivity analyses were carried out to detect potential violations of MR assumptions. Results: The MR analysis results indicate that the genetically predicted selenium levels were associated with decreased estimated glomerular filtration (eGFR) (effect = −0.0042, 95% confidence interval [CI]: −0.0053–0.0031, p = 2.186 × 10⁻¹³) and increased blood urea nitrogen (BUN) (effect = 0.0029, 95% confidence interval [CI]: 0.0006–0.0052, p = 0.0136) with no pleiotropy detected. Conclusions: The MR study indicated that an increased level of selenium is a causative factor for kidney function impairment.

Background: The elevated calcium and phosphorus levels in patients undergoing hemodialysis may increase the risk of all-cause mortality. Paricalcitol, as a new vitamin D receptor activator (VDRA), seemed to be effective in reducing the calcium and phosphorus levels. Objectives: The aim of this study was to compare the efficacy and safety of paricalcitol with other VDRAs in patients undergoing hemodialysis. Methods: PubMed, Embase, and Web of Science database were systematically reviewed. Selection criteria: Studies that focused on the use of paricalcitol for hemodialysis patients were eligible for inclusion. Data collection and analysis: Two independent investigators performed the literature search, data extraction, and assessment of methodological quality. The outcomes were expressed with standard mean difference (SMD), HR, or risk ratio (RR) with 95% CI. Results: Thirteen studies involving 112,695 patients were included in this meta-analysis. Among these studies, four studies were cohort studies and nine studies were randomized controlled trials (RCTs). For cohort studies, they were regarded as being of high quality; for RCTs, only one was classified as being at low risk of bias; and the remaining eight studies were at being unclear risk of bias. Compared with other VDRAs, paricalcitol significantly improved the overall survival (HR =0.86, 95% CI: 0.80, 0.92; P<0.001) and reduced the intact parathyroid hormone (iPTH) (SMD =-0.53, 95% CI: -0.90, -0.17; P=0.004). Paricalcitol offered similar effect with other VDRAs in the control of calcium (SMD =0.32, 95% CI: -0.04, 0.67; P=0.078) and phosphorus (SMD =0.06, 95% CI: -0.26, 0.37; P=0.727) levels. However, the serum change in calcium phosphate product was greater in the paricalcitol group than in the other VDRA group (SMD =2.13, 95% CI: 0.19, 4.07; P=0.031). There was no significant difference in the incidence of adverse events between the two groups (RR =1.02, 95% CI: 0.93, 1.12; P=0.674). Conclusion: Paricalcitol was crucial in reducing the mortality in patients undergoing hemodialysis. Moreover, both paricalcitol and other VDRAs were effective in control of the serum iPTH, calcium, and phosphorus levels. Given the potential limitations in this study, more prospective large-scale, well-conducted RCTs are needed to confirm these findings.

Background: Peritoneal dialysis-related peritonitis (PDRP) is one of the most common complications of peritoneal dialysis (PD). Understanding the risk factors and etiological characteristics is indispensable for infection prevention and improving the outcome and life quality.Methods: A total of 70 PD patients were separated into the PDRP group (n=25) and the control group (n=45). Variables, including gender, age, body mass index, primary diseases, and history of basic diseases, in the two groups were analyzed to assess the risk factors of PDRP. Metagenomic next-generation sequencing (mNGS) and microbial culture were compared in detecting pathogenic microorganisms. Gut microbiota analysis was performed in 35 PDRP patients based on mNGS data.Results: Dialysis time and times of dialysate change were the risk factors of PDRP, and times of dialysate change was the independent risk factor of PDRP (p = 0.046). mNGS produced higher sensitivity (65.79%) than microbial culture (36.84%) in identifying pathogenic microorganisms. Staphylococcus aureus and Klebsiella pneumoniae (four cases) were the most frequent pathogens causing PDRP, followed by Staphylococcus capitis (three cases). β diversity of the gut microbiota was significantly different between patients with fewer times of dialysate change (≤4) and more (>5), as well as between patients with gram-positive (G+) bacterial and gram-negative (G−) bacterial infection.Conclusion: The dialysis time and times of dialysate changes not only are risk factors for peritonitis in PD patients but also stimulate significant changes in the gut microbiome structure in PDRP patients. These findings may provide a novel viewpoint for the management of patients with PDRP.