Renal Failure最新文献

Introduction: Predicting the outcome of a kidney transplant involving a living donor advances donor decision-making donors for clinicians and patients. However, the discriminative or calibration capacity of the currently employed models are limited. We set out to apply artificial intelligence (AI) algorithms to create a highly predictive risk stratification indicator, applicable to the UK's transplant selection process.

Methodology: Pre-transplant characteristics from 12,661 live-donor kidney transplants (performed between 2007 and 2022) from the United Kingdom Transplant Registry database were analyzed. The transplants were randomly divided into training (70%) and validation (30%) sets. Death-censored graft survival was the primary performance indicator. We experimented with four machine learning (ML) models assessed for calibration and discrimination [integrated Brier score (IBS) and Harrell's concordance index]. We assessed the potential clinical utility using decision curve analysis.

Results: XGBoost demonstrated the best discriminative performance for survival (area under the curve = 0.73, 0.74, and 0.75 at 3, 7, and 10 years post-transplant, respectively). The concordance index was 0.72. The calibration process was adequate, as evidenced by the IBS score of 0.09.

Conclusion: By evaluating possible donor-recipient pairs based on graft survival, the AI-based UK Live-Donor Kidney Transplant Outcome Prediction has the potential to enhance choices for the best live-donor selection. This methodology may improve the outcomes of kidney paired exchange schemes. In general terms we show how the new AI and ML tools can have a role in developing effective and equitable healthcare.

Long-term exposure to ambient air pollution is a recognized environmental risk factor for chronic kidney disease (CKD), but its dynamic effects on kidney function remain incompletely understood. This nationwide longitudinal study included 5,306 participants from the China Health and Retirement Longitudinal Study (CHARLS) to examine associations between five major air pollutants (PM₁, PM_2.5, PM₁₀, NO₂, and O₃) and kidney function decline, measured by the annual slope of estimated glomerular filtration rate (eGFR). Air pollutant exposures were assessed both as continuous variables and dichotomized by median levels. Higher exposure to PM₁, PM_2.5, PM₁₀, and NO₂ was consistently associated with faster eGFR decline. In fully adjusted models, each 1 μg/m³ increase in PM_2.5 corresponded to a steeper decline in eGFR (β = -0.02; 95% CI: -0.03 to -0.02), while participants in high PM_2.5 areas had an annual decline of -0.51 mL/min/1.73 m² (95% CI: -0.72 to -0.31). O₃ showed a significant association only in binary models. Weighted quantile sum regression identified PM_2.5 and PM₁ as dominant contributors. A favorable lifestyle markedly mitigated pollution-related decline; under high PM₁ exposure, eGFR declined by -0.69 (95% CI: -1.06 to -0.33) in those with favorable lifestyles versus -2.20 (95% CI: -2.65 to -1.75) in those with unfavorable lifestyles. These findings were robust across multiple sensitivity analyses. These findings emphasize the adverse impact of long-term air pollution exposure on kidney function and suggest that healthy lifestyle behaviors may offer significant protective benefits.

The urotensin II (UII) system comprises UII, UII-related peptide (URP), and their shared receptor UT. Bioactive UII can be generated from its precursor, prepro-UII, through proteolytic cleavage by the serine protease furin. The kidney serves as a significant source of UII, with elevated levels reported in infants with chronic kidney disease. Here, we investigated the contribution of the UII system to the loss of kidney function during ischemia-reperfusion (IR)-induced acute kidney injury (AKI) in neonatal pigs. Intra-arterial renal infusion of porcine UII reduced renal blood flow and increased vascular resistance, effects reversed by the UT antagonist urantide. Although IR did not alter whole-kidney UT expression, it increased furin, UII, URP, and vascular UT levels. Urantide attenuated IR-induced kidney hypoperfusion, elevations in AKI biomarkers and circulating cytokines, and histological kidney injury. In primary neonatal pig proximal tubule epithelial cells (PTECs), chemical IR (cIR), modeled by 1 h of ischemia (ATP-, glucose-, and serum-depleted medium) followed by reperfusion (restoration of complete medium), elevated furin and UII production. The furin inhibitor SSM 3 trifluoroacetate (SSM 3) suppressed cIR-induced UII synthesis. Moreover, both urantide and SSM 3 mitigated cIR-induced PTEC injury. These findings suggest that in neonatal pigs: (1) renal IR upregulates furin, UII, and URP in kidney tissue and UT in the microvasculature, (2) furin promotes UII biosynthesis in renal epithelial cells, and (3) UT inhibition protects against ischemic AKI.

Background: Inflammation is a key contributor to contrast-induced acute kidney injury (CI-AKI), yet its predictive role remains unclear. The systemic immune-inflammation index (SII) is a novel inflammatory biomarker, but its association with CI-AKI risk in coronary artery disease (CAD) patients undergoing coronary angiography is not well established. This study aimed to evaluate the relationship between preoperative SII and CI-AKI in a large multicenter cohort.

Methods: This retrospective cohort study analyzed CAD patients from five tertiary hospitals in China (2007-2020). Patients were stratified into SII tertiles, and multivariable logistic regression, restricted cubic splines (RCS), and two-piecewise logistic regression models were employed to assess the association between SII and CI-AKI risk.

Results: Among 30,822 patients, 3,246 (10.5%) developed CI-AKI. Higher preoperative SII levels were associated with increased CI-AKI risk ([SII-M vs. SII-L]: OR = 1.22, 95% CI [1.09-1.36], p = 0.001; [SII-H vs. SII-L]: OR = 1.70, 95% CI [1.53-1.90], p < 0.001). RCS analysis demonstrated a nonlinear relationship (p for nonlinearity = 0.008). The inflection point was at 19.12 × 10¹¹/L. Below this inflection point, each 100-unit increase in SII correlated with a 5% higher CI-AKI risk (OR = 1.05, 95% CI [1.04-1.06], p < 0.001), while no significant association was observed above this level.

Conclusion: Preoperative SII may be an independent predictor of CI-AKI risk in CAD patients undergoing undergoing coronary angiography, demonstrating a nonlinear dose-response relationship with a significant threshold effect. These findings suggest that SII may serve as a useful biomarker for early CI-AKI risk stratification in clinical practice.

Background: Observational studies suggest a correlation between mitochondrial DNA copy number (mtDNA-CN) and renal function; however, the causality remains uncertain. This study employed a two-sample bidirectional Mendelian randomization (MR) analysis to investigate the genetic causal relationship between mtDNA-CN and renal function. Methods: Genome-wide association study (GWAS) data for mtDNA-CN were obtained from the UK Biobank (n = 395,718), with renal function data primarily sourced from the CKDGen consortium and FinnGen studies. Four MR methods were employed, using inverse variance weighting as the primary approach, complemented by weighted median, MR Egger, and MR-PRESSO for sensitivity analyses. Multivariable MR (MVMR) assessed result robustness. Reverse MR treated renal function as the exposure. Validation was performed using additional mtDNA-CN GWAS data from the CHARGE UK Biobank (n = 465,809). Results: Forward MR analysis demonstrated a positive association between genetically predicted mtDNA-CN and estimated glomerular filtration rate (eGFR) [odds ratio (OR) = 1.007, 95% CI 1.003-1.012, p = 0.003]. MVMR suggested weaker evidence after adjusting for neutrophil count. Reverse MR revealed causal associations of urinary albumin-creatinine ratio (OR = 0.958, 0.923-0.994, p = 0.023) and microalbuminuria (OR = 0.981, 0.965-0.997, p = 0.021) with mtDNA-CN, though these effects were non-significant after multiple testing correction. Sensitivity and validation analyses confirmed robust. The findings from validation analyses were consistent. Conclusion: Our study suggests a potential causal association between mtDNA-CN and eGFR. However, the impact of confounding factors and the absence of consistent associations with other renal function markers underscore the necessity for further research to clarify the role of mtDNA-CN in renal function.

Background: Patients with chronic kidney disease (CKD) are at a high risk of cardiovascular disease. This study aims to observe the short-term changes of left ventricular (LV) myocardial work in stage 5 CKD patients with successful kidney transplantation (KT).

Methods: 45 stage 5 CKD patients who are candidates for KT were enrolled. Changes in clinical variables, laboratory data, routine transthoracic echocardiography, and noninvasive myocardial work (NIMW) were analyzed at pre-KT, 10 days, and 3 months post-KT. NIMW parameters include global myocardial work index (GWI), global constructive work (GCW), global wasted work (GWW), and global work efficiency (GWE).

Results: 1) Renal function indicators, including blood urea nitrogen, serum creatinine, and estimated glomerular filtration rate improved significantly at 10 days post-KT. At 3 months post-KT, there appears to be a continuing recovery trend; 2) GWE, GWI, and GCW were significantly increased at 3 months post-KT, but GCW and GWI with an early decrease at 10 days post-KT; 3) At the 10 days post-KT, the changes in systolic blood pressure and hemoglobin were positively correlated with the changes in GWI. Meanwhile, the change in systolic blood pressure was also positively correlated with the change in GCW. The change in diastolic blood pressure was positively correlated with the change in GWW.

Conclusion: LV systolic function doesn't improve in parallel with renal function after a successful KT. Steadily controlling blood pressure and correcting anemia is associated with improving myocardial work after KT, especially in the early post-transplant period.

Purpose: This study aims to investigate the protective effect of baicalin on sepsis-associated acute kidney injury (SA-AKI) and its molecular mechanism.

Materials and methods: An SA-AKI mouse model was established via lipopolysaccharide (LPS) injection. Baicalin's effects on renal function, oxidative stress, and apoptosis were evaluated using histopathology, dihydroethidium, and terminal deoxynucleotidyl transferase dUTP nick end labeling staining. Bioinformatics, molecular docking, ribonucleic acid (RNA) sequencing, and Western blotting were employed to investigate the role of baicalin in regulating the peroxisome proliferator‑activated receptor‑γ (PPAR-γ)/uncoupling protein 1 (UCP1) pathway. Human kidney-2 cells were used for in vitro validation.

Results: In this study, baicalin significantly ameliorated LPS-induced acute kidney injury by modulating the PPAR-γ/UCP1 signaling pathway. Both in vivo and in vitro experiments revealed that baicalin attenuates inflammation, oxidative stress, and apoptosis while restoring mitochondrial function. RNA sequencing analysis revealed significant upregulation of PPAR-γ/UCP1 in the baicalin-treated group. Further molecular docking and molecular dynamics simulations confirmed a stable interaction between baicalin and UCP1. Validation via small interfering RNA-mediated knockdown of PPAR-γ and UCP1 revealed that inhibition of the PPAR-γ/UCP1 pathway abrogated baicalin's protective effects, highlighting the critical role of this pathway in mediating baicalin's renoprotection.

Conclusion: Baicalin protects against SA-AKI by activating the PPAR-γ/UCP1 signaling pathway. This study provides new insights into the mechanisms through which baicalin mitigates kidney injury in sepsis, suggesting its potential as a therapeutic agent for SA-AKI.

Background: Systematic reviews and meta-analyses play a pivotal role in evidence-based medicine, including nephrology, by consolidating findings from multiple studies. To maximize their utility, rigorous quality assessment during peer review is essential. Challenges such as heterogeneity, bias, and methodological flaws often undermine these studies, necessitating a structured appraisal process.

Methods: This guide outlines a framework for nephrologists on appraising systematic reviews and meta-analyses. Key areas include heterogeneity assessment using the I² statistic, interpretation of forest plots for pooled effect estimates, and the use of funnel plots with Egger's test to identify potential publication bias. Risk of bias is evaluated using RoB 2 for randomized controlled trials and ROBINS-I for non-randomized studies. Subgroup and sensitivity analyses, along with meta-regression, address heterogeneity and examine the robustness of findings.

Results: The I² statistic quantifies heterogeneity by estimating the proportion of variability in a meta-analysis. Funnel plots and Egger's test help detect publication bias. Major biases, such as selection, performance, detection, and publication bias, are identified using structured tools like AMSTAR 2, Cochrane RoB 2, and ROBINS-I. The GRADE framework further assesses the overall certainty of the evidence. Emphasis is placed on PRISMA compliance, protocol pre-registration, and transparent reporting of statistical analyses, subgroup, and sensitivity assessments. The inclusion of grey literature remains optional.

Conclusion: By focusing on key areas such as heterogeneity, risk of bias, and robust statistical methods, this guide enables nephrologists to critically appraise systematic reviews and meta-analyses, fostering better clinical decision-making and improved patient care in nephrology.

The independent and domain-specific associations between physical activity (PA) and chronic kidney disease (CKD) remain underexplored. This study investigates the relationships between leisure-time, occupational, and transportation-related PA, along with sedentary behavior, and CKD prevalence in a nationally representative U.S. adult cohort. We analyzed 24,950 participants from the National Health and Nutrition Examination Survey (NHANES) 1999-2012. PA and sedentary behavior were assessed via validated questionnaires. Participants were classified based on adherence to physical activity guidelines (≥150 min/week). Multivariable logistic regression and restricted cubic splines were used to evaluate dose-response and non-linear associations. We found that meeting PA guidelines for total, leisure-time, and occupational PA was independently associated with lower odds of CKD (OR [95% CI]: 0.82 [0.73-0.93], 0.86 [0.76-0.97], and 0.85 [0.76-0.96], respectively). No significant association was observed for transportation-related PA. Sedentary behavior exceeding 6 h/day was associated with higher CKD prevalence. These associations were more pronounced in women, and dose-response patterns were evident across PA domains. This large-scale cross-sectional study identifies robust, domain-specific inverse associations between PA and CKD prevalence, particularly among women. Findings support stratified behavioral interventions targeting leisure and occupational activity domains, alongside sedentary behavior reduction, to mitigate CKD burden. Prospective studies are warranted to confirm causal pathways.

Background: In patients with end-stage renal disease (ESRD), vascular calcification significantly impairs hemodialysis (HD) vascular access functionality, compromising both dialysis efficacy and long-term patency. Early risk prediction of vascular calcification facilitates timely clinical interventions to preserve vascular access integrity.

Methods: A cross-sectional analysis was performed. Risk factors for vascular calcification in CKD patients were identified from the literature and Kidney Disease: Improving Global Outcomes guidelines. All variable selection and model training procedures were conducted on the training set. Univariate logistic regression was performed for all candidate variables. A nomogram was then constructed based on the final multivariate logistic model to facilitate clinical interpretation.

Result: A total of 136 HD patients were included. The predictive model, relying on arteriovenous (AV) access usage time, hip circumference, and diabetes status, is reliable and clinically actionable tool for predicting AV access calcification. Its robust performance across validation and subgroup analyses supports its potential for integration into routine clinical practice.

Conclusion: This study developed a nomogram-based predictive model for calcification, providing a simple, cost-effective, and reliable tool for early risk assessment. Monitoring hip circumference may serve as a practical approach for identifying high-risk patients, allowing for timely intervention and improved vascular access outcomes.