Renal Failure最新文献

Acute kidney injury (AKI) is a heterogeneous syndrome in which conventional stratification based on serum creatinine and urine output may fail to capture the full spectrum of underlying metabolic disturbances. In a retrospective cohort study of hospitalized adults with AKI admitted to Hospital General de Mazatlán between January 2022 and July 2025, we sought to identify biochemical phenotypes associated with major adverse kidney events (MAKE). Demographic, clinical, and biochemical variables, including urea, creatinine, calcium, phosphorus, potassium, hemoglobin, albumin, and pH, were standardized using z-scores and clustered using k-means analysis. The primary outcome was MAKE, defined as in-hospital mortality or new requirement for kidney replacement therapy (KRT). Among 797 patients, three distinct biochemical phenotypes were identified: Phenotype 1, characterized by relatively preserved biochemical parameters; Phenotype 2, defined by anemia and hypocalcemia; and Phenotype 3, marked by severe metabolic derangements. Phenotype 3 exhibited the most severe kidney dysfunction and metabolic instability, including anemia, hyperkalemia, hyperphosphatemia, hypocalcemia, and acidosis, and was strongly associated with MAKE (odds ratio [OR] 3.39, 95% confidence interval [CI] 2.12-5.40; p < 0.001), in-hospital mortality (OR 2.47, 95% CI 1.48-4.12; p < 0.001), and initiation of KRT (OR 5.80, 95% CI 1.60-21.12; p = 0.007). Phenotype 2 was more frequently observed in women and was associated with AKI stage 3, gastrointestinal bleeding, and malignancy, but was not independently associated with MAKE. Biochemical phenotyping identified clinically meaningful AKI subgroups and highlighted a high-risk phenotype characterized by profound metabolic instability and adverse kidney outcomes.

This Bayesian network meta-analysis evaluated the efficacy and safety of six prolyl hydroxylase inhibitors (PHIs) versus erythropoiesis-stimulating agents (ESAs) or placebo for chronic kidney disease (CKD) anemia. Electronic databases were searched through 1 May 2025. The prespecified primary outcome was change in hemoglobin, while secondary outcomes included iron metabolism indices (serum iron, transferrin saturation [TSAT], ferritin, hepcidin) and overall composite adverse events (AEs). Surface under the cumulative ranking curve (SUCRA) was used for ranking. Forty-six randomized controlled trials with 32,305 patients were included. In non-dialysis CKD (ND-CKD), roxadustat yielded the greatest hemoglobin rise (MD = 1.21 g/dL, 95% CI: 0.72-1.71; SUCRA = 88.6%) versus placebo and ESA. In dialysis CKD (D-CKD), roxadustat again ranked the highest (MD = 1.78 g/dL, 95% CI: 1.32-2.24; SUCRA = 86.2%) versus ESA and other PHIs. For TSAT, ESA ranked best in ND-CKD (MD = 5.24%, 95% CI: 1.16-9.32), while daprodustat led in D-CKD (MD = 3.07%, 95% CI: 0.22-5.91). Roxadustat improved serum iron in D-CKD (MD = 6.19 μg/dL, 95% CI: 2.81-9.58), and vadadustat and roxadustat reduced hepcidin in ND-CKD. Consistency assessment revealed no statistically significant heterogeneity/inconsistency between direct/indirect comparisons, supporting the robustness of the results. Regarding safety, ESA had the lowest AE risk in ND-CKD (OR = 0.85, 95% CI: 0.74-0.98), while roxadustat ranked lowest (SUCRA = 18.4%). Roxadustat demonstrated the strongest efficacy in hemoglobin improvement but higher AE incidence in ND-CKD, whereas ESA and daprodustat showed safety and iron metabolism benefits, supporting individualized therapy for renal anemia.Registration number: PROSPERO (CRD420251066181).

The interplay between macro-microcirculatory dysfunction and sepsis associated acute kidney injury (SA-AKI) remains elusive. This study aimed to explore the association between hemodynamics and endothelial damage in SA-AKI by evaluating the combined predictive value of renal resistive index (RRI) and plasma syndecan-1. This prospective observational study enrolled 80 septic patients admitted to the general intensive care unit (ICU) of a tertiary hospital from May to December 2024. Plasma syndecan-1 levels were measured at admission, and RRI was assessed within 24 h of ICU admission. Univariate and multivariate logistic regression models were applied to identify independent risk factors of SA-AKI. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis by calculating the area under the curve (AUC). Among 80 septic patients, 41(51.25%) developed AKI. Syndecan-1 levels were significantly higher in the AKI group [109.95 (73.67-221.40) vs.73.67 (54.59-109.95) ng/mL, p = 0.007], and RRI values were markedly elevated (0.69 ± 0.08 vs. 0.60 ± 0.06, p < 0.001) compared to non-AKI patients. Univariate analysis revealed syndecan-1 (OR = 2.68, 95%CI 1.29-5.59) and RRI (OR = 1.18, 95%CI 1.09-1.28) as predictors of AKI. In multivariate models adjusted for confounders, both plasma syndecan-1 (OR = 3.57, 95%CI 1.01-12.64, p = 0.048) and RRI (OR = 1.19, 95% CI 1.07-1.33, p = 0.002) retained significance. A predictive model using a combination of plasma syndecan-1 and RRI achieved superior diagnostic performance (AUC 0.859, sensitivity 87.8%, specificity 92.3%). In patients with SA-AKI, elevated plasma syndecan-1 and RRI were identified as independent risk factors. The combination of syndecan-1 and RRI can serve as synergistic biomarkers for the prediction of SA-AKI.

Minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS) are two key nephrotic syndrome types with significant clinical implications. MCD predominantly affects children, while FSGS is more common in adults, often leading to irreversible kidney dysfunction. Despite shared features like podocyte injury and immune dysregulation, their pathological and clinical presentations differ. Understanding gene expression changes in these diseases could reveal new therapeutic targets. Single-cell transcriptomic datasets (GSE213030 and GSE176465) were analyzed to investigate cellular interactions in MCD and FSGS. Machine learning algorithms developed diagnostic models, and immune subtypes were identified for detailed subtype analysis. Key genes were validated using qRT-PCR and immunohistochemical staining in a mouse model, focusing on their association with M1 macrophage activation. Integrated single-cell analysis identified six key genes (PTPRC, ACTR2, MYO1F, UBB, CSF1R, and LYN) central to macrophage activation. These genes were closely linked to M1 macrophage activation, as confirmed through transcriptomic profiling and spatial co-expression patterns in Sprague-Dawley (SD) rat models. Machine learning models validated their predictive value in disease progression from MCD to FSGS. This study highlights six hub genes as potential biomarkers for predicting MCD-to-FSGS progression. Their roles in macrophage activation suggest these genes may serve as novel therapeutic targets for personalized treatment strategies, particularly for patients at high risk of disease transition.

Background: Arteriovenous (AV) access, an essential component of dialysis treatment, has been implicated in the development of cardiovascular abnormalities. However, whether AV access blood flow and the duration of exposure to this flow, as represented by the dialysis vintage, have independent or interactive effects on cardiac outcomes remains unclear.

Methods: In this multicenter cross-sectional study, we enrolled hemodialysis patients who had undergone both transthoracic echocardiography and measurement of AV access flow, between April 2014 and January 2024. Left ventricular mass index (LVMI) was used as a surrogate marker of cardiovascular morbidity. AV access flow was quantified as brachial artery flow volume (FV) using pulsed Doppler ultrasonography. Multivariate regression models were applied to investigate the associations of FV and dialysis vintage with LVMI, and to assess potential interactions between these variables.

Results: A total of 241 patients were included. The mean FV was 0.71 ± 0.29 L/min, and the median dialysis vintage was 5.0 years (interquartile range, 3.0-11.0 years). Higher FV was significantly associated with increased LVMI (mean difference = 22.83; 95% confidence interval [CI]: 0.37 to 45.29; p = 0.046), whereas dialysis vintage was not (mean difference = 0.51; 95% CI: -0.41 to 1.45; p = 0.27). Moreover, no statistically significant interaction was observed (mean difference = 0.13; 95% CI: -3.14 to 3.40; p = 0.94).

Conclusion: AV access flow may serve as a candidate variable in future left ventricular hypertrophy prediction algorithms and cardio-renal machine learning models because of its linear and independently significant association with LVMI.

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are widely used in patients with chronic kidney disease (CKD), but existing evidence regarding their efficacy and safety remains inconsistent. To evaluate the cardiorenal outcomes and adverse effects of GLP-1 RAs in this population, we conducted a systematic review and meta-analysis of randomized controlled trials from PubMed, Embase, Cochrane Central Register of Controlled Trials, and Web of Science up to December 2024. Nine trials involving 21,717 patients, the vast majority of whom had T2DM, were included. GLP-1RAs treatment for CKD was associated with decreasing the incidence of major adverse kidney events (MAKE; RR, 0.84; 95% CI, 0.76-0.94) and major adverse cardiac and cerebrovascular events (MACE; RR, 0.84; 95% CI, 0.72-0.97), reducing all-cause mortality (RR, 0.83; 95% CI, 0.76-0.90) and albuminuria level (SMD, -1.22; 95% CI, -1.53 - 0.90). Gastrointestinal events associated with GLP-1 RA treatments including nausea (RR, 4.14; 95% CI, 2.70-6.33), vomiting (RR, 3.05; 95% CI, 1.88-4.97), diarrhea (RR, 2.65; 95% CI, 1.76-3.98), and dyspepsia (RR, 3.79; 95% CI, 1.02-14.12) have garnered significant attention. In conclusion, administration of GLP-1RAs treatment demonstrates excellent cardiorenal protective effects in CKD, primarily in patients with co-existing T2DM, though with notable gastrointestinal concerns.

Kidney stone disease is a major global health burden with high recurrence, closely linked to oxidative stress. While iron, a redox-active metal, can exacerbate oxidative stress via the Fenton reaction, population evidence on its association with kidney stone risk is scarce. Based on data from 4,370 adults in the National Health and Nutrition Examination Survey (NHANES 2017-2018), we conducted survey-weighted multivariable logistic regression to assess the associations between iron status indicators and kidney stone risk, and used restricted cubic splines to examine potential dose-response relationships. Animal tissues were analyzed via IHC, Western blot, and biochemical assays. After adjustment, each 10% increase in transferrin saturation correlated with a 26% lower likelihood of kidney stones (odds ratio [OR] 0.74, 95% confidence interval [CI] 0.56-0.97, p = .04), while each 10 mg/day increase in dietary iron intake correlated with a 12% higher risk (OR 1.12, 95% CI 1.01-1.24, p = .036). Dose-response analysis revealed a U-shaped relationship for iron intake (inflection point: 11.7 mg/day). Animal experiments confirmed renal iron accumulation, elevated sTfR, and activated ferroptosis. This study first demonstrates a significant association between dysregulated iron metabolism and kidney stone risk, suggesting that systemic iron dysregulation and local renal ferroptosis may contribute to stone pathogenesis, offering new preventive insights.

Objectives: Kidney transplantation remains the gold standard for end-stage renal disease, yet long-term graft survival is limited by acute and chronic rejection. Emerging evidence highlights the critical role of immunometabolism, the bidirectional relationship between alloimmunity and metabolic dysregulation, specifically in the context of post-transplant diabetes mellitus (PTDM). This study investigates whether the expression of genes traditionally associated with diabetes susceptibility can predict kidney transplant rejection.

Methods: We performed a transcriptomic reanalysis of a publicly available dataset (GSE49198) comprising 596 peripheral blood samples from kidney transplant recipients. A panel of 13 candidate genes (INSR, CAT, TNF, MMP2, TGFB1, VEGFA, IGF1, PPARG, PPARGC1A, HLA-DQB1, CTLA4, ABCA1, DPP4) was selected based on prior domain knowledge. Patients were stratified into a High-Risk group (Acute and Chronic Rejection, n = 95) and a Low-Risk group (Stable, Tolerant, Minimal Immunosuppression, n = 439). Statistical analysis included Mann-Whitney U tests with Bonferroni correction, Spearman's rank correlation, hierarchical clustering, and 3D Principal Component Analysis (PCA).

Results: Three genes (PPARG, INSR, and DPP4) showed statistically significant differential expression between High-Risk and Low-Risk cohorts (p < 0.05, corrected). PPARG and INSR were upregulated in rejection, while DPP4 was downregulated. Inter-gene correlation analysis revealed low redundancy. 3D PCA revealed a topological distinction: Low-Risk patients formed a dense homeostatic cluster, whereas High-Risk patients exhibited vector space dispersion ('metabolic scattering').

Conclusions: We identified a distinct metabolic gene signature capable of predicting kidney transplant rejection. The downregulation of DPP4 with the upregulation of PPARG and INSR suggests that metabolic reprogramming and loss of homeostasis are hallmarks of immune-mediated graft failure.

Proactive safety evaluation of molecularly targeted therapies requires generalizable frameworks that integrate real-world evidence with mechanistic insights. As a case in point, tepotinib, a mesenchymal-epithelial transition (MET) inhibitor for non-small cell lung cancer, has a known pulmonary toxicity profile, but its link to acute kidney injury (AKI) and underlying mechanism remain unclear. We devised a tri-scale in silico strategy encompassing population-scale pharmacovigilance signal extraction from the FDA Adverse Event Reporting System (FAERS) (2020-2025) via disproportionality analysis (Reporting Odds Ratio, ROR, and Proportional Reporting Ratio, PRR), network toxicology-based multi-target exploration for shared target and hub gene identification, and mechanistic docking-based molecular plausibility assessment using the Cavity-detection guided Blind Docking (CB-Dock2) platform. Pharmacovigilance analysis identified a significant renal impairment signal (ROR = 20.60). Network toxicology suggested potential nephrotoxicity and revealed 173 shared targets and prioritizing six hub genes (HSP90AA1, AKT1, EGFR, CASP3, TNF, SRC). These genes were shown to be critically involved in PI3K-Akt and MAPK pathways. Molecular docking revealed high-affinity binding between tepotiniband all six hub targets (Vina scores: -8.0 to -10.6 kcal/mol), providing a structural basis for the postulated mechanistic link to AKI. These findings not only highlight the necessity for enhanced renal monitoring in tepotinib-treated patients but, more broadly, establish the FAERS-NetDock Pipeline as a reusable, generalizable and hypothesis-generating framework for evaluating tyrosine kinase inhibitors (TKIs)-induced nephrotoxicity; this framework is immediately applicable to profiling the safety of other TKIs (e.g. crizotinib, capmatinib, savolitinib, afatinib and osimertinib) and is readily adaptable for de-risking a wider spectrum of targeted therapies.

Chronic kidney disease (CKD) constitutes a significant global public health challenge, with emerging evidence suggesting that riboflavin may confer renoprotective effects. However, the association between dietary riboflavin intake and CKD risk remains inadequately elucidated. To investigate this, we analyzed National Health and Nutrition Examination Survey (NHANES) 2005-2018 datasets using weighted multivariate logistic regression, interaction testing, stratified subgroup analyses, and curve fitting. Additionally, network pharmacology and molecular docking simulations were employed to identify and validate potential therapeutic targets. Our results showed that patients with CKD exhibited significantly lower riboflavin intake than their non-CKD counterparts (1.98 vs. 2.21 mg/d, p < 0.001). After full adjustment, each 1 mg/d increment in riboflavin intake was associated with an 18.8% reduced risk of CKD (adjusted OR = 0.812, 95% CI: 0.686-0.962). Individuals in the highest intake quartile had a 42.7% lower risk compared to the lowest quartile (adjusted OR = 0.573, 95% CI: 0.400-0.822). A non-linear dose-response relationship was observed, characterized by an inflection point at 1.66 mg/d, indicating a more pronounced protective effect at lower intake levels. Mechanistic investigations suggested that riboflavin's benefits may be mediated through interactions with key targets like caspase-3 (CASP3), Erb-B2 receptor tyrosine kinase 2 (ERBB2), and matrix metallopeptidase 9 (MMP9), implicating apoptotic and metabolic pathways. In conclusion, dietary riboflavin intake is inversely associated with CKD risk, particularly at lower concentrations, and strategic augmentation of intake represents a promising dietary intervention for CKD prevention and management.