This study aims to evaluate the impact of COVID-19 on the progression of CKD in non-dialysis patients and its relation to clinical outcomes in Palestine.

We conducted a retrospective cohort study that followed non-dialysis CKD patients receiving treatment at outpatient clinics in governmental hospitals. Out of the 248 CKD patients who met the inclusion criteria, 98 were diagnosed with COVID-19 between March 2020 and March 2022. We collected data at three distinct time intervals, both prior to and after their COVID-19 infection. We examined the decline in eGFR and gathered demographic information, hospitalization, and mortality rates. The drop in eGFR was recorded 15 months from baseline.

The mean age of the patients was 55 years, with 55.6% being male. Patients diagnosed with COVID-19 faced a significantly higher risk of rapid deterioration in eGFR, with a 3.7-fold increase compared to those without COVID-19 (ap-value: <0.001; aOR: 3.7; 95% CI: 2.1-6.3). Additionally, COVID-19 patients had 4.4 times higher mortality rates (ap-value: 0.005; aOR: 4.4; 95% CI: 1.6-12.4), 13.3 times higher rates of dialysis initiation within 15 months post-baseline (ap-value: <0.001; aOR: 13.3; 95% CI: 6.1-28.7), and 3.5 times higher rates of hospital admissions (ap-value: <0.001; aOR: 3.5; 95% CI: 1.8-6.7) compared to the COVID-19 negative group.

CKD patients who contract COVID-19 experience a more rapid decline in kidney function, leading to worse health outcomes, including increased mortality rates, a greater need for dialysis, and higher hospitalization rates.

It has been proved that glucagon-like peptide-1 receptor (GLP1R) agonists have positive effects on renal outcomes in diabetic patients. However, it remains unknown whether GLP1R agonists could provide similar protection against other kidney diseases.

We performed two-sample Mendelian randomization (MR) analyses to determine the causal effects of GLP1R agonists on multiple kidney diseases. Exposure to GLP1R agonist was proxied by the available cis-eQTLs for GLP1R. Primary outcomes included the risk assessment for diabetic nephropathy, IgA nephropathy, membranous nephropathy, nephrotic syndrome, chronic kidney disease, acute glomerulonephritis, chronic glomerulonephritis and calculus of kidney/ureter. Type 2 diabetes and body mass index were used as positive control. Two-stage network MR analyses were conducted to assess the mediation effect of inflammatory proteins on the relationships between GLP1R agonists and kidney diseases.

After meta-analyses of both discovery and validation cohorts, genetically proxied GLP1R agonist was found to significantly associated with a decreased risk of diabetic nephropathy (OR = 0.72, 95%CI = 0.54-0.97, p = 0.031) and IgA nephropathy (OR = 0.58, 95%CI = 0.36-0.94, p = 0.027). Two-stage network MR revealed that there was an indirect effect of GLP1R agonist on IgA nephropathy through signaling lymphocytic activation molecule family member 1 (SLAMF1), with a mediated proportion of 34.27% (95% CI, 1.47-67.03%, p = 0.041) of the total effect.

The findings of current study presented genetic proof for the potential protective effects of GLP1R agonists in the development of diabetic nephropathy and IgA nephropathy, offering a novel sight for future mechanistic and clinical applications.

Quality indicators (QIs) are essential for evaluating healthcare quality, but their validation for nondiabetic chronic kidney disease (CKD) populations is limited. We aimed to assess the association between QIs and outcomes in nondiabetic CKD patients. Using Taiwan's National Health Insurance claims data and death registries, we analyzed 27,842 nondiabetic adults with stage 3B-5 CKD from 2016 to 2019. Three QIs were assessed: renin-angiotensin system (RAS) inhibitor prescription, proteinuria testing, and nonsteroidal anti-inflammatory drug (NSAID) avoidance. Each patient received an overall QI score (range: 0-3) based on the sum of the individual QI scores. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between QI scores and outcomes, including long-term dialysis, all-cause death, hospitalization for acute kidney injury (AKI), hyperkalemia, and acidosis. The study population had a mean age of 68.7 years and a female prevalence of 41.7%. Only 33.5% of patients received the highest QI score. During a median follow-up period of 23 months, higher overall QI scores were associated with lower risks of long-term dialysis (HR 0.891, 95% CI 0.846-0.938), all-cause death (HR 0.900, 95% CI 0.864-0.939), and acidosis (HR 0.882, 95% CI 0.799-0.972). Notably, the prescription of RAS inhibitors was consistently correlated with better outcomes. These findings underscore the importance of quality indicators, particularly the continued use of RAS inhibitors, in improving outcomes for nondiabetic CKD patients. Future research should focus on refining existing QIs and expanding their validation to broader populations and healthcare settings.

Chronic kidney disease (CKD) is a growing global health challenge. As the disease progresses, it can lead to end-stage renal disease, necessitating dialysis or kidney transplantation. However, access to these life-saving treatments is often limited by geographic, financial, and resource constraints, underscoring the importance of public awareness and interest. This study examined global and U.S. search trends related to CKD and dialysis using Google Trends™ data from 2004 to 2024. Public search activity was measured using the Relative Search Interest (RSI) index, which ranges from 0 to 100. Both CKD and dialysis exhibited an upward trend in search activity worldwide and in the U.S., as indicated by a positive slope in linear regression analysis (all p < .0001), though some fluctuations and regional differences were observed. Pearson's correlation analysis demonstrated a strong relationship between the U.S. dialysis RSI scores from Google Trends and real-world dialysis incidence rates from the United States Renal Data System (USRDS) (r = 0.961, p < .0001). Notably, in 2020, search activity for both CKD and dialysis declined, likely due to disruptions caused by the COVID-19 pandemic. The study highlights the potential of Google Trends as a valuable tool for assessing public interest and awareness of kidney health, providing insights that can inform public health strategies and educational initiatives. However, relying solely on Google Trends data to assess public interest is insufficient, due to inherent limitations and biases. Findings derived from search trends should be interpreted with caution and ideally supplemented with additional research methodologies.

Chronic kidney and urinary tract diseases, including glomerulonephritis, nephrotic syndrome, and chronic kidney disease (CKD), present significant global health challenges. Recent studies suggest a complex interplay between infectious pathogens and immune-mediated kidney damage. This study employs Generalized Summary data-based Mendelian Randomization (GSMR) to explore causal relationships between pathogen-derived antibodies and major urinary and kidney diseases.We conducted a two-sample MR analysis using summary statistics from large-scale Genome-Wide Association Studies (GWAS) to assess associations between 46 pathogen-specific antibodies and seven urinary system diseases. We utilized robust statistical methods, including inverse variance weighting, to ascertain causal effects while controlling for potential confounders.Significant associations were identified between several pathogen-specific antibodies and disease risk. Notably, Epstein-Barr virus (EBNA-1) antibody levels were inversely associated with glomerulonephritis and nephrotic syndrome, indicating a potential protective effect. Conversely, Anti-Merkel cell polyomavirus IgG seropositivity was linked to increased risks of CKD and glomerulonephritis. Additionally, immune-mediated mechanisms were highlighted, with certain antibodies exhibiting dual roles as risk factors or protective agents.This study underscores the complex role of pathogen antibodies in the pathogenesis of kidney and urinary tract diseases, revealing significant implications for future research and potential therapeutic strategies. The findings advocate for further investigation into specific pathogen interactions with the immune system, aiming to inform targeted interventions.

Heart failure (HF) is a major complication in patients with end-stage renal disease (ESRD) and is the leading cause of death in this high-risk population. Sacubitril/Valsartan is an angiotensin receptor-neprilysin inhibitor (ARNI) that has been shown to improve treatment outcomes in patients with ESRD accompanied by HF. Unfortunately, in clinical practice, some patients who received sacubitril/valsartan treatment not only did not show a good therapeutic effect, but also got worse with the passage of time. To explore potential biomarkers for predicting the clinical efficacy of sacubitril/valsartan, serum samples were prospectively collected upon admission and again collected after sacubitril/valsartan treatment was completed. Patients were divided into good response group (GR) and poor response group (PR). At the same time, samples before treatment were divided into GR group and PR group by sample tracing and matching, and metabolomics analysis was conducted. In the end, a total of 9 different metabolites were identified between patients in the early GR and PR groups. In order to find more effective biomarkers, two algorithms, random forest (RF) and support vector machine (SVM), were used for metabolite selection and performance evaluation, and three kinds of Lysophosphatidylcholine (LysoPC) metabolites showed good predictive effect, and the expression of the enzyme phospholipase A2 group IVA (PLA2G4A), associated with this metabolite was significantly elevated in the PR group. The disordered metabolism may reduce the sensitivity of patients to sacubitril/valsartan treatment, and PLA2G4A targeted inhibitors may be a promising therapeutic strategy to improve the sensitivity of patients with ESRD and HF to sacubitril/valsartan treatment.

The modern diet contains a substantial level of fat which is believed to be one of the leading causes of the progression of kidney disease. Several studies have already demonstrated that consumption of a high-fat diet (HFD) induces inflammation and oxidative stress, causing activation of upstream mechanisms associated with kidney injury. For the prevention of such pathological events, a change in diet or the taking of nutritional supplements are recommended as alternative treatments. One of the forms of vitamin B6, pyridoxine (PN), has been shown to be an effective antioxidant and can also inhibit the formation of advanced-glycation end products (AGEs). In this study, the protective effects of PN (100 mg/kg/day for a period of eight weeks) against HFD-induced complications in obese rats were investigated. Rats fed on a HFD developed obesity which promoted inflammation, glucose intolerance, AGE receptor upregulation, oxidative stress, and kidney dysfunction. Intervention using PN mitigated obesity-related events and the impairment of kidney function by markedly reducing oxidative stress and also restoring the activity of antioxidant enzymes. Other studies have shown that some vitamin B6 derivatives inhibit the formation of AGEs but our study shows for the first time that PN exerted an antiglycative effect in this HFD-induced obesity model. Consequently, PN could potentially be a novel supplement for obese individuals to avoid kidney injury.

Cystinosis is a rare autosomal recessive lysosomal storage disorder characterized by the accumulation of cystine within lysosomes, leading to multi-systemic complications. The present study describes the case details (the presentation and management) of a 4-year-old female child diagnosed with infantile cystinosis, further complicated by distal renal tubular acidosis and stage 4 chronic kidney disease. The patient exhibited significant ocular manifestations, notably bilateral corneal cystine crystal deposits, observed as a shimmering effect under slit-lamp biomicroscopy and marked papilledema in both eyes. Fundoscopic examination also revealed retinal cystine deposits, indicating systemic involvement. The systemic complications included renal dysfunction requiring ongoing dialysis and bicarbonate supplementation to manage metabolic acidosis, as well as elevated intracranial pressure. Ophthalmological management focused on vision preservation through corrective lenses and topical cysteamine eye drops to reduce corneal cystine accumulation. Regular follow-up appointments were scheduled to monitor corneal clarity and optic nerve health. The case described herein underscores the complexity of cystinosis and the critical need for a multidisciplinary approach involving ophthalmology, nephrology, and neurology. Early diagnosis and timely therapeutic interventions are essential to mitigate the progressive nature of the disease and improve patient outcomes. The present case report also highlights the challenges in managing the condition, including treatment adherence and potential complications, and emphasizes the importance of continued research to develop more effective therapies and improve the quality of life for affected individuals.

Understanding the impact of psychosocial factors and pain management on cardiovascular disease (CVD) risk and life expectancy in patients with chronic kidney disease (CKD) is critical for developing targeted interventions. We aimed to assess the associations of social isolation, loneliness, and pain risk with incident CVD in patients with CKD and to evaluate the impact of these factors on the life expectancy of CKD patients.

This prospective cohort study comprised 34,381 CKD patients from the UK Biobank. Loneliness and social isolation were measured using two-item and three-item scales, respectively. The risk of pain spreading score (ROPS) was determined by summing responses to six items based on mood, trauma, sleep, neuroticism, and anthropometric measurement. The Cox proportional hazards regression model was used to evaluate CVD risk by estimating hazard ratios (HRs) and 95 % confidence intervals (CIs).

Higher levels of loneliness (HR2 vs. 0 = 1.32, 95 % CI = 1.22-1.44), social isolation (HR2+ vs. 0 = 1.11, 95 % CI = 1.04-1.19), and higher ROPS (HRhigh vs low risk = 1.34, 95 % CI = 1.28-1.40) were associated with a higher risk of CVD in CKD patients (P-trend<0.001 for all). Significant interactions between loneliness and ROPS were observed, suggesting a synergistic effect on CVD risk. Moreover, loneliness, social isolation, and elevated ROPS were significantly associated with reduced life expectancy among patients with CKD.

The study findings suggest that addressing social isolation and loneliness, along with effective pain management, is crucial for reducing the risk of CVD and improving life expectancy in patients with CKD.

Chronic kidney disease (CKD) and its progression to end-stage renal disease (ESRD) represent significant global health challenges, contributing to increased morbidity and mortality. Despite the potential diagnostic value of ATR-FTIR spectroscopic analysis of serum in CKD, research in this area remains limited. This study addressed this gap by aiming to explore the spectral profiles of sera obtained from hemodialysis patients and healthy controls. We investigated serum spectral profiles from 21 hemodialysis patients and 21 age/sex-matched controls using ATR-FTIR spectroscopy in the mid-infrared region (4000-400 cm-1). Spectroscopic analysis revealed elevated spectral intensity in ESRD samples compared to controls. Principal Component Analysis (PCA) successfully distinguished ESRD from control samples across multiple spectral regions (1480-900 cm-1, 1800-900 cm-1, and combined 3000-2800/1800-900 cm-1). Partial Least Squares Discriminant Analysis (PLS-DA) demonstrated enhanced group separation, with the optimized PLS model achieving perfect classification metrics (100% accuracy, sensitivity, and specificity). The combined spectral region models exhibited superior diagnostic performance compared to other regions. The analysis identified key molecular biomarkers associated with ESRD, including alterations in lipids, protein structures (represented by amide I and II bands), carbohydrates, nucleic acids, and immunoglobulins, which correlate with known biochemical changes in CKD pathophysiology. These findings demonstrate that ATR-FTIR spectroscopy with multivariate analysis is a rapid, cost-effective screening tool for CKD. The identified spectral biomarkers provide insights into disease-related biochemical alterations, adding valuable data to the research in this field.

Mitigation of adriamycin (ADR)-induced nephropathy remains a significant challenge in clinical management. Brain-targeted administration of losartan demonstrates comparable nephroprotective effects at a 1:500 concentration relative to gavage administration. This study established an exosome-based nano-delivery platform (ExoACP) to reduce drug dosage for alleviating ADR-induced nephropathy. The platform was rigorously tested for toxicity and blood-brain barrier penetration. Additionally, the role and possible mechanism of ExoACP-Los in alleviating ADR-induced nephropathy in mice were investigated. ExoACP showed enhanced penetration in brain microvascular endothelial cells, with a 7.20-fold increase in uptake. In the ADR model, ExoACP-Los exhibited anti-inflammatory and anti-fibrotic effects by downregulating the renin-angiotensin system, reducing extracellular matrix deposition by nearly half. These findings suggest ExoACP-Los can alleviate ADR-induced nephropathy by enhancing targeted drug delivery to the brain while reducing losartan. Overall, ExoACP holds significant potential for future clinical applications in chronic nephropathy.

Transcatheter aortic valve implantation (TAVI) is a proven treatment for severe aortic stenosis (AS); however, the effects of TAVI on central blood pressure (CBP) and clinical outcomes remain unclear. We assessed CBP indices before and after TAVI and their prognostic value. Seventy-six patients with severe AS who underwent TAVI were retrospectively evaluated, and CBP was estimated noninvasively 1 day before and after TAVI. The following indices were measured: augmentation index corrected for heart rate (HR) (AIx@HR75), peak pressure of the forward wave (Pf) and backward wave (Pb), time to peak pressure of the forward wave corrected for HR (Tfc) and the backward wave corrected for HR (Tbc), and ejection duration (ED). The primary endpoint was the composite outcome of all-cause mortality and hospitalized heart failure. The median follow-up period was 1135 (844-1404) days. Tfc, Tbc, ED, Pb, and AIx@HR75 decreased despite no significant changes in Pf after TAVI. The univariable Cox proportional hazards model showed that ED 1 day after TAVI was associated with composite outcomes (hazard ratio: 1.02; 95% confidence interval [CI]: 1.01-1.04; P = 0.002). When the patients were divided into two groups by the cutoff value determining composite outcomes by receiver operating characteristic curve analysis, a long ED 1 day after TAVI was significantly associated with composite outcomes by Kaplan-Meier curve analysis (log-rank test, P < 0.001). The multivariable Cox proportional hazards model showed that a long ED 1 day after TAVI was associated with composite outcomes (adjusted hazard ratio: 12.12; 95% CI 2.41-60.81; P = 0.002). In conclusion, a long ED 1 day after TAVI was associated with adverse clinical outcomes.

The American Heart Association recently released an updated algorithm for evaluating cardiovascular health (CVH), Life's Essential 8 (LE8). However, few studies have examined the association of LE8 with risk of cardiovascular disease (CVD) and mortality among individuals with chronic kidney disease (CKD). We investigated whether LE8 was associated with subsequent risk of CVD and mortality in the Chinese population of adults with CKD.

This prospective study included 18,716 adults (55.4 ± 14.0 years, 77.9 % men) with CKD free of CVD at baseline from the Kailuan study. A LE8 score (range 0-100 points) was constructed based on diet, physical activity, smoking, sleep duration, body mass index, blood lipids, blood glucose, and blood pressure. Incident CVD and mortality were identified by electronic health records and registers. Multivariable Cox regression models were used to compute hazard ratios (HRs) and 95 % confidence intervals (CIs).

During a median follow-up of 14.0 and 14.4 years, 2117 cases of CVD and 4190 deaths were documented. After adjusting for potential confounders, comparing the high LE8 score (80-100 points) to the low LE8 score (<50 points), the multivariable HRs (95 % CIs) were 0.28 (0.20, 0.40) for CVD, 0.14 (0.06, 0.34) for myocardial infarction, 0.35 (0.25, 0.50) for total stroke, and 0.68 (0.56, 0.83) for all-cause mortality, respectively.

Among patients with CKD, greater adherence to CVH, as defined by LE8, was significantly associated with a lower risk of CVD and all-cause mortality.

Chronic kidney disease (CKD) often follows acute kidney injury, leading to renal fibrosis and progressive renal failure. Spermine, a polyamine with antioxidant and anti-inflammatory properties, helps reduce renal fibrosis and may serve as a biomarker for CKD progression. We used spatially resolved metabonomic analysis with AFADESI-MSI to examine polyamine distribution in kidneys of a folic acid (FA)-induced CKD mouse model. Results showed decreased spermine and increased spermidine levels, associated with elevated spermine oxidase (SMOX) and spermidine/spermine N1-acetyltransferase (SSAT) enzyme expression in CKD. These findings suggest that altered polyamine metabolism contributes to CKD progression and may provide targets for polyamine-based therapies.

Cognitive impairment is a prevalent complication in chronic kidney disease (CKD), ranging from mild deficits in early stages to more severe conditions, such as mild cognitive impairment and dementia in advanced stages. CKD patients exhibit reduced performance in memory, attention, language, visuospatial abilities and executive functions.

Contributing factors include uraemic toxins, structural brain changes, blood-brain barrier dysfunction, anaemia and comorbidities like diabetes mellitus. Malnutrition, affecting nearly half of CKD patients, exacerbates cognitive decline through inflammation, oxidative stress and protein-energy wasting. Nutritional deficiencies, particularly in protein, vitamin D, B vitamins, omega-3 fatty acids and antioxidants, are linked to impaired cognition. Emerging evidence highlights the role of the gut-brain axis, with gut-derived uraemic toxins and microbiome alterations contributing to cognitive dysfunction. Processed foods and microplastics further compound risks by promoting inflammation and neurotoxicity. Dialysis and kidney transplantation offer opportunities for cognitive recovery, though challenges remain, particularly in haemodialysis patients. Nutritional interventions, including tailored protein intake, micronutrient supplementation and dietary counselling, are critical for mitigating cognitive decline. Addressing CKD comorbidities, such as anaemia and diabetes through targeted nutritional and pharmacological strategies, improves outcomes. Integrating psychological and social support enhances quality of life, given the high prevalence of anxiety and depression in CKD patients.

Future research should focus on personalized nutrition, gut microbiota modulation and routine cognitive assessments to optimise care. A holistic approach combining medical, nutritional and psychosocial strategies is essential for improving cognitive and overall health in CKD patients.

Chronic kidney disease (CKD) impacts a large percentage of the global population. Chronic kidney disease-mineral bone disorder (MBD) is the broad term describing alterations in key circulating factors involved in mineralization, ectopic calcification, and bone abnormalities. Cardiovascular complications, involving vascular calcification are one of the leading causes of death in this patient population. Plasma levels of pyrophosphate, a potent inhibitor of ectopic mineralization, are low in CKD and end-stage kidney disease patients. These data suggest that the correction of pyrophosphate levels could stand out as a crucial therapeutic goal to mitigate vascular calcifications and reduce cardiovascular mortality. The primary enzyme responsible for the generation of plasma pyrophosphate is ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1). We therefore evaluated INZ-701, a recombinant human ENPP1-Fc fusion protein, in an adenine-induced rat model of CKD. Our investigation revealed that INZ-701 administration resulted in significantly lower levels of calcification in the vasculature and soft tissues. Moreover, INZ-701 treatment significantly prevented the osteoid volume increase observed in vehicle-treated rats, addressing another critical clinical manifestation of CKD-MBD. These results underscore the potential of INZ-701 to reduce vascular calcification and bone mineralization abnormalities in CKD.

Creatinine levels in different body fluids can serve as an important biomarker for kidney functioning relevant to prostate cancer and chronic kidney disease (CKD). Creatinine levels vary in concentration in different body fluids, such as blood, urine, and saliva. Unlike previously reported sensors, the developed creatinine sensor can be employed for all levels of creatinine in samples of real patients.

In this study, an efficient voltammetric sensor for creatinine is developed by modifying a glassy carbon electrode (GCE) with poly (ethyleneimine) (PEI) capped silver nanoparticles at titanium dioxide (PEI-AgNPs)/TiO2, i.e., titanium dioxide (TiO2)/graphene oxide (GO) nanocomposites (Ag@GO/TiO2-GCE). The Ag@GO/TiO2 nanocomposite was characterized by scanning electron microscopy (SEM), atomic force microscopy (AFM), thermal gravimetric analysis (TGA), X-ray diffraction (XRD), transmission electron microscopy (TEM), dynamic light scattering (DLS), zeta potential, Fourier transform infrared (FT-IR) spectroscopy, and UV-Vis spectrophotometry. Various voltammetric techniques namely cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), chronoamperometry (CA), and differential pulse voltammetry (DPV) were employed. The Ag@GO/TiO2-GCE demonstrated good selectivity, stability, and a quick response time of 1.0 s for creatinine. An extended linear dynamic range (LDR) of creatinine from 0.01 pM (DPV) to 1.0 M (CV) based on different voltammetric techniques is imperative for detecting diverse creatinine levels in various body fluids. The LOD and LOQ of the developed creatinine detection method were found to be 1.15 pM and 3.5 pM, respectively. The electrochemical sensor exhibited an exceptionally high sensitivity of 15.74 μApM-1cm-2.The body fluids from healthy volunteers were spiked with a known amount of creatinine to evaluate sensor efficiency in the context of recovery. Finally, blood serum, saliva, and urine samples of kidney patients were analyzed for creatinine levels.

An important merit of the developed creatinine sensor is its ability for non-invasive point-of-care diagnosis in saliva with more than 90 % recovery. The comparison of the developed method with the standard Jaffes' colorimetric method endorsed its reliability and extended ability for the samples where Jaffes' method fails. The low LOD, high sensitivity, extended LDR, and low-cost render the possibility of adopting this method for point-of-care diagnosis.

To estimate the global disease burden and cross-national inequalities in the distribution of ischemic heart disease attributable to kidney dysfunction (KI-IHD) from 1990 to 2021.

The estimates for age-standardized death rates (ASDR) and age-standardized disability-adjusted life-years rates (ASDAR) of KI-IHD were obtained from the Global Burden of Disease Study (GBD) 2021. Data for gross domestic product (GDP) and GDP growth rates were extracted from World Bank database. The average annual percent change (AAPC) was calculated to analyze temporal trends of ASDR and ASDAR by Joinpoint regression model. Slope index of inequality and concentration index were generated to quantify the cross-national socioeconomic inequality of KI-IHD burden.

From 1990 to 2021, the ASDR and ASDAR of KI-IHD has shown downward trend globally; with AAPC values of -1.384 % and -1.204 %. The ASDR and ASDAR of KI-IHD was higher in males than females, with increasing age, the burden gradually increased. The concentration index showed 0.02 (95%CI: 0.02, 0.06) in 1990 and -0.11 (95%CI: 0.15, -0.07) in 2021. The slope index of inequality showed that an excess of 170 ASDR per 100,000 existed between countries with the lowest and the highest SDI in 1990, however, in 2021, the results are reversed, a reduction of 159 per 100,000. GDP growth rate and GDP per capita might be associated with the health inequality of KI-IHD.

The burden of KI-IHD has decreased in almost 70 % of countries over the past three decades. Disproportional distribution of health inequalities was concentrated in poor countries.

The link between immigrant status, a key social determinant of health, and kidney disease remains uncertain. To evaluate this, we compared incident adverse kidney outcomes between immigrants and non-immigrants using Canadian provincial health administrative data. We conducted a population-based observational cohort study of all adult Ontario residents (immigrants and non-immigrants) with normal baseline kidney function (estimated glomerular filtration rate (eGFR) 70 mL/min/1.73m2 or more). Multivariable Cox proportional hazard regression modeling was used to evaluate the relationship between immigrant status and the composite adverse kidney outcome of 40% eGFR decline or kidney failure. The study cohort included 10,440,210 individuals with 22% immigrants and 78% non-immigrants. The mean (Standard Deviation) age and eGFR were 45 (17) years and 102 (16) mL/min/1.73m2, respectively. Immigrants experienced a 27% lower hazard for the composite adverse kidney outcome (adjusted hazard ratio 0.73 [95% Confidence Interval 0.72-0.74]) compared to non-immigrants which was primarily driven by 40% eGFR decline. However, immigrants also experienced a 12% lower hazard for incident kidney failure (0.88 [0.84-0.93]) compared to non-immigrants. Results were consistent upon accounting for the competing risk of death and adjusting for baseline albuminuria. As has been demonstrated with other chronic diseases, these novel findings suggest that a "healthy immigrant effect" also extends to kidney disease. Differential kidney disease outcomes were identified among immigrants based on refugee status and world region of origin which may inform health policy decision-making toward targeted screening strategies and more cost-effective resource allocation for immigrant populations.

Kidney diseases refer to a group of disorders that affect the structure and function of the kidneys, impairing their ability to filter waste products, excess fluids, and toxins from the blood. These diseases can be acute and chronic, and if left untreated, can lead to kidney failure. Their progression is closely associated with inflammation and oxidative stress. Key signaling cascades, such as TLR-4/MAPK and TLR-4/NF-κB, are instrumental in fostering renal inflammation. Excessive ROS production worsens kidney damage, whereas activation of the Nrf-2/ARE pathway mitigates this by enhancing antioxidant defense. Moreover, the TGF-β/Smad pathway is heavily implicated in driving renal fibrosis, a major factor in disease progression. Additionally, elevated uric acid levels exacerbate inflammatory signaling, thereby worsening renal injury and dysfunction. Current treatments for kidney diseases have several concerns, including the need for routine monitoring, side effects, and long-term regimens. Several natural compounds have shown promise in supporting kidney health by modulating these key molecular targets. Genistein is a naturally occurring isoflavone predominantly found in soybeans and soy-based products, such as tofu, soy milk, and tempeh. It has demonstrated beneficial effects in various renal disorders, including both acute and chronic conditions, by regulating key molecular mediators involved in tissue injury, fibrosis, and cellular defense mechanisms. These mediators include TLR-4, MAPK, NF-κB, TGF-β, Smads, ACE, angiotensin, SIRT1, Nrf-2, ROS, SERBP, JAK/STAT and cytokines, among others. Considering the potential of genistein in modulating these mediators, the current review investigates the mechanistic interactions among these mediators in mediating its renoprotective effects.

Chronic kidney disease is a persistent ailment marked by the gradual decline of kidney function. Its classification primarily relies on the estimated glomerular filtration rate and the existence of kidney damage. The kidney disease improving global outcomes organization has established a widely accepted system for categorizing chronic kidney disease. explainable artificial intelligence for classification involves creating machine learning models that not only accurately predict outcomes but also offer clear and interpretable explanations for their decisions. Traditional machine learning models often pose difficulties in comprehending the intricate processes behind specific classification choices due to their intricate and obscure nature. In this study, an explainable artificial intelligence-chronic kidney disease model is introduced for the process of classification. The model applies explainable artificial intelligence by utilizing extra trees and shapley additive explanations values. Also, binary breadth-first search algorithm is used to select the most important features for the proposed explainable artificial intelligence-chronic kidney disease model. This methodology is designed to derive valuable insights for enhancing decision-making strategies within the field of classifying chronic kidney diseases. The performance of the proposed model is compared with another machine learning models, namely, random forest, decision tree, bagging classifier, adaptive boosting, and k-nearest neighbor, and the performance of the models is evaluated using accuracy, sensitivity, specificity, F-score, and area under the ROC curve. The experimental results demonstrated that the proposed model achieved the best results with accuracy equals 99.9%.

11-Oxygenated androgens are a group of adrenal-derived steroids that require peripheral activation. In vitro data highlight a putative role for 11β-hydroxysteroid dehydrogenase type 2 (HSD11B2) in 11-oxygenated androgen biosynthesis, converting 11β-hydroxyandrostenedione to 11-ketoandrostenedione (11KA4), the direct precursor of the potent androgen 11-ketotestosterone (11KT). As the kidney is the major site of HSD11B2 expression, we hypothesized that patients with chronic kidney disease (CKD) would have reduced 11-oxygenated androgen biosynthesis due to impaired HSD11B2 activity.

To determine the role of HSD11B2 in 11-oxygenated androgen biosynthesis using a human CKD cohort alongside complementary cell culture and computational modeling approaches.

Cross-sectional observational study of patients with CKD (n = 85) and healthy controls (n = 46) measuring serum and urinary concentrations of glucocorticoids, and classic and 11-oxygenated androgens by liquid chromatography tandem mass spectrometry. A computational model of peripheral 11-oxygenated androgen biosynthesis was fitted to the serum data to calculate relative HSD11B2 expression levels for each participant.

HSD11B2 activity declined with estimated glomerular filtration rate (eGFR), evidenced by higher cortisol/cortisone (E) ratios in patients with CKD than in controls (P < .0001). Serum concentrations of E, 11KA4, 11KT, and 11β-hydroxytestosterone were lower in patients with CKD than in controls (P < .0001 for each). A computational model based on enzyme kinetic parameters of HSD11B2, 11β-hydroxysteroid dehydrogenase type 1, 17β-hydroxysteroid dehydrogenase type 2, and aldo-keto reductase 1C3 confirmed HSD11B2 as the key enzyme responsible for reduced 11-oxygenated androgen biosynthesis in CKD. Predicted HSD11B2 expression correlated with eGFR.

This is the first in vivo study to confirm a central role for renal HSD11B2 in 11-oxygenated androgen biosynthesis. Determining the clinical implications of this observation for patients with CKD requires further research.

This study investigated the impact of anti-aging protein α-Klotho on cardiometabolic diseases (CMDs) among middle-aged and elderly population. A total of 11,198 participants aged 40-79 years were included in the National Health and Nutrition Examination Survey (NHANES) spanning 2007-2016. Serum α-Klotho levels were quantified via enzyme-linked immunosorbent assays. CMDs comprised cardiovascular disease (CVD), and four metabolic disorders: type 2 diabetes (T2DM), obesity, chronic kidney disease (CKD), and non-alcoholic fatty liver disease (NAFLD). Weighted logistic regression analysis, subgroup analysis, mediation analysis, restricted cubic splines (RCS), and Cox proportional hazards regression analysis were used. α-Klotho exhibited negative associations with each single CMD except T2DM, and RCS showed U-shape and L-shape dose-response relationships of α-Klotho with risk of T2DM and CKD, respectively. Ordered logistic regression analysis revealed that higher levels of Klotho markedly reduced the cumulative number of metabolic comorbidities complicating CVD (OR 0.56 (0.35, 0.91)). Simple mediation analysis showed CKD may explain up to 20.42% of the association between Klotho and CVD. Notably, α-Klotho's association with cardiometabolic comorbidities was particularly evident among individuals who were widowed/divorced/separated, non-Hispanic Black, lower-income, or less educated, with hypertension, current smokers, lower leisure and commuting physical activity, but higher work-related physical activity. Regarding long-term effects, higher α-Klotho levels were associated with lower all-cause mortality among participants with CMDs, but not among those without CMDs. Higher α-Klotho levels were associated with lower CMD prevalence, particularly in high-risk cardiovascular populations with lower socioeconomic status and unfavorable lifestyles and reduced all-cause mortality risk among CMD patients.

Various parts of Prunus persica (L.) Batsch (peach) exhibit medicinal properties and are utilized in traditional Chinese medicine (TCM) for therapeutic purposes. Notably, the root of P. persica, referred to as "taoshugen" in Chinese, is utilized by experienced TCM practitioners for the treatment of liver cirrhosis, suggesting its potential efficacy in mitigating organ fibrosis.

The study aimed to investigate the potential protective role of the water extract of taoshugen (WE-TSG) against chronic kidney disease-associated renal fibrosis and the underlying mechanisms.

The chemical composition of WE-TSG was characterized using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The anti-renal fibrosis efficacy of WE-TSG was evaluated in vitro using TGF-β1-stimulated renal tubular TCMK1 cells and in vivo using a murine model of unilateral ureter obstruction (UUO). The underlying mechanisms were elucidated using RNA-seq and CRISPR/Cas9-mediated loss of function of candidate genes. The activity of TGF-β signaling and the extent of fibrosis were determined by luciferase reporter assays, histology, immunohistochemistry, RT-PCR, and Western blot.

LC-MS/MS analysis identified 14 major compounds in WE-TSG, primarily flavonoids and organooxygen compounds. In TCMK1 cells, WE-TSG significantly inhibited the activity of TGF-β-responsive luciferase reporters, CAGA-luc and CTGF-luc, and dose-dependently (3.125, 6.25, and 12.5 μg/mL) suppressed TGF-β1-induced Smad2/3 phosphorylation (p-Smad2/3) and fibrotic gene (fibronectin, Col1a1, and Ctgf) expression, without affecting total Smad2/3 protein levels. In vivo, oral administration of WE-TSG (1.4 and 2.8 g/kg) attenuated structural abnormalities, collagen deposition, and fibrotic gene (fibronectin, Col1a1, and α-SMA) expression, alongside reduced TGF-β signaling activity (TGF-β1 and p-Smad2/3) in the kidney tissues of UUO mice. RNA-seq in TCMK1 cells identified that Pmepa1, a negative-feedback regulator of TGF-β signaling, was significantly upregulated upon WE-TSG pretreatment. Importantly, knockout of Pmepa1 abolished the anti-TGF-β signaling and anti-fibrosis effects of WE-TSG in TGF-β1-stimulated TCMK1 cells. Moreover, kidney-targeted Pmepa1 knockdown also abrogated the anti-renal fibrosis role of WE-TSG in UUO mice.

Our findings demonstrate that WE-TSG inhibits TGF-β signaling and attenuates UUO-induced renal fibrosis by promoting Pmepa1 expression, highlighting the potential of herbal medicine taoshugen in the clinical treatment of CKD.

This study aimed to investigate the causal relationship between lipidomes and chronic kidney disease (CKD) and identify and quantify the role of immune cells as a potential mediator. Using summary-level data from a genome-wide association study, a 2-sample Mendelian randomization (MR) analysis of genetically predicted lipidomes (7174 cases) and CKD (406,745 cases) was performed. Furthermore, we used 2-step MR to quantitate the proportion of the effect of immune cells traits-mediated lipidomes on CKD. The MR analysis revealed a causal relationship between lipidomes and CKD, with different lipidomes either increasing or decreasing the risk of CKD. Immune cells may serve as intermediaries in the pathway from lipidomes to CKD. Our study indicates that CD33 on basophils accounts for 3.23% of the reduced risk associated with triacylglycerol (53:3) levels in CKD. In conclusion, our study has identified a causal relationship between lipidomes and CKD, as well as the mediating role of CD33 on basophils. However, other risk factors like potential mediators require further investigation. In clinical practice, particular attention should be paid to lipidomic changes, especially triacylglycerol, in patients with CKD.

Measuring the thickness of the glomerular basement membrane (GBM) and assessing the percentage of podocyte foot process effacement (%PFPE) are important for diagnosing non-neoplastic kidney diseases. However, when performed manually by nephropathologists using electron microscopy (EM) images, these assessments are hindered by the lack of universally standardized guidelines, leading to technical challenges. We have developed a novel deep learning (DL)-based pipeline which has the potential to reduce human error and enhance the consistency and efficiency of GBMs and %PFPE quantifications.

This study utilized 196 EM images from kidney biopsies (representing 21 different kidney diseases from 83 subjects) which were manually annotated by consensus of 3 nephrologists and 2 nephropathologist providing ground truth (GT) masks of GBMs, podocytes, red blood cells and other glomerular ultrastructures. Of these, 165 images were used to develop two DL models (DeepLabV3+ and U-Net architectures) for EM image segmentation. Subsequently, the models were evaluated on the remaining 31 images and compared for segmentation accuracy, and the predicted GBM and podocyte masks were analyzed by algorithms in the pipeline which automatically measured the corrected harmonic mean of GBM thickness (cmGBM) and estimated the %PFPE. The automated measurements were statistically compared to the corresponding cmGBM measured and %PFPE estimated using the consensus GBM and podocyte GT masks. The goal was to identify differences between measurements provided by these three methods. Statistical evaluations were carried out using the intraclass correlation coefficient (ICC), and the Bland-Altman plots estimating the bias and limits of agreement (LoAs) between the GT and DL mask-based measurements.

In the 31 test set images, the DeepLabV3+ model achieved a global accuracy (gACC) of 92.8 % and a weighted intersection over union (wIoU) of 0.869, outperforming the U-Net model, which recorded a gACC of 88.9 % and a wIoU of 0.800. For GBM thickness measurements, the cmGBM derived from DeepLabV3+ masks exhibited excellent agreement with GT-masks based measurements (ICC = 0.991, p < 0.001), whereas the U-Net model showed good agreement (ICC = 0.881, p < 0.001). The %PFPE estimates obtained using the DL-generated podocyte masks were highly consistent with those based on GT, with ICC values of 0.926 and 0.928 for DeepLabV3+ and U-Net, respectively. The Bland-Altman plots revealed a positive bias in the cmGBM and %PFPE obtained from the masks generated by the DeepLabV3+ model, and negative bias in the cmGBM and %PFPE obtained from the masks generated by the U-Net model. However, the DeepLabV3+ masks provided narrower LoA ranges than the U-Net masks for measuring cmGBM.

This study highlights the potential of AI to address the limitations of manual assessments of glomerular ultrastructures in EM images by providing comprehensive, objective and accurate measurements of GBM thickness and %PFPE estimates. Our pipeline with DeepLabV3+ demonstrated robust EM image segmentation efficiency and excellent reliability of measurements when compared to expert ground truth. Further refinement of this AI-driven method for advancing the diagnostic capabilities and standardization of AI in nephropathology is warranted.

The cytochrome P450 family 3 subfamily A polypeptide 5 (CYP3A5) gene plays an important role in renal function through its product's involvement in metabolizing endogenous substances and drugs, including immunosuppressants used following kidney transplantation. A single-nucleotide polymorphism, CYP3A5*3 (rs776746), produces a non-functional variant that may influence progression of chronic kidney disease (CKD) by impairing renal filtration. However, the frequency of the CYP3A5*3 allele in the Thai population and its association with renal parameters remain underexplored. This study aimed to determine the prevalence of CYP3A5 polymorphisms and their association with renal function.

We investigated the distribution of CYP3A5 polymorphisms in 329 northeastern Thai participants, including 205 CKD patients and 124 healthy controls. Genotyping was performed using the TaqMan allelic discrimination assay. Renal function parameters were assessed and compared between CYP3A5*1 and CYP3A5*3 allele carriers.

In the entire cohort, the allele frequency of CYP3A5*3 was 63.2%, with genotype frequencies of CYP3A5*1/*1 (16.7%), CYP3A5*1/*3 (40.1%), and CYP3A5*3/*3 (43.2%). There was no significant difference in the CYP3A5 allele frequencies between CKD and control groups. CYP3A5*3 carriers exhibited significantly lower eGFR, urine creatinine and serum creatinine clearance and higher UACR compared to CYP3A5*1 carriers. After adjusting for confounders, CYP3A5*3 remained significantly associated with reduced urine creatinine.

This study highlights a high prevalence of CYP3A5 polymorphisms in the northeastern Thai population. The association of the CYP3A5*3 allele with renal function parameters underscores the need for further research into the mechanisms by which CYP3A5 affects kidney function, which could inform personalized CKD management strategies.

Although use of the autogenous arteriovenous fistula is the first choice for vascular access for hemodialysis, the tunneled cuffed catheter (TCC) remains an important alternative method that is applied widely in maintenance hemodialysis for patients with end-stage renal disease. In addition to common complications, such as thrombosis, infection, formation of a fibrin sheath, or central vein stenosis, TCC dysfunction, such as kinks, cuff detachment, or mechanical destruction, can be easily overlooked. The reasons for these clinical problems are multifactorial and include the insertion handling, presence of diabetes mellitus, catheter type, malnutrition, and the patient's body habitus. This minireview describes our experience with TCC and the current literature on managing TCC dysfunction.

To explore the influence of the serum total bilirubin to total cholesterol (TBIL/TC) ratio on the progression of chronic kidney disease (CKD) in people with type 2 diabetes.

The present retrospective discovery cohort investigated 4282 patients. The exposure was baseline TBIL/TC ratio. The outcome was the first time to progressing CKD, defined by a drop in the estimated glomerular filtration rate (eGFR) category, along with a reduction in eGFR of at least 25% compared to the baseline value. Hazard ratios (HRs) for CKD progression were evaluated based on the Cox proportional hazards approach. Dose-response relationships were conducted using Restricted Cubic Splines (RCS). Additionally, 758 patients were enrolled as an independent validation cohort.

During a median observation period of 2.4 years (interquartile range 1.3-3.8 years) within the discovery cohort, 522 individuals showed progression in CKD. The analysis revealed a negative association between the TBIL/TC ratio and the risk of CKD progression, with an adjusted HR of 0.17 and a 95% CI ranging from 0.07 to 0.41. After adjusting for confounding variables, the HRs for the second, third, and fourth quartiles of the TBIL/TC ratio were recorded at 0.61 (95% CI 0.48, 0.78), 0.55 (95% CI 0.42, 0.72), and 0.55 (95% CI 0.41, 0.74), respectively. Analysis with RCS indicated an optimal TBIL/TC ratio threshold of 0.25%. Similar results were also observed in the validation cohort.

A higher TBIL/TC ratio was significantly associated with a reduced risk of CKD progression in patients with type 2 diabetes.

Managing type-2 diabetes (T2D) in chronic kidney disease (CKD) patients requires consideration of kidney function, and many drugs have not been investigated thoroughly. Clinical studies have demonstrated Glargine U300 (Gla-300) supports achievement of adequate glycemic control at low hypoglycemia risk.

This cross-sectional study analysed routine data of 21 359 T2D patients with CKD (1786 using Gla-300; 19 568 without any insulin) from the prospective Diabetes-Patienten-Verlaufsdokumentation (DPV) registry to evaluate patient characteristics and safety of Gla-300 use across different CKD stages.

Patients on Gla-300 had T2D onset at an earlier age (median age 55.1 vs. 62.3 years), longer diabetes duration (17.3 vs. 11.3 years), higher body weight (91.3 vs. 83.9 kg) and HbA1c levels (7.3% vs. 6.7%) than non-insulin patients (all p < 0.001). Gla-300 usage increased from CKD stage 1-4 (median dose 44 vs. 55 units) with higher baseline HbA1c levels (7.2% vs. 7.4%). Although severe hypoglycemia rates were low, a slight increase (0.01%/PY vs. 0.04%/PY) was observed with decreasing estimated glomerular filtration rate levels. Compared to others, stage 5 CKD patients had a distinct profile with lower HbA1c levels (6.9%), body weight (90 kg) and higher Gla-300 usage (50 units). Metformin, SGLT-2 inhibitors and GLP-1 RA were common concomitant drugs with diminished usage in advanced CKD stages, while Gla-300 was common at all stages.

Despite variations in patient profiles, Gla-300 is widely used across all CKD stages, particularly in advanced stages with a low rate of severe hypoglycemia, suggesting its safe administration in CKD patients.

COVID-19 has been linked to acute kidney injury (AKI) and chronic kidney disease (CKD), but machine learning (ML) models predicting these risks post-pandemic have been absent. We aimed to use large electronic health records (EHR) and ML algorithms to predict the incidence of AKI and CKD during the post-pandemic period, assess the necessity of including COVID-19 infection history as a predictor, and develop a practical webpage application for clinical use.

National EHR data from TriNetX, emulating a prospective cohort of 104,565 patients from 07/01/2022 to 03/31/2024, were used. A total of 69 baseline variables were included, with demographics, comorbidities, lab test results, vital signs, medication histories, hospitalization visits, and COVID-19-related variables. Prediction windows of 1 month and 1 year were defined to assess AKI and CKD incidence. Eight machine learning models, primarily including extreme gradient boosting (XGBoost), neural network, and random forest (RF), were applied. Cross-validation and model tuning were conducted during the training process. Model performance was evaluated using six metrics, including the area under the receiver-operating-characteristic curve (AUROC). A combination of model-driven, data-driven, and clinical-driven methods was employed to identify the final models. An application with the final models was built using the R Shiny framework.

The final models, incorporating 9 variables-primarily including eGFR, inpatient visit number, and number of COVID-19 infections-were selected. XGBoost demonstrated the best performance for predicting the incidence of AKI in 1 month (AUROC = 0.803), AKI in 1 year (AUROC = 0.799), and CKD in 1 year (AUROC = 0.894). Random Forest (RF) was selected for predicting the incidence of CKD in 1 month (AUROC = 0.896). A comparison of AUROC with and without COVID-19 infection confirmed its importance as a critical predictor in the model. The final models were translated into a convenient tool to facilitate their use in clinical settings.

Our study demonstrates the applicability of using large national EHR data in developing high-performance machine learning models to predict AKI and CKD risks in the post-COVID-19 period. Incorporating the number of COVID-19 infections in the past year showed improved prediction performance and should be considered in future models for kidney disease prediction. A user-friendly application was created to support clinicians in risk assessment and surveillance.

Artificial Intelligence and Biomedical Informatics Pilot Funding, Penn State College of Medicine.

Kidney diseases, characterized by renal dysfunction, are the leading causes of death worldwide. It is crucial to prevent and treat kidney diseases to reduce their associated morbidity and mortality. Moderate physical exercise has been recognized to be advantageous for kidney health. Irisin is an exercise-induced myokine that was identified in 2012. It plays an important role in energy and bone metabolism, oxidative stress reduction, anti-inflammatory processes, cell death inhibition, and cardiovascular protection. However, the relationship between irisin and kidney diseases have not been fully elucidated. This review explores the role of irisin as a biomarker for kidney disease diagnosis and its associated complications, as well as the mechanisms through which it participates in various cell death pathways, such as apoptosis, autophagy, pyroptosis, and ferroptosis. Furthermore, irisin secretion levels were discussed to provide a basis for kidney disease prevention and treatment avenues, as well as therapeutic guidance for developing new and promising intervention strategies. Clinical Trial Registration: None.

Renal protection is a frequent indication for urological surgery in pediatric patients; however, preoperative assessment is not routinely performed. We assessed the rates of preoperative renal function testing and stratified outcomes after major pediatric urological surgery. Pediatric urology patients, specifically high-risk patients undergoing genitourinary surgeries, are likely to have an underdiagnosis of renal dysfunction after surgery.

Cases were identified from the 2012 to 2019 National Surgical Quality Improvement Program-Pediatric database. Patients who underwent major urological surgery on an inpatient basis were included in this study. Abnormal renal function was defined as a creatinine (Cr) level of ≥0.5 mg/dL (younger than 2 years) and a glomerular filtration rate of <90 mL/min (2 years or older). Glomerular filtration rate was calculated using the bedside Schwartz equation (2 years or older): estimated glomerular filtration rate = 0.413 × (height/Cr).

A total of 17,315 patients were included, of whom 3792 (21.9%) had documented Cr values. Based on the defined criteria, abnormal renal function was found in 7.3% of infants (younger than 2 years), 6.3% of children (2-9 years), and 15.0% of adolescents (10-18 years). Patients with abnormal preoperative renal function values were significantly (p < 0.001) more likely to experience readmission (10.2% vs. 5.8%), reoperation (3.7% vs. 1.6%), surgical organ/space infection (0.9% vs. 0.4%), transfusion (1.5% vs. 0.6%), renal insufficiency (1.6% vs. 0.4%), or urinary tract infection (5.1% vs. 3.6%).

In this pediatric population, 21.9% of the patients had documented preoperative Cr values before major urological surgery. Patients with documented abnormal preoperative renal function tests experienced higher complication rates. These patients have higher rates of progressive renal insufficiency and acute renal failure than those with normal renal function. The introduction of a standardized and unbiased risk assessment tool has the potential to offer patients benefits by pinpointing individuals with a heightened risk of complications. Further investigation is necessary to enhance the precise categorization of at-risk patients.

Identifying patients on dialysis among those with an estimated glomerular filtration rate (eGFR) < 15 mL/min/1.73 m2 remains challenging. To facilitate clinical research in advanced chronic kidney disease (CKD) using electronic health records, we aimed to develop algorithms to identify dialysis patients using laboratory data obtained in routine practice.

We collected clinical data of patients with an eGFR < 15 mL/min/1.73 m2 from six clinical research core hospitals across Japan: four hospitals for the derivation cohort and two for the validation cohort. The candidate factors for the classification models were identified using logistic regression with stepwise backward selection. To ensure transplant patients were not included in the non-dialysis population, we excluded individuals with the disease code Z94.0.

We collected data from 1142 patients, with 640 (56%) currently undergoing hemodialysis or peritoneal dialysis (PD), including 426 of 763 patients in the derivation cohort and 214 of 379 patients in the validation cohort. The prescription of PD solutions perfectly identified patients undergoing dialysis. After excluding patients prescribed PD solutions, seven laboratory parameters were included in the algorithm. The areas under the receiver operation characteristic curve were 0.95 and 0.98 and the positive and negative predictive values were 90.9% and 91.4% in the derivation cohort and 96.2% and 94.6% in the validation cohort, respectively. The calibrations were almost linear.

We identified patients on dialysis among those with an eGFR < 15 ml/min/1.73 m2. This study paves the way for database research in nephrology, especially for patients with non-dialysis-dependent advanced CKD.