Risk Of Chronic Kidney Disease Research Articles

Association of dietary manganese intake with new-onset chronic kidney disease in participants with diabetes

BackgroundWe explored the association of dietary manganese (Mn) with new-onset chronic kidney disease (CKD) in participants with diabetes on different glycemia control status and potential mechanisms. MethodsThe study included 7248 adults with diabetes from the UK Biobank who had complete dietary data and were free of CKD at baseline. Dietary information was collected by the online 24-h diet recall questionnaires. The primary outcome was new-onset CKD. Results565 (7.8 %) participants developed new-onset CKD during a median follow-up of 11.96 years. Overall, there was a significantly inverse relationship of dietary Mn intake with new-onset CKD in individuals with diabetes at glycated hemoglobin (HbA1c) ≥6.5 % (per SD increment, HR [95%CI]: 0.79 [0.68-0.91]), but not in people with diabetes at HbA1c <6.5 % (per SD increment, HR [95%CI]: 1.07 [0.90-1.29]; P for interaction = 0.004). In individuals with diabetes at HbA1c ≥6.5 %, body mass index and waist circumference significantly mediated the association between dietary Mn intake and new-onset CKD, with mediated proportions of 17.5 % and 17.4 %, respectively. ConclusionsHigher dietary Mn intake was significantly associated with a lower new-onset CKD risk in participants with diabetes at poor glycemic control status. The inverse association was mainly mediated by obesity. If further confirmed, our findings underscore the importance of maintaining adequate dietary Mn intake for the primary prevention of new-onset CKD in patients with diabetes, especially those with poor glycemic control.

Glucose-Lowering Drugs and Primary Prevention of Chronic Kidney Disease in Type 2 Diabetes Patients: A Real-World Primary Care Study

Background/Objectives: The burden of chronic kidney disease (CKD) is increasing, as is the prevalence of type 2 diabetes mellitus (T2DM). Post-hoc analyses of clinical trials support that sodium–glucose cotransporter-2 inhibitors (SGLT-2i) and glucagon-like peptide-1 receptors agonists (GLP-1RAs) prevent CKD in T2DM patients. Methods: We used the Spanish primary care database BIFAP to perform a retrospective cohort study with a nested case-control analysis to assess the incidence, risk factors, and the effect of glucose-lowering drugs (GLDs) on the primary prevention of CKD. Results: From a cohort of 515,701 T2DM subjects (2.75 million person-years), we found 89,075 incident CKD cases, yielding an overall incidence rate (95%CI) of 324.3 (322.1–326.5) per 10,000 person-years. In the nested case–control analysis, gout, hyperuricemia, and hyperkalemia were the factors showing the highest AORs. Long-term users (≥3 years) of GLP1-RAs and SGLT-2i, compared to other GLDs, showed a decreased risk for CKD (AOR = 0.85; 95%CI: 0.73–0.99 and AOR = 0.89; 95%CI: 0.74–1.08, respectively), and for incident CKD at KDIGO stages G3-G5 (AOR = 0.72; 95%CI: 0.56–0.94 and AOR = 0.64; 95%CI: 0.46–0.91, respectively). Conclusions: In a real-world primary care setting, the long-term use of GLP-1RAs and SGLT-2i, but not other GLDs, appeared to decrease the risk of incident CKD in T2DM, supporting a role in primary prevention of CKD.

First interim results from FINE-REAL: a prospective, non-interventional, phase 4 study providing insights into the use and safety of finerenone in a routine clinical setting.

Finerenone, a selective non-steroidal mineralocorticoid receptor antagonist, improves kidney and cardiovascular outcomes in patients with chronic kidney disease (CKD) associated with type 2 diabetes (T2D). The FINE-REAL study (NCT05348733) aims to evaluate the characteristics and treatment patterns of participants treated with finerenone in clinical practice. FINE-REAL is a prospective, single-arm, non-interventional study of patients initiated on finerenone as part of their routine care in accordance with country-approved labels. The study, initiated in June 2022, is expected to be completed by January 2028. The cutoff for this pre-specified interim analysis was June 13, 2023. Participants were recruited across nephrology, endocrinology, cardiology, and primary care settings. Of 556 participants enrolled in the study by the cut-off date, 504 were included in this analysis (median follow-up duration of 7months [finerenone treatment initiation to last recorded observation]). At baseline, 76.1% of participants were in the high or very high (KDIGO) CKD risk categories. Angiotensin converting enzyme inhibitors/angiotensin receptor blockers and sodium-glucose cotransporter 2 inhibitors were prescribed to 71.8% and 46.6% of participants, respectively. Based on prescribing information, 87.9% and 12.1% of participants initiated finerenone at doses of 10 and 20mg, respectively. Finerenone treatment was uninterrupted in 92.3% of participants after 7months' median follow-up. Treatment-emergent adverse events occurred in 110 (21.8%) participants. Hyperkalemia occurred in 25 (5.0%) participants, with no cases leading to death, dialysis, or hospitalization. At this interim analysis, finerenone was initiated in patients with CKD and T2D across various clinical practices participating in the study. Treatment discontinuation and hyperkalemia occurred infrequently.

Proteome-wide mendelian randomization identifies novel therapeutic targets for chronic kidney disease.

There is an urgent need to pinpoint novel targets for drug discovery in the context of chronic kidney disease (CKD), and the proteome represents a significant pool of potential therapeutic targets. To address this, we performed proteome-wide analyses using Mendelian randomization (MR) and colocalization techniques to uncover potential targets for CKD. We extracted summary-level data from the ARIC study, focusing on 7213 European American (EA) individuals and 4657 plasma proteins. To broaden our analysis, we incorporated genetic association data from Icelandic cohorts, thereby enhancing our investigation into the correlations with chronic kidney disease (CKD), creatinine-based estimated glomerular filtration rate (eGFRcrea), and estimated glomerular filtration rate (eGFR). We utilized genetic association data from the GWAS Catalog, including CKD (765,348, 625,219 European ancestry and 140,129 non-European ancestry), eGFRcrea (1,004,040, European ancestry), and eGFR (567,460, European ancestry). Employing MR analysis, we estimated the associations between proteins and CKD risk. Additionally, we conducted colocalization analysis to evaluate the existence of shared causal variants between the identified proteins and CKD. We detected notable correlations between levels predicted based on genetics of three circulating proteins and CKD, eGFRcrea, and eGFR. Notably, our colocalization analysis provided robust evidence supporting these associations. Specifically, genetically predicted levels of Transcription elongation factor A protein 2 (TCEA2) and Neuregulin-4 (NRG4) exhibited an inverse relationship with CKD risk, while Glucokinase regulatory protein (GCKR) showed an increased risk of CKD. Furthermore, our colocalization analysis also supported the associations of TCEA2, NRG4, and GCKR with the risk of eGFRcrea and eGFR.

Portable Electrochemical System and Platform with Point-of-Care Determination of Urine Albumin-to-Creatinine Ratio to Evaluate Chronic Kidney Disease and Cardiorenal Syndrome.

The urine albumin (Alb)-to-creatinine (Crn) ratio (UACR) is a sensitive and early indicator of chronic kidney disease (CKD) and cardiorenal syndrome. This study developed a portable and wireless electrochemical-sensing platform for the sensitive and accurate determination of UACR. The developed platform consists of a carbon nanotube (CNT)-2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid)(ABTS)-based modified UACR sensor, a miniaturised potentiostat, a cup holder embedded with a magnetic stirrer and a smartphone app. The UACR sensing electrode is composed of two screen-printed carbon working electrodes, one screen-printed carbon counter electrode and a screen-printed AgCl reference electrode. The miniaturised potentiostat, which is controlled by the developed app, performs cyclic voltammetry and amperometry to detect Alb and Crn, respectively. Clinical trials of the proposed system by using spot urine samples from 30 diabetic patients indicate that it can accurately classify all three CKD risk statuses within 30 min. The high accuracy of our proposed sensing system exhibits satisfactory agreement with the commercial biochemical analyser TBA-25FR (Y = 0.999X, R2 = 0.995). The proposed UACR sensing system offers a convenient, reliable and affordable solution for personal mobile health monitoring and point-of-care urinalysis.

Prevalence and associated factors of chronic kidney disease among Truká Indigenous adults in Cabrobó, Brazil: a population-based study

The prevalence of chronic kidney disease (CKD) is increasing worldwide, especially in developing countries, due to factors such as lifestyle changes and the rise of non-communicable diseases. Populations living in socioeconomically disadvantaged areas are subject to a higher burden of CKD. However, the burden of CKD on Brazilian Indigenous people, especially those undergoing an advanced urbanisation process, has not yet been described. This cross-sectional study included 1715 Truká Indigenous adults from Cabrobó, Brazil. CKD was defined according to the Kidney Disease Improving Global Outcomes guidelines classification as a urinary albumin/creatinine ratio ≥30mg/g and/or an estimated glomerular filtration rate <60mL/min/1.73m2. Univariate and multiple logistic regression models were used to evaluate factors associated with CKD. Odds ratio (OR) with a 95% confidence interval (CI) was used to measure association. Out of the 1654 participants analysed (61 excluded due to missing data), the prevalence of CKD was 10% (95% CI, 8.6%-11.5%), with a higher prevalence in women compared to men (12.4% versus 6.9%, p<0.001). The mean age was 40.5 years, with 55.6% being women. In univariate analysis, female sex (OR, 1.9; 95% CI, 1.3-2.7), age ≥60 years (OR, 4.6; 95% CI, 3.2-6.6), cardiovascular disease (OR, 2.1; 95% CI, 1.1-4.1), and dyslipidemia (OR, 1.6; 95% CI, 1.1-2.4) were identified as associated factors with CKD. Multiple logistic regression analysis identified age ≥60 years, female sex, and dyslipidemia as independently associated factors with CKD. The prevalence of CKD among Truká Indigenous adults analysed is high and affects a higher proportion of women. Our study found no association between hypertension, diabetes, obesity, and CKD risk, despite their high prevalence. These findings assist in developing early CKD detection strategies in Brazilian Indigenous communities, supporting disease treatment and prevention. National Council for Scientific and Technological Development (CNPq)-Ministry of Science, Technology, and Innovation of Brazil, and the Maria Emília Foundation.

Разработка интеллектуальной системы поддержки принятия врачебных решений для прогнозирования хронической болезни почек у детей.

Introduction. Chronic kidney disease is often diagnosed too late. Currently, the diagnostic accuracy is 44.1%, which highlights the urgent need to improve diagnostic methods. The purpose of the study: to develop a model – a system of support of medical decisions to predict chronic kidney disease in children. Materials and methods. А one-center retrospective cohort study (2011–2022) of children with chronic kidney disease of 1–4 stages in the age from 1 to 17 years. To construct a predictive model for diagnosing chronic kidney disease in children, an ensemble learning method was used, using which the models obtained by machine learning algorithms were combined: multi-factor logistic regression and decision tree. The models use five variables: asthenic physique in a child, loss of protein and red blood cells with urine, ESR and blood serum sodium. Results. The study involved 158 patients. The main group includes 128 children with chronic kidney disease of stage 1–4 aged 1–17. The comparison group was 30 children with no diagnosed kidney pathology aged 1 to 17. The children of the two groups did not differ statistically by sex and age. A model has been obtained to predict chronic kidney disease in children on a test sample with an accuracy of 93.5% [87.1; 100.0]%; a sensitivity of 92.0% [82.1; 100.0]; a specificity of 100.0% [100.0; 100.0.0]; ROC-AUC = 98.7%;100.0].0. Obtained model of excellent quality (&gt;90%). The model describes 90.3% [83.8; 96.1]% variance. Conclusion. The proposed model demonstrates excellent predictive ability and may be of important clinical importance for predicting the chronic process in primary health care, where symptoms associated with the risk of chronic kidney disease, may be overlooked. Predicting and developing early nephroprotective strategies can lead to better treatment outcomes and prolong life.

A Risk Prediction Model for New-Onset Chronic Kidney Disease in the Elderly

Plain Language SummaryDifferent regions have different risk factors for chronic kidney disease (CKD), and using a single model for prediction can often lead to errors. This study aimed to create an easy-to-use tool to predict the risk of CKD in older adults. We analyzed data from 5,416 people aged over 65 who had regular health check-ups between January 2017 and July 2021. We found that about 20% developed CKD during a follow-up period of 2.3 years. Factors like age, being female, diabetes, high triglyceride levels, and initial kidney function were used to build the prediction model. This model was good at forecasting CKD risk and was validated to ensure its accuracy. It can help doctors quickly identify older adults who might be at risk of kidney problems and start early treatment.

Personalized Prediction of Long-Term Renal Function Prognosis Following Nephrectomy Using Interpretable Machine Learning Algorithms: Case-Control Study.

Acute kidney injury (AKI) is a common adverse outcome following nephrectomy. The progression from AKI to acute kidney disease (AKD) and subsequently to chronic kidney disease (CKD) remains a concern; yet, the predictive mechanisms for these transitions are not fully understood. Interpretable machine learning (ML) models offer insights into how clinical features influence long-term renal function outcomes after nephrectomy, providing a more precise framework for identifying patients at risk and supporting improved clinical decision-making processes. This study aimed to (1) evaluate postnephrectomy rates of AKI, AKD, and CKD, analyzing long-term renal outcomes along different trajectories; (2) interpret AKD and CKD models using Shapley Additive Explanations values and Local Interpretable Model-Agnostic Explanations algorithm; and (3) develop a web-based tool for estimating AKD or CKD risk after nephrectomy. We conducted a retrospective cohort study involving patients who underwent nephrectomy between July 2012 and June 2019. Patient data were randomly split into training, validation, and test sets, maintaining a ratio of 76.5:8.5:15. Eight ML algorithms were used to construct predictive models for postoperative AKD and CKD. The performance of the best-performing models was assessed using various metrics. We used various Shapley Additive Explanations plots and Local Interpretable Model-Agnostic Explanations bar plots to interpret the model and generated directed acyclic graphs to explore the potential causal relationships between features. Additionally, we developed a web-based prediction tool using the top 10 features for AKD prediction and the top 5 features for CKD prediction. The study cohort comprised 1559 patients. Incidence rates for AKI, AKD, and CKD were 21.7% (n=330), 15.3% (n=238), and 10.6% (n=165), respectively. Among the evaluated ML models, the Light Gradient-Boosting Machine (LightGBM) model demonstrated superior performance, with an area under the receiver operating characteristic curve of 0.97 for AKD prediction and 0.96 for CKD prediction. Performance metrics and plots highlighted the model's competence in discrimination, calibration, and clinical applicability. Operative duration, hemoglobin, blood loss, urine protein, and hematocrit were identified as the top 5 features associated with predicted AKD. Baseline estimated glomerular filtration rate, pathology, trajectories of renal function, age, and total bilirubin were the top 5 features associated with predicted CKD. Additionally, we developed a web application using the LightGBM model to estimate AKD and CKD risks. An interpretable ML model effectively elucidated its decision-making process in identifying patients at risk of AKD and CKD following nephrectomy by enumerating critical features. The web-based calculator, found on the LightGBM model, can assist in formulating more personalized and evidence-based clinical strategies.

Genetically predicted frailty index and risk of chronic kidney disease

Previous findings have reported the association between frailty and chronic kidney disease. However, the causality remains ambiguous. This study aimed to determine whether frailty index is causally associated with chronic kidney disease. We obtained the frailty genome-wide association study (GWAS) data and chronic kidney disease GWAS data from the FinnGen R5 (total n = 216,743; case = 3902, control = 212,841) as the exposure and outcome, respectively. A two-sample Mendelian randomization (MR) analysis was primarily conducted using the inverse-variance weighted (IVW), weighted median and MR-Egger regression analyses. Multivariable MR analysis (MVMR) was conducted for additional adjustment. In the two-sample Mendelian randomization analyses, a total of 14 single nucleotide polymorphisms (SNPs) were recognized as effective instrumental variables. The IVW method showed evidence to support a causal association between frailty index and chronic kidney disease (beta = 1.270; 95% CI 0.608 to 1.931; P < 0.001). MR-Egger revealed a causal association between frailty index and chronic kidney disease (beta = 3.612; 95% CI 0.805 to 6.419; P = 0.027). MR-Egger regression revealed that directional pleiotropy was unlikely to be biasing the result (intercept = − 0.053; P = 0.119). The weighted median approach and weighted mode method also demonstrated a causal association between frailty index and chronic kidney disease (beta = 1.148; 95% CI 0.278 to 2.019; P = 0.011; beta = 2.194; 95% CI 0.598 to 3.790; P = 0.018). Cochran’s Q test and the funnel plot indicated no directional pleiotropy. MVMR analysis revealed that the causal association between frailty index and chronic kidney disease remained after adjusting for potential confounders, body-mass index, inflammatory bowel disease, waist-hip ratio, and C-reactive protein. Our study provides evidence of causal association between frailty and chronic kidney disease from genetic perspectives.

Low brain-derived neurotrophic factor and high vascular cell adhesion molecule-1 levels are associated with chronic kidney disease in patients with type 2 diabetes mellitus.

Patients with type 2 diabetes mellitus (DM) have a high prevalence of chronic kidney disease (CKD). Energy imbalance and inflammation may be involved in the pathogenesis of CKD. We examined the effects of brain-derived neurotrophic factor (BDNF) and vascular cell adhesion molecule-1 (VCAM-1) on CKD in patients with type 2 DM. Patients with type 2 DM were enrolled for this cross-sectional study. Fasting serum was prepared to measure the BDNF and VCAM-1 levels. An estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 was used as the criterion for identifying patients with CKD. Of the 548 enrolled participants, 156 had CKD. Patients with CKD exhibited significantly lower BDNF (median of 21.4 ng/mL, interquartile range [IQR]: 17.0-27.0 ng/mL vs. median of 25.9 ng/mL, IQR: 21.0-30.4 ng/mL, P <0.001) and higher VCAM-1 (median of 917 ng/mL, IQR: 761-1172 ng/mL vs. median of 669 ng/mL, IQR: 552-857 ng/mL, P <0.001) levels than those without CKD. Serum BDNF levels were inversely correlated with VCAM-1 levels (Spearman's rank correlation coefficient = -0.210, P <0.001). The patients were divided into four subgroups based on median BDNF and VCAM-1 levels (24.88 ng/mL and 750 ng/mL, respectively). Notably, patients in the high VCAM-1 and low BDNF group had the highest prevalence (50%) of CKD. Multivariate logistic regression revealed a significantly higher odds ratio (OR) of CKD in the high VCAM-1 and low BDNF group (OR = 3.885, 95% CI: 1.766-8.547, P <0.001), followed by that in the high VCAM-1 and high BDNF group (OR = 3.099, 95% CI: 1.373-6.992, P =0.006) compared with that in the low VCAM-1 and high BDNF group. However, the risk of CKD in the low VCAM-1 and low BDNF group was not significantly different from that in the low VCAM-1 and high BDNF group (P =0.266). CKD in patients with type 2 DM is associated with low serum BDNF and high VCAM-1 levels. BDNF and VCAM-1 have a synergistic effect on CKD. Thus, BDNF and VCAM-1 can be potential biomarkers for CKD risk stratification in patients with type 2 DM.

Investigating the relationship of co-exposure to multiple metals with chronic kidney disease: An integrated perspective from epidemiology and adverse outcome pathways

Systematic studies on the associations between co-exposure to multiple metals and chronic kidney disease (CKD), as well as the underlying mechanisms, remain insufficient. This study aimed to provide a comprehensive perspective on the risk of CKD induced by multiple metal co-exposures through the integration of occupational epidemiology and adverse outcome pathway (AOP). The study participants included 401 male mine workers whose blood metal, β2-microglobulin (β2-MG), and cystatin C (Cys-C) levels were measured. Generalized linear models (GLMs), quantile g-computation models (qgcomp), least absolute shrinkage and selection operator (LASSO), and bayesian kernel machine regression (BKMR) were utilized to identify critical nephrotoxic metals. The mean concentrations of lead, cadmium, mercury, arsenic, and manganese were 191.93, 3.92, 4.66, 3.11, 11.35, and 16.33 µg/L, respectively. GLM, LASSO, qgcomp, and BKMR models consistently identified lead, cadmium, mercury, and arsenic as the primary contributors to kidney toxicity. Based on our epidemiological analysis, we used a computational toxicology method to construct a chemical-genetic-phenotype-disease network (CGPDN) from the Comparative Toxicogenomics Database (CTD), DisGeNET, and GeneCard databases, and further linked key events (KEs) related to kidney toxicity from the AOP-Wiki and PubMed databases. Finally, an AOP framework of multiple metals was constructed by integrating the common molecular initiating events (reactive oxygen species) and KEs (MAPK signaling pathway, oxidative stress, mitochondrial dysfunction, DNA damage, inflammation, hypertension, cell death, and kidney toxicity). This is the first AOP network to elucidate the internal association between multiple metal co-exposures and CKD, providing a crucial basis for the risk assessment of multiple metal co-exposures.

Association between GATM gene polymorphism and progression of chronic kidney disease: a mitochondrial related genome-wide Mendelian randomization study

Chronic Kidney Disease (CKD) stands as a substantial challenge within the global health landscape. The elevated metabolic demands essential for sustaining normal kidney function have propelled an increasing interest in unraveling the intricate relationship between mitochondrial dysfunction and CKD. However, the authentic causal relationship between these two factors remains to be conclusively elucidated. This study endeavors to address this knowledge gap through the Mendelian Randomization (MR) method. We utilized large-scale QTL datasets (including 31,684 eQTLs samples, 1980 mQTLs samples, and 35,559 pQTLs samples) to precisely identify key genes related to mitochondrial function as exposure factors. Subsequently, we employed GWAS datasets (comprising 480,698 CKD samples and 1,004,040 eGFRcrea samples) as outcome factors. Through a comprehensive multi-level analysis (encompassing expression, methylation, and protein quantification loci), we evaluated the causal impact of these genes on CKD and estimated glomerular filtration rate (eGFR). The integration and validation of diverse genetic data, complemented by the application of co-localization analysis, bi-directional MR analysis, and various MR methods, notably including inverse variance weighted, have collectively strengthened our confidence in the robustness of these findings. Lastly, we validate the outcomes through examination in human RNA sequencing datasets encompassing various subtypes of CKD. This study unveils significant associations between the glycine amidinotransferase (GATM) and CKD, as well as eGFR. Notably, an augmentation in GATM gene and protein expression corresponds to a diminished risk of CKD, whereas distinct methylation patterns imply an increased risk. Furthermore, a discernible reduction in GATM expression is observed across diverse pathological subtypes of CKD, exhibiting a noteworthy positive correlation with GFR. These findings establish a causal relationship between GATM and CKD, thereby highlighting its potential as a therapeutic target. This insight lays the foundation for the development of potential therapeutic interventions for CKD, presenting substantial clinical promise.

Effects of long-term lithium therapy on kidney functioning in mood disorders: A population-based historical cohort study.

Lithium is Food and Drug Administration-approved for bipolar disorder (BD) and is also used in depressive disorders but is underutilized due to concerns about chronic kidney disease (CKD). We explored clinical and demographic profiles of patients on long-term lithium therapy (LTLT) and assessed kidney function. Our aims were to identify the predictors for CKD stage ≥3 and the impact of lithium discontinuation post-CKD diagnosis. We conducted a population-based historical cohort study of adult patients with mood disorders on LTLT at the Marshfield Clinical Health System from 1990 to 2019. Data on lithium therapy and kidney-related information (estimated glomerular filtration rate and CKD) were extracted from electronic medical records. Among 1603 patients with mood disorders (mean age 42.1 years, 60% females), 15.3% (n = 246) developed CKD stage ≥3. Patients without CKD were on lithium for 4.5 years, compared to 6.6 years for those with CKD. Hypertension, age, and BD were significant CKD risk factors. Kidney function declined linearly with lithium duration, returning to pre-treatment trajectory in patients without CKD but showed no improvement in those with CKD after lithium discontinuation. The findings suggest that CKD occurs in 15% of patients with mood disorder receiving LTLT, with its progression potentially influenced by existing comorbidities rather than lithium alone. These results underscore the importance of monitoring kidney function in patients on LTLT and considering individual risk factors for CKD development. In patients who developed CKD, Li discontinuation did not impact change in kidney function.

Medullary Nephrocalcinosis

Medullary nephrocalcinosis is a clinical variant of chronic kidney disease characterized by diffuse deposition of calcium and phosphate salts in the parenchyma, leading to inflammatory-dystrophic changes and the development of chronic renal failure. Medullary nephrocalcinosis is divided into primary (develops in previously unaltered kidneys and initially affects the proximal part of the nephron) and secondary (simultaneously affects all parts of the renal glomeruli, causing nephrosclerosis and increasing the risk of chronic kidney disease). The article describes two clinical cases of medullary nephrocalcinosis with different etiological factors. In the first case, the disease developed against the background of regular use of third-generation cephalosporins (ceftriaxone), while in the second case, it resulted from lipid and purine metabolism disorders. The genetic and etiopathogenetic aspects of medullary nephrocalcinosis are discussed. Given the importance of determining the causes and pathogenetic mechanisms of medullary nephrocalcinosis, the need for thorough diagnostics in adult patients with changes in the renal parenchyma accompanied by hyperparathyroidism, hyper- or normocalcemia, hypophosphatemia, hypomagnesemia, and hypercalciuria is emphasized. Diagnostic workup should include genetic, metabolic, and iatrogenic components of kidney damage.

Arterial stiffness is associated with new-onset chronic kidney disease.

Background: A potential independent association between arterial stiffness (AS) and the development of new-onset chronic kidney disease (CKD) has not been thoroughly examined. Patients and methods: A total of 6929 participants were collected from the Kailuan study. All participants were free of CKD at the baseline. The participants were divided into four groups based on their brachial-ankle pulse wave velocity (baPWV) values. Cox regression models were used to analyze the relationship between baPWV values and the risk of new-onset CKD. Results: Over the course of a 10.06-year follow-up period, a total of 962 cases of new-onset CKD were documented. Cox proportional hazards analyses showed that a higher baPWV quartile was linked to an increased risk of new-onset CKD. Conclusions: Brachial-ankle pulse wave velocity has a strong correlation with the development of new-onset CKD. Therefore, baPWV can be considered an innovative indicator for predicting the occurrence of new-onset CKD.

Valuing a Reduction in the Risk of Chronic Kidney Disease: A Large-Scale Multi-Country Stated Preference Approach

Valuing a Reduction in the Risk of Chronic Kidney Disease: A Large-Scale Multi-Country Stated Preference Approach

Long-term exposure to NO2 and PM2.5 and the occurrence of chronic kidney disease among patients with type 2 diabetes in Taiwan

BackgroundIndividuals diagnosed with type 2 diabetes (T2D) frequently exhibit chronic kidney disease (CKD) which may be caused by environmental hazards such as exposure to air pollutants. However, limited research has explored the effects of prolonged exposure to air pollutants on CKD development in this population. This study examines the relationship between long-term exposure to air pollutants and CKD incidence in a longitudinal cohort of individuals with type 2 diabetes in Taiwan MethodsBetween 2003 and 2005, we recruited 1316 T2D patients (693 females [52.66 %]; mean age 56.16 ± 8.97 years). Patients were followed until December 31, 2012, with at least two clinical visits. Baseline demographics, medical history, and biomarker levels were collected. The development of CKD was determined by eGFR level < 60 mL/min/1.73 m2. Monthly averages of nitrogen dioxide (NO2) and fine particulate matter [PM ≤ 2.5 μm in aerodynamic diameter (PM2.5)] were acquired from 72 ambient air monitoring stations. The kriging method was employed to estimate the exposure levels to PM2.5, NO2, temperature, and relative humidity in the participants' residential areas. Cox regression with time-dependent covariates regression was applied to assess the impact of long-term exposure to air pollutants and CKD risk. ResultsOf 992 patients with normal renal function at baseline, 411 (41.43 %) experienced CKD occurrence over a median follow-up period of 5.45 years. The incidence of CKD was 93.96 cases per 1000 person-years. In multivariable adjusted models, patients exposed to PM2.5 levels above the third quartile of (>33.44 μg/m3) and NO2 levels above the fourth quartile (>22.55 ppb) were found to have an increased risk of CKD occurrence compared to lower exposure levels. ConclusionsThis longitudinal study highlights the increased risk of CKD in individuals with type 2 diabetes due to prolonged exposure to NO2 and PM2.5, emphasizing the need for tailored air quality management strategies for this high-risk population.

Metabolically healthy obesity and chronic kidney disease risk: exploring the dynamics.

Obesity represents a prevalent global health concern with significant implications for various diseases, including chronic kidney disease (CKD). Within this landscape, the phenomenon of metabolically healthy obesity has emerged, challenging traditional notions about the health risks associated with excess weight. While traditional CKD risk factors involve obesity, metabolic syndrome, diabetes, and hypertension, the metabolically healthy obese (MHO) subgroup disrupts these assumptions. Our main objective in this study is to integrate existing literature on CKD in MHO individuals. In this endeavor, we delve into the pathophysiological foundations, the transition between obesity phenotypes and their impact on renal health, examine the implications of their metabolic resilience on mortality within a renal context, and explore potential management strategies specifically designed for MHO individuals. Offering a comprehensive overview of the pathophysiology, we cover various factors contributing to the risk of CKD in the metabolically healthy obese setting, including inflammation, cytokines, hemodynamics, and the renin-angiotensin-aldosterone system, gastrointestinal microbiota, diet, exercise, adipose distribution, and lipotoxicity. Through this synthesis, we aim to provide a comprehensive understanding of the risk of CKD in those classified as MHO.

Identifying subtypes of type 2 diabetes mellitus based on real-world electronic medical record data in China

AimsTo replicate the European subtypes of type 2 diabetes mellitus (T2DM) in the Chinese diabetes population and investigate the risk of complications in different subtypes. MethodsA diabetes cohort using real-world patient data was constructed, and clustering was employed to subgroup the T2DM patients. Kaplan–Meier analysis and the Cox models were used to analyze the association between diabetes subtypes and the risk of complications. ResultsA total of 2,652 T2DM patients with complete clustering data were extracted. Among them, 466 (17.57 %) were classified as severe insulin-deficient diabetes (SIDD), 502 (18.93 %) as severe insulin-resistant diabetes (SIRD), 672 (25.34 %) as mild obesity-related diabetes (MOD), and 1,012 (38.16 %) as mild age-related diabetes (MARD). The risk of chronic kidney disease (CKD) and diabetic retinopathy (DR) were different in the four subtypes. Compared with MARD, SIRD had a higher risk of CKD (HR 2.40 [1.16, 4.96]), and SIDD had a higher risk of DR (HR 2.16 [1.11, 4.20]). The risk of stroke and coronary events had no difference. ConclusionsThe European T2DM subtypes can be replicated in the Chinese diabetes population. The risk of CKD and DR varied among different subtypes, indicating that proper interventions can be taken to prevent specific complications in different subtypes.