Protocol for a systematic review of the application of the kidney failure risk equation and Oxford classification in estimating prognosis in IgA nephropathy.

BACKGROUND: IgA nephropathy (IgAN) is a common cause of chronic kidney disease (CKD) and end-stage renal disease (ESRD). Outcomes are highly variable and predicting risk of disease progression at an individual level is challenging. Accurate risk stratification is important to identify individuals most likely to benefit from treatment. The Kidney Failure Risk Equation (KFRE) has been extensively validated in CKD populations and predicts the risk of ESRD at 2 and 5 years using non-invasive tests; however, its predictive performance in IgAN is unknown. The Oxford classification (OC) describes pathological features demonstrated on renal biopsy that are associated with adverse clinical outcomes that may also inform prognosis. The objective of this systematic review is to compare the KFRE with the OC in determining prognosis in IgAN. METHODS: A systematic review will be conducted and reported in line with PRISMA guidelines (PRISMA-P checklist attached as Additional file 1). Inclusion criteria will be cohort studies that apply the KFRE or OC to determine the risk of CKD progression or ESRD in individuals with IgAN. Multiple databases will be searched in duplicate to identify relevant studies, which will be screened first by title, then by abstract and then by full-text analysis. Results will be collated for comparison. Risk of bias and confidence assessments will be conducted independently by two reviewers, with a third reviewer available if required. DISCUSSION: Identifying individuals at the highest risk of progression to ESRD is challenging in IgAN, due to the heterogeneity of clinical outcomes. Risk prediction tools have been developed to guide clinicians; however, it is imperative that these aids are accurate and reproducible. The OC is based on observations made by specialist renal pathologists and may be open to observer bias, therefore the utility of prediction models incorporating this classification may be diminished, particularly as in the future novel biomarkers may be incorporated into clinical practice. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022364569.

Risk factors for chronic kidney disease in middle eastern patients with type 2 diabetes mellitus: A cross-sectional study using the KDIGO classification.

AIMS: Chronic kidney disease (CKD) is prevalent in patients with type 2 diabetes mellitus (T2DM). This study aimed to investigate risk factors for CKD progression across the kidney disease-Improving Global Outcomes (KDIGO)categories in a Middle Eastern population beyond hyperglycemia as emphasized by KDIGO guidelines which classifying CKD by cause and severity. METHODS: This cross-sectional study targeted 1603 patients with T2DM. Risk factors for CKD progression were determined using odds ratios (ORs) and 95 % confidence intervals (CIs). RESULTS: Overall, 35.5 %, 31.7 %, and 32.8 % of patients were classified as low-risk, moderate-risk, and high-/very high-/highest-risk, respectively. Several factors were associated with high/very high/highest risk categorization, including being aged >45 years (OR: 1.85, 95 % CI: 1.36-2.49; P < 0.001), male gender (OR: 1.87, 95 % CI: 1.38-2.54; P < 0.001), hypertension (OR: 3.66, 95 % CI: 2.32-5.78; P < 0.001), and T2DM duration of ≥15 years (OR: 3.2, 95 % CI: 2.27-4.5; P < 0.001). Patients with more concurrent risk factors were notably represented in the high/very high/highest risk category. CONCLUSIONS: Male patients, older patients, and those with comorbid hypertension, longstanding T2DM, and additional concurrent risk factors have a significantly higher risk of advanced CKD. Such findings should be considered when planning management approaches for patients with CKD.

Is the combination of linagliptin and allopurinol better prophylaxis against post-contrast acute kidney injury? A multicenter prospective randomized controlled study.

BACKGROUND: Patients with diabetic kidney disease (DKD) are at increased risk to develop post-contrast acute kidney injury (AKI). Diabetic patients under dipeptidyl peptidase 4 inhibitors (DPP4Is) experience a lower propensity to develop AKI. We speculated that linagliptin as a single agent or in combination with allopurinol may reduce the incidence of post-contrast AKI in stage 3-5 chronic kidney disease (CKD) patients with underlying DKD. METHODS: Out of 951 DKD patients eligible for this study, 800 accepted to sign informed consent. They were randomly allocated to 4 equal groups that received their prophylaxis for 2 days before and after radiocontrast. The first control group received N-acetyl cysteine and saline, the 2nd received allopurinol, the 3rd group received linagliptin, and the 4th received both allopurinol and linagliptin. Post-procedure follow-up for kidney functions was conducted for 2 weeks in all patients. RESULTS: 20, 19, 14, and 8 patients developed post-contrast AKI in groups 1 through 4, respectively. Neither linagliptin nor allopurinol was superior to N-acetyl cysteine and saline alone. However, the combination of the two agents provided statistically significant renal protection: post-contrast AKI in group 4 was significantly lower than in groups 1 and 2 (p < 0.02 and <0.03, respectively). None of the post-contrast AKI cases required dialysis. CONCLUSION: Linagliptin and allopurinol in combination may offer protection against post-contrast AKI in DKD exposed to radiocontrast. Further studies are needed to support this view. TRIAL REGISTRATION CLINICALTRIALS.GOV: NCT03470454.

Sofosbuvir/velpatasvir with or without low-dose ribavirin for patients with chronic hepatitis C virus infection and severe renal impairment.

OBJECTIVE: Data regarding the real-world effectiveness and safety of sofosbuvir/velpatasvir (SOF/VEL) with or without low-dose ribavirin (RBV) in patients with chronic hepatitis C virus (HCV) infection and severe renal impairment (RI) are limited. We evaluated the performance of SOF/VEL with or without low-dose RBV in HCV-infected patients with chronic kidney disease stage 4 or 5. DESIGN: 191 patients with compensated (n=181) and decompensated (n=10) liver diseases receiving SOF/VEL (400/100 mg/day) alone and SOF/VEL with low-dose RBV (200 mg/day) for 12 weeks were retrospectively recruited at 15 academic centres in Taiwan. The effectiveness was determined by sustained virological response at off-treatment week 12 (SVR12) in evaluable (EP) and per-protocol populations (PP). The safety profiles were assessed. RESULTS: The SVR12 rates by EP and PP analyses were 94.8% (95% CI 90.6% to 97.1%) and 100% (95% CI 97.9% to 100%). In patients with compensated liver disease, the SVR12 rates were 95.0% and 100% by EP and PP analyses. In patients with decompensated liver disease, the SVR12 rates were 90.0% and 100% by EP and PP analyses. Ten patients who failed to achieve SVR12 were attributed to non-virological failures. Among the 20 serious adverse events (AEs), none were judged related to SOF/VEL or RBV. The AEs occurring in ≥10% included fatigue (14.7%), headache (14.1%), nausea (12.6%), insomnia (12.0%) and pruritus (10.5%). None had ≥grade 3 total bilirubin or alanine aminotransferase elevations. CONCLUSION: SOF/VEL with or without low-dose RBV is effective and well-tolerated in HCV-infected patients with severe RI.

Comparative Analysis for Prediction of Kidney Disease Using Intelligent Machine Learning Methods.

Chronic kidney disease (CKD) is a major burden on the healthcare system because of its increasing prevalence, high risk of progression to end-stage renal disease, and poor morbidity and mortality prognosis. It is rapidly becoming a global health crisis. Unhealthy dietary habits and insufficient water consumption are significant contributors to this disease. Without kidneys, a person can only live for 18 days on average, requiring kidney transplantation and dialysis. It is critical to have reliable techniques at predicting CKD in its early stages. Machine learning (ML) techniques are excellent in predicting CKD. The current study offers a methodology for predicting CKD status using clinical data, which incorporates data preprocessing, a technique for managing missing values, data aggregation, and feature extraction. A number of physiological variables, as well as ML techniques such as logistic regression (LR), decision tree (DT) classification, and K-nearest neighbor (KNN), were used in this work to train three distinct models for reliable prediction. The LR classification method was found to be the most accurate in this role, with an accuracy of about 97 percent in this study. The dataset that was used in the creation of the technique was the CKD dataset, which was made available to the public. Compared to prior research, the accuracy rate of the models employed in this study is considerably greater, implying that they are more trustworthy than the models used in previous studies as well. A large number of model comparisons have shown their resilience, and the scheme may be inferred from the study's results.

Management of gout in chronic kidney disease: a G-CAN Consensus Statement on the research priorities.

Gout and chronic kidney disease (CKD) frequently coexist, but quality evidence to guide gout management in people with CKD is lacking. Use of urate-lowering therapy (ULT) in the context of advanced CKD varies greatly, and professional bodies have issued conflicting recommendations regarding the treatment of gout in people with concomitant CKD. As a result, confusion exists among medical professionals about the appropriate management of people with gout and CKD. This Consensus Statement from the Gout, Hyperuricemia and Crystal-Associated Disease Network (G-CAN) discusses the evidence and/or lack thereof for the management of gout in people with CKD and identifies key areas for research to address the challenges faced in the management of gout and CKD. These discussions, which address areas for research both in general as well as related to specific medications used to treat gout flares or as ULT, are supported by separately published G-CAN systematic literature reviews. This Consensus Statement is not intended as a guideline for the management of gout in CKD; rather, it analyses the available literature on the safety and efficacy of drugs used in gout management to identify important gaps in knowledge and associated areas for research.

National Estimates of CKD Prevalence and Potential Impact of Estimating Glomerular Filtration Rate Without Race.

BACKGROUND: The implications of removing the adjustment for Black race in equations to eGFR on the prevalence of CKD and management strategies are incompletely understood. METHODS: We estimated changes in CKD prevalence and the potential effect on therapeutic drug prescriptions and prediction of kidney failure if race adjustment were removed from the CKD-EPI GFR estimating equation. We used cross-sectional and longitudinal data from adults aged ≥18 years in the National Health and Nutrition Examination Survey (NHANES) from 2015 to 2016, and the Veterans Affairs (VA) Health Care System in 2015. In the VA cohort, we assessed use of common medications that require dose adjustment on the basis of kidney function, and compared the prognostic accuracy of the Kidney Failure Risk Equation with versus without race adjustment of eGFR. RESULTS: The prevalence of CKD among Black adults increased from 5.2% to 10.6% in NHANES, and from 12.4% to 21.6% in the VA cohort after eliminating race adjustment. Among Black veterans, 41.0% of gabapentin users, 33.5% of ciprofloxacin users, 24.0% of metformin users, 6.9% of atenolol users, 6.6% of rosuvastatin users, and 5.8% of tramadol users were reclassified to a lower eGFR for which dose adjustment or discontinuation is recommended. Without race adjustment of eGFR, discrimination of the Kidney Failure Risk Equation among Black adults remained high and calibration was marginally improved overall, with better calibration at higher levels of predicted risk. CONCLUSIONS: Removal of race adjustment from CKD-EPI eGFR would double the estimated prevalence of CKD among Black adults in the United States. Such a change is likely to affect a sizeable number of drug-dosing decisions. It may also improve the accuracy of kidney failure risk prediction among higher-risk Black adults.

Low Health Literacy is Associated with the Onset of CKD during the Life Course.

BACKGROUND: Health literacy, the ability to deal with information related to one's health, is a predictor of health outcomes in CKD. However, research has not explored whether low health literacy predicts the onset of CKD. METHODS: We used data from participants of Lifelines, a prospective population-based cohort study of individuals living in The Netherlands, to assess the share of individuals with low health literacy by eGFR category, whether low health literacy is associated with CKD onset in the general population and in the subgroup of older adults, and whether established CKD risk factors mediate this association. RESULTS: In the total sample of 93,885 adults (mean follow-up 3.9 years), low health literacy was more likely among individuals in worse eGFR categories, increasing from 26.4% in eGFR category 1 to 50.0% in category 5 (P=0.02). Low health literacy, compared with adequate health literacy, was associated with the onset of CKD in the total sample (3.0% versus 2.1%) and in the subgroup of older adults (13.4% versus 11.3%), with odds ratios (ORs) of 1.44 (95% confidence interval (95% CI), 1.31 to 1.59) and 1.21 (95% CI, 1.04 to 1.41), respectively. After adjustment for sex, age, education, and income, health literacy was associated with CKD onset only in older adults (OR, 1.25; 95% CI, 1.04 to 1.50). This association was mediated by hypertension and high body mass index (BMI) in the crude model, but only by BMI after adjustment (with BMI explaining 18.8% of the association). CONCLUSIONS: Low health literacy is a risk factor for CKD onset among older adults, which suggests that CKD prevention might benefit from strategies to address low health literacy.

Subtyping CKD Patients by Consensus Clustering: The Chronic Renal Insufficiency Cohort (CRIC) Study.

BACKGROUND: CKD is a heterogeneous condition with multiple underlying causes, risk factors, and outcomes. Subtyping CKD with multidimensional patient data holds the key to precision medicine. Consensus clustering may reveal CKD subgroups with different risk profiles of adverse outcomes. METHODS: We used unsupervised consensus clustering on 72 baseline characteristics among 2696 participants in the prospective Chronic Renal Insufficiency Cohort (CRIC) study to identify novel CKD subgroups that best represent the data pattern. Calculation of the standardized difference of each parameter used the cutoff of ±0.3 to show subgroup features. CKD subgroup associations were examined with the clinical end points of kidney failure, the composite outcome of cardiovascular diseases, and death. RESULTS: The algorithm revealed three unique CKD subgroups that best represented patients' baseline characteristics. Patients with relatively favorable levels of bone density and cardiac and kidney function markers, with lower prevalence of diabetes and obesity, and who used fewer medications formed cluster 1 (n=1203). Patients with higher prevalence of diabetes and obesity and who used more medications formed cluster 2 (n=1098). Patients with less favorable levels of bone mineral density, poor cardiac and kidney function markers, and inflammation delineated cluster 3 (n=395). These three subgroups, when linked with future clinical end points, were associated with different risks of CKD progression, cardiovascular disease, and death. Furthermore, patient heterogeneity among predefined subgroups with similar baseline kidney function emerged. CONCLUSIONS: Consensus clustering synthesized the patterns of baseline clinical and laboratory measures and revealed distinct CKD subgroups, which were associated with markedly different risks of important clinical outcomes. Further examination of patient subgroups and associated biomarkers may provide next steps toward precision medicine.

Impact of postoperative acute kidney injury on predicting the upstaging of chronic kidney disease after robot-assisted partial nephrectomy.

INTRODUCTION: The aim of our study was to assess the impact of acute kidney injury (AKI) on postoperative upstaging of chronic kidney disease (CKD) after robot-assisted partial nephrectomy (RAPN). METHODS: This study consisted of 110 patients who had undergone RAPN and were followed up for at least 6 months after surgery. Patients were classified as AKI or non-AKI based on their serum creatinine level and estimated glomerular filtration rate within 7 days after surgery. Patient characteristics, outcome of RAPN and estimated glomerular filtration rate, and CKD upstage 6 months after surgery were compared between the AKI and non-AKI groups. RESULTS: A total of 26 patients (23.6%) experienced AKI after surgery. RENAL (radius, exophytic/endophitic properties, nearness of the tumor to the collecting system or sinus, anterior/posterior, location relative to the polar lines) nephrometry scores were ≥7 for 22 (84.6%) in the AKI group and 39 (46.4%) in the non-AKI group (P = .0006). A significantly smaller proportion of patients in the AKI group than in the non-AKI group recovered 90% of baseline function (38.5% vs 81.0%, P < .0001). CKD upstaging occurred in a total of 27 patients 24.5%) and in a significantly larger proportion of patients in the AKI group than in the non-AKI group (42.3% vs 19.0%, P = .0160). There was no significant difference in characteristics and perioperative outcomes between the patients with and without CKD, except for in those experiencing AKI. CONCLUSION: After RAPN, AKI can be associated with CKD upstaging.

Prevalence of foot disorders according to chronic kidney disease stage.

BACKGROUND: Chronic kidney disease (CKD) is a public health disease that affects 15.1% of the adult population. Although a high prevalence (94.1%) of skin disorders has been detected in people on haemodialysis or with advanced CKD, few studies have analysed foot disorders at initial CKD stages. OBJECTIVES: To analyse the prevalence of foot disorders according to CKD stage. PARTICIPANTS: A total of 209 people with a mean age of 73.2 ± 13.8 years (52.0% women) in the nephrology department of Virgen del Puerto Hospital, Plasencia (Spain) were examined from January 2018 to April 2019. MEASUREMENTS: CKD stages were determined by nephrologists according to the Kidney Disease Improving Global Outcomes Guideline. An expert podiatrist identified foot disorders. Data were statistically treated with the IBM SPSS Statistics. Comparisons between variables were analysed by the χ2  test or Fisher's exact test, with a significance level of less than 5%. RESULTS: The prevalence of foot disorders was high for skin disorders (97.6% dermatopathies and 66.0% keratopathies), nail disorders (98.5% onychopathies) and toe deformities (97.1%). People at initial and intermediate stages presented more keratopathies (hyperkeratosis at G1 and G3a and pinch callus at G3a). Stage G1 showed fewer changes in nail colour and half and half nails. Stage G4 showed more claw toes and hematoma and stage G5 more Beau's lines, changes in skin colour, hematomas and thin shiny skin. CONCLUSIONS: The high prevalence of foot disorders detected in people with CKD requires specific and personalised professional care to relieve symptoms and avoid complications, helping to improve the quality of life of people with this condition.

Observations from a teaching hospital in Ireland: changing from MDRD to CKD-EPI eGFR in routine practice.

Estimates of glomerular filtration rate (eGFR) help assess kidney function. Estimated GFR can be used to classify patients into one of six Chronic Kidney Disease (CKD) categories as recommended by the Kidney Disease Improving Global Outcomes clinical practice guidelines; CKD1 ≥90, CKD2 60-89, CKD3a 45-59, CKD3b 30-44, CKD4 15-29 or CKD5 ≤15 mL/min/1.73 m2 The Modification of Diet and Renal Disease (MDRD) study formula was widely adopted to calculate eGFR. The CKD Epidemiology Collaboration (CKD-EPI) formula improved accuracy of CKD staging at eGFR ≥60 mL/min/1.73 m2 MDRD and CKD-EPI eGFR were calculated on 111 444 serum creatinine results from adult patients measured as part of the routine Clinical Chemistry service. Application of CKD-EPI eGFR reclassified 18% to a lower (13.9%) or higher (4.0%) CKD stage. CKD staging was lower when <65 years and higher when ≥65 years. Females were more often reclassified compared with males (2.6% vs 0.8%). Overall, CKD-EPI eGFR classified less with CKD (stages 3a-5), unless ≥75 years. Older males and inpatients had higher CKD stages when CKD-EPI eGFR was applied. It has been recommended to replace MDRD eGFR with CKD-EPI eGFR. In general, doing this will have little impact, however, for some patients their CKD classification will be different.

Empagliflozin and Cardiovascular and Kidney Outcomes across KDIGO Risk Categories: Post Hoc Analysis of a Randomized, Double-Blind, Placebo-Controlled, Multinational Trial.

BACKGROUND AND OBJECTIVES: In the Empagliflozin Cardiovascular Outcome Event Trial in Type 2 Diabetes Mellitus Patients (EMPA-REG Outcome), empagliflozin, in addition to standard of care, significantly reduced risk of cardiovascular death by 38%, hospitalization for heart failure by 35%, and incident or worsening nephropathy by 39% compared with placebo in patients with type 2 diabetes and established cardiovascular disease. Using EMPA-REG Outcome data, we assessed whether the Kidney Disease Improving Global Outcomes (KDIGO) CKD classification had an influence on the treatment effect of empagliflozin. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Patients with type 2 diabetes, established atherosclerotic cardiovascular disease, and eGFR≥30 ml/min per 1.73 m2 at screening were randomized to receive empagliflozin 10 mg, empagliflozin 25 mg, or placebo once daily in addition to standard of care. Post hoc, we analyzed cardiovascular and kidney outcomes, and safety, using the two-dimensional KDIGO classification framework. RESULTS: Of 6952 patients with baseline eGFR and urinary albumin-creatinine ratio values, 47%, 29%, 15%, and 8% were classified into low, moderately increased, high, and very high KDIGO risk categories, respectively. Empagliflozin showed consistent risk reductions across KDIGO categories for cardiovascular outcomes (P values for treatment by subgroup interactions ranged from 0.26 to 0.85) and kidney outcomes (P values for treatment by subgroup interactions ranged from 0.16 to 0.60). In all KDIGO risk categories, placebo and empagliflozin had similar adverse event rates, the notable exception being genital infection events, which were more common with empagliflozin for each category. CONCLUSIONS: The observed effects of empagliflozin versus placebo on cardiovascular and kidney outcomes were consistent across the KDIGO risk categories, indicating that the effect of treatment benefit of empagliflozin was unaffected by baseline CKD status. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER: EMPA-REG OUTCOME, NCT01131676.

Novel Mechanistic PBPK Model to Predict Renal Clearance in Varying Stages of CKD by Incorporating Tubular Adaptation and Dynamic Passive Reabsorption.

Chronic kidney disease (CKD) has significant effects on renal clearance (CLr ) of drugs. Physiologically-based pharmacokinetic (PBPK) models have been used to predict CKD effects on transporter-mediated renal active secretion and CLr for hydrophilic nonpermeable compounds. However, no studies have shown systematic PBPK modeling of renal passive reabsorption or CLr for hydrophobic permeable drugs in CKD. The goal of this study was to expand our previously developed and verified mechanistic kidney model to develop a universal model to predict changes in CLr in CKD for permeable and nonpermeable drugs that accounts for the dramatic nonlinear effect of CKD on renal passive reabsorption of permeable drugs. The developed model incorporates physiologically-based tubular changes of reduced water reabsorption/increased tubular flow rate per remaining functional nephron in CKD. The final adaptive kidney model successfully (absolute fold error (AFE) all < 2) predicted renal passive reabsorption and CLr for 20 permeable and nonpermeable test compounds across the stages of CKD. In contrast, use of proportional glomerular filtration rate reduction approach without addressing tubular adaptation processes in CKD to predict CLr generated unacceptable CLr predictions (AFE = 2.61-7.35) for permeable compounds in severe CKD. Finally, the adaptive kidney model accurately predicted CLr of para-amino-hippuric acid and memantine, two secreted compounds, in CKD, suggesting successful integration of active secretion into the model, along with passive reabsorption. In conclusion, the developed adaptive kidney model enables mechanistic predictions of in vivo CLr through CKD progression without any empirical scaling factors and can be used for CLr predictions prior to assessment of drug disposition in renal impairment.

Impact of Chronic Kidney Disease Classification on New-Onset Atrial Fibrillation in the General Population　- The TAMA MED Project-AF and CKD.

BACKGROUND: Atrial fibrillation (AF) and chronic kidney disease (CKD) are known risk factors for each other. In Tama City in Tokyo, 12-lead ECG and serum creatinine concentration have been included as essential examinations in specific health checkups to diagnose AF and CKD. In the present study, we investigated the impact of CKD classification on new-onset AF in the general population.Methods and Results:Among 13,478 subjects aged 40-74 years at entry (age, 65.6±7.8 years; men, 42.0%), renal impairment with estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2and proteinuria were found in 15.5% and 4.6%, respectively. CKD severity in individual subjects was classified according to a heatmap of the Japanese Society of Nephrology as 81.3% in the green, 15.1% in the yellow, 2.5% in the orange, and 0.9% in the red. Of those without AF in 2012, it had developed in 115 up to 2017; thus, the new-onset AF incidence rate was 2.6/1,000 person-years. Hazard ratios and 95% confidence intervals for new-onset AF in each CKD classification were 1.50 (0.93-2.41, P=0.097) in the yellow, 2.53 (1.03-6.23, P=0.044) in the orange, and 4.65 (1.47-14.70, P=0.009) in the red compared with the green as a reference. CONCLUSIONS: CKD classification was significantly associated with new-onset AF in the general population. Thus, it would be useful for risk stratification of new-onset AF. Renal function evaluation is recommended in health checkups.

[The definition of chronic kidney disease in a context of aging population].

Chronic kidney disease (CKD) is a progressively chronic disease that carries a high burden of morbidity and mortality and is associated with significant healthcare utilization and costs. Recent trends shown that the prevalence of CKD is stable in Europe and USA, whereas tends to decline in some countries with a high standard of care. According to international guidelines, chronic kidney disease (CKD) is defined as the presence of kidney damage or a glomerular filtration rate (eGFR) less than 60 ml/min. This staging method has a main drawback, its imprecise assessment of renal function at the extremes of the age bracket: the use of a fixed threshold value (glomerular filtration rate [GFR <60 ml /min]) to define chronic renal failure appears an imprecise measure in the young and in the elderly. In these two groups, in fact, the measurement of GFR is difficult to categorize in a "rigid" system of classification. The reduction of the GFR with aging is due to a complex process that leads to a steady reduction of the functioning nephrons over 40 years of age. Taken together, these findings should spur us to adopt a new definition of CKD. An age-adapted definition of CKD could be a good solution to avoid a diagnosis of CKD in elderly patients (GFR >45 ml/min) when there are no prognostic implications on survival. The adoption of this new definition would also reduce the high prevalence of the disease in the general population, with a beneficial reduction of the costs associated with monitoring a mildly decreased eGFR.

Spectrum of biopsy proven renal diseases in Central China: a 10-year retrospective study based on 34,630 cases.

Chronic kidney diseases have become a major issue worldwide. The spectrum of biopsy proven renal diseases differs between locations and changes over time. It is therefore essential to describe the local epidemiological trends and the prevalence of renal biopsy in various regions to shine new light on the pathogenesis of various renal diseases and provide a basis for further hypothesis-driven research. We retrospectively analyzed 34,630 hospitalized patients undergoing native renal biopsy between January 1, 2009 and December 31, 2018. Indications for renal biopsy and histological diagnosis were analyzed to describe the prevalence of renal biopsy, and changing prevalence between period 1 (2009-2013) and period 2 (2014-2018) were further analyzed. Nephrotic syndrome (NS) was the most common indication for biopsy. Membranous nephropathy (MN, 24.96%) and IgA nephropathy (IgAN, 24.09%) were the most common primary glomerulonephritis (PGN). MN was most common in adults, with IgAN more prevalent in children. Lupus nephritis (LN) was the most common secondary glomerulonephritis (SGN) in adults, while Henöch-Schönlein purpura nephritis (HSPN) in children. The prevalence of MN increased significantly and nearly doubled from period 1 (15.98%) to period 2 (30.81%) (P = 0.0004). The same trend appeared with membranoproliferative glomerulonephritis (MPGN), diabetic nephropathy (DN) and obesity-related glomerulopathy (ORG), while the frequencies of minimal change disease (MCD), focal segmental glomerulosclerosis (FSGS), LN and hepatitis B associated glomerulonephritis (HBV-GN) significantly decreased between the two intervals. NS was the most common indication for biopsy across all age groups and genders. MN has overtaken IgAN to become the most common PGN in adults, while IgAN was the most common PGN in children. LN was the most common SGN in adults, and HSPN the most common in children.