The prognostic value of triglyceride-glucose index to adverse renal outcomes in patients with type 2 diabetes mellitus: results from the cohort study of ACCORD.

BACKGROUND: The triglyceride-glucose (TyG) index is a new and good biomarker of insulin resistance (IR). The prognostic utility of the TyG index for patients with type 2 diabetes mellitus (T2DM) remains uncertain. Our study seeks to elucidate the connection between the TyG index and adverse renal outcomes within a T2DM population, while also examining if these relationships are influenced by subgroup variations. METHODS: We analyzed data from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial, involving 10,196 T2DM participants, to assess the link between triglyceride-glucose levels and adverse renal outcomes. This evaluation included Restricted Cubic Spline (RCS) analysis, Kaplan-Meier survival analysis, and Multivariate Cox proportional regression. Additionally, we examined the interaction between subgroups concerning adverse renal outcomes. RESULTS: During a 7-year follow-up, 5824 patients (57.1%) experienced worsening renal function, 2309 patients (23.2%) developed albuminuria, and 280 patients (2.7%) advanced to renal failure. After adjusting for a range of confounding variables, triglyceride-glucose levels were significantly linked to both worsening renal function (p < 0.001) and the onset of albuminuria (p = 0.020). Nonetheless, no significant association was observed between triglyceride-glucose levels and renal failure (p = 0.247). Furthermore, there was no significant subgroups interaction to the associations between TyG levels and adverse renal outcomes. CONCLUSION: Our study underscores the significant relationship between the triglyceride-glucose index and the risk of adverse renal outcomes in patients with T2DM. The TyG index, as a readily calculable measure, offers clinicians a valuable tool for anticipating the risk of adverse renal outcomes in this patient population.

The diagnosis of acute interstitial nephritis caused by infection versus antibiotic-induced interstitial nephritis: a narrative review.

Acute interstitial nephritis (AIN) is a significant contributor to acute kidney injury and can be attributed to a variety of factors, including but not limited to allergens or drugs, infections, autoimmune or systemic diseases, and idiopathic forms of the disease. In some cases, AIN requires a therapeutic action according to a single specific etiology by handling the offending agent and applying an immunosuppressant. Although AIN can be diagnosed through renal biopsy, it is not able to pinpoint the precise cause when multiple causes are suspected to be present simultaneously. Such situations arise when a patient suffering from infection develops AIN during antibiotic therapy, the exact causative factor of which becomes a challenge for the clinicians to determine. This is attributed to the different approaches employed in different etiologies, wherein clinicians are required to maintain the current antibiotic therapy or augment the dose in cases of infection as AIN etiology, without resorting to immunosuppressant therapy as the primary objective is infection killing. In contrast, antibiotics as an etiology for AIN require an alternative drug from the antibiotics group, along with an immunosuppressant. In the interim, delaying the identification of the precise cause may result in interstitial fibrosis and chronic kidney disease. This narrative review highlights certain findings that can be typical of infection-associated ATIN compared with antibiotic-associated ATIN based on clinical history and physical examination, clinical presentation of different antibiotic drug classes, histopathological features, classical and novel biomarkers, serum and urine cytokines and chemokines, cellular biomarkers, and genetic biomarkers. Although these findings cannot provide conclusive and clear recommendations that can be useful in the clinical practice, they can entice researchers to conduct original research on these features to discover clear recommendations.

The prediction of in-hospital mortality in elderly patients with sepsis-associated acute kidney injury utilizing machine learning models.

Background: Sepsis-associated acute kidney injury (SA-AKI) is a severe complication associated with poorer prognosis and increased mortality, particularly in elderly patients. Currently, there is a lack of accurate mortality risk prediction models for these patients in clinic. Objectives: This study aimed to develop and validate machine learning models for predicting in-hospital mortality risk in elderly patients with SA-AKI. Methods: Machine learning models were developed and validated using the public, high-quality Medical Information Mart for Intensive Care (MIMIC)-IV critically ill database. The recursive feature elimination (RFE) algorithm was employed for key feature selection. Eleven predictive models were compared, with the best one selected for further validation. Shapley Additive Explanations (SHAP) values were used for visualization and interpretation, making the machine learning models clinically interpretable. Results: There were 16,154 patients with SA-AKI in the MIMIC-IV database, and 8426 SA-AKI patients were included in this study (median age: 77.0 years; female: 45%). 7728 patients excluded based on these criteria. They were randomly divided into a training cohort (5,934, 70%) and a validation cohort (2,492, 30%). Nine key features were selected by the RFE algorithm. The CatBoost model achieved the best performance, with an AUC of 0.844 in the training cohort and 0.804 in the validation cohort. SHAP values revealed that AKI stage, PaO2, and lactate were the top three most important features contributing to the CatBoost model. Conclusion: We developed a model capable of predicting the risk of in-hospital mortality in elderly patients with SA-AKI.

Peroxiredoxin 1 aggravates acute kidney injury by promoting inflammation through Mincle/Syk/NF-κB signaling.

Damage-associated molecular patterns (DAMPs) are a cause of acute kidney injury (AKI). Our knowledge of these DAMPs remains incomplete. Here, we report serum peroxiredoxin 1 (Prdx1) as a novel DAMP for AKI. Lipopolysaccharide (LPS) and kidney ischemia/reperfusion injury instigated AKI with concurrent increases in serum Prdx1 and reductions of Prdx1 expression in kidney tubular epithelial cells. Genetic knockout of Prdx1 or use of a Prdx1-neutralizing antibody protected mice from AKI and this protection was impaired by introduction of recombinant Prdx1 (rPrdx1). Mechanistically, lipopolysaccharide increased serum and kidney proinflammatory cytokines, macrophage infiltration, and the content of M1 macrophages. All these events were suppressed in Prdx1-/- mice and renewed upon introduction of rPrdx1. In primary peritoneal macrophages, rPrdx1 induced M1 polarization, activated macrophage-inducible C-type lectin (Mincle) signaling, and enhanced proinflammatory cytokine production. Prdx1 interacted with Mincle to initiate acute kidney inflammation. Of note, rPrdx1 upregulated Mincle and the spleen tyrosine kinase Syk system in the primary peritoneal macrophages, while knockdown of Mincle abolished the increase in activated Syk. Additionally, rPrdx1 treatment enhanced the downstream events of Syk, including transcription factor NF-κB signaling pathways. Furthermore, serum Prdx1 was found to be increased in patients with AKI; the increase of which was associated with kidney function decline and inflammatory biomarkers in patient serum. Thus, kidney-derived serum Prdx1 contributes to AKI at least in part by activating Mincle signaling and downstream pathways.

Machine learning for the prediction of all-cause mortality in patients with sepsis-associated acute kidney injury during hospitalization.

Background: Sepsis-associated acute kidney injury (S-AKI) is considered to be associated with high morbidity and mortality, a commonly accepted model to predict mortality is urged consequently. This study used a machine learning model to identify vital variables associated with mortality in S-AKI patients in the hospital and predict the risk of death in the hospital. We hope that this model can help identify high-risk patients early and reasonably allocate medical resources in the intensive care unit (ICU). Methods: A total of 16,154 S-AKI patients from the Medical Information Mart for Intensive Care IV database were examined as the training set (80%) and the validation set (20%). Variables (129 in total) were collected, including basic patient information, diagnosis, clinical data, and medication records. We developed and validated machine learning models using 11 different algorithms and selected the one that performed the best. Afterward, recursive feature elimination was used to select key variables. Different indicators were used to compare the prediction performance of each model. The SHapley Additive exPlanations package was applied to interpret the best machine learning model in a web tool for clinicians to use. Finally, we collected clinical data of S-AKI patients from two hospitals for external validation. Results: In this study, 15 critical variables were finally selected, namely, urine output, maximum blood urea nitrogen, rate of injection of norepinephrine, maximum anion gap, maximum creatinine, maximum red blood cell volume distribution width, minimum international normalized ratio, maximum heart rate, maximum temperature, maximum respiratory rate, minimum fraction of inspired O2, minimum creatinine, minimum Glasgow Coma Scale, and diagnosis of diabetes and stroke. The categorical boosting algorithm model presented significantly better predictive performance [receiver operating characteristic (ROC): 0.83] than other models [accuracy (ACC): 75%, Youden index: 50%, sensitivity: 75%, specificity: 75%, F1 score: 0.56, positive predictive value (PPV): 44%, and negative predictive value (NPV): 92%]. External validation data from two hospitals in China were also well validated (ROC: 0.75). Conclusions: After selecting 15 crucial variables, a machine learning-based model for predicting the mortality of S-AKI patients was successfully established and the CatBoost model demonstrated best predictive performance.

Identification of common molecular signatures of SARS-CoV-2 infection and its influence on acute kidney injury and chronic kidney disease.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the main cause of COVID-19, causing hundreds of millions of confirmed cases and more than 18.2 million deaths worldwide. Acute kidney injury (AKI) is a common complication of COVID-19 that leads to an increase in mortality, especially in intensive care unit (ICU) settings, and chronic kidney disease (CKD) is a high risk factor for COVID-19 and its related mortality. However, the underlying molecular mechanisms among AKI, CKD, and COVID-19 are unclear. Therefore, transcriptome analysis was performed to examine common pathways and molecular biomarkers for AKI, CKD, and COVID-19 in an attempt to understand the association of SARS-CoV-2 infection with AKI and CKD. Three RNA-seq datasets (GSE147507, GSE1563, and GSE66494) from the GEO database were used to detect differentially expressed genes (DEGs) for COVID-19 with AKI and CKD to search for shared pathways and candidate targets. A total of 17 common DEGs were confirmed, and their biological functions and signaling pathways were characterized by enrichment analysis. MAPK signaling, the structural pathway of interleukin 1 (IL-1), and the Toll-like receptor pathway appear to be involved in the occurrence of these diseases. Hub genes identified from the protein-protein interaction (PPI) network, including DUSP6, BHLHE40, RASGRP1, and TAB2, are potential therapeutic targets in COVID-19 with AKI and CKD. Common genes and pathways may play pathogenic roles in these three diseases mainly through the activation of immune inflammation. Networks of transcription factor (TF)-gene, miRNA-gene, and gene-disease interactions from the datasets were also constructed, and key gene regulators influencing the progression of these three diseases were further identified among the DEGs. Moreover, new drug targets were predicted based on these common DEGs, and molecular docking and molecular dynamics (MD) simulations were performed. Finally, a diagnostic model of COVID-19 was established based on these common DEGs. Taken together, the molecular and signaling pathways identified in this study may be related to the mechanisms by which SARS-CoV-2 infection affects renal function. These findings are significant for the effective treatment of COVID-19 in patients with kidney diseases.

[Status Quo and Research Progress in Diagnosis and Treatment of Patients With Diabetes Mellitus and Chronic Kidney Disease].

As the incidence of diabetes mellitus is rapidly increasing worldwide,that of related complications,such as diabetic kidney disease(DKD),also increases,conferring a heavy economic burden on the patients,families,society,and government.Diabetes mellitus complicated with chronic kidney disease(CKD)includes DKD and the CKD caused by other reasons.Because of the insufficient knowledge about CKD,the assessment of diabetes mellitus complicated with CKD remains to be improved.The therapies for diabetes mellitus complicated with CKD focus on reducing the risk factors.In clinical practice,DKD may not be the CKD caused by diabetes.According to clinical criteria,some non-diabetic kidney disease may be misdiagnosed as DKD and not be treated accurately.This review summarizes the status quo and research progress in the assessment,diagnosis,and treatment of diabetes mellitus complicated with CKD and predicts the directions of future research in this field.

The Gut Microbiota Dysbiosis in Preeclampsia Contributed to Trophoblast Cell Proliferation, Invasion, and Migration via lncRNA BC030099/NF-κB Pathway.

Background: Preeclampsia (PE) is the main reason of maternal and perinatal morbidity and mortality. Gut microbiota imbalance in PE patients is accompanied by elevated serum lipopolysaccharide (LPS) levels, but whether it affects the occurrence and development of PE, the underlying mechanism is not clear. This paper intends to investigate the relationship between lncRNA BC030099, inflammation, and gut microbiota in PE. Methods: The feces of the patients were collected, and gut microbiota changes were assessed by 16S rRNA sequencing and pathway analysis by PICRUSt. Next, we examined LPS and lncRNA BC030099 levels in feces or placenta of PE patients. Then, we knocked down lncRNA BC030099 in HTR-8/SVneo cells and added the NF-κB pathway inhibitor JSH-23. CCK-8 and Transwell assays were performed to determine cell proliferation, migration, and invasion. Western blot was utilized to evaluate MMP2, MMP9, snail, and E-cadherin, p-IκBα, IκBα, and nuclear NF-κB p65 levels. IL-6, IL-1ß, and TNF-α levels were examined by ELISA. Results: Gut microbiota was altered in PE patients, and microbial genes associated with LPS biosynthesis were significantly elevated in gut microbiota in the PE group. LPS level in feces and placenta of PE group was significantly elevated. lncRNA BC030099 level in placenta of PE group was also notably promoted. Knockdown of lncRNA BC030099 promoted HTR-8/SVneo cell proliferation, migration, and invasion. Knockdown of lncRNA BC030099 also elevated MMP2, MMP9, and snail levels and repressed E-cadherin level. In addition, lncRNA BC030099 affected NF-κB pathway. Furthermore, NF-κB inhibitor reversed HTR-8/SVneo cell proliferation, invasion, and migration induced by LPS. Conclusions: The gut microbiota dysbiosis in PE contributed to HTR-8/SVneo cell proliferation, invasion, and migration via lncRNA BC030099/NF-κB pathway.

Serum Sortilin Is Associated with Coronary Artery Calcification and Cardiovascular and Cerebrovascular Events in Maintenance Hemodialysis Patients.

OBJECTIVE: To analyze the role of serum sortilin in coronary artery calcification (CAC) and cardiovascular and cerebrovascular events (CCE) in maintenance hemodialysis (MHD) patients. METHODS: One hundred eleven patients with MHD ≥3 months were included in this study. The general data, clinical features, hematological data, and medication history of the patients were recorded. Eighty-five cases were examined by vascular color Doppler ultrasound, cardiac color Doppler ultrasound, lateral lumbar radiography, and coronary artery calcification score. The patients were followed up for a median time of 45 months. The primary endpoint was CCE or death from a vascular event, and the role of sortilin in this process was analyzed. RESULTS: Among 85 MHD patients, 51 cases (60.00%) had different degrees of CAC. There were significant differences in diabetes, dialysis time, serum phosphorus, calcium-phosphorus product, medical history of phosphate binders, sortilin, and carotid artery plaque between 4 different degrees of calcification groups (p < 0.05). Logistic regression analysis showed that diabetes (OR = 5.475; 95% CI: 1.794-16.71, p = 0.003), calcium-phosphorus product (OR = 2.953; 95% CI: 1.198-7.279, p = 0.019), and sortilin (OR = 1.475 per 100 pg/mL; 95% CI: 1.170-1.858, p = 0.001) were independent risk factors for CAC. During the follow-up, 28 cases of 111 patients (25.23%) suffered from CCE. There were significant differences in CCE between mild, moderate, and severe CAC groups and noncalcification groups (p < 0.05). Cox regression analysis showed that diabetes mellitus (HR 3.424; 95% CI: 1.348-8.701, p = 0.010), CAC (HR 5.210; 95% CI: 1.093-24.83, p = 0.038), and serum sortilin (HR = 8.588; 95% CI: 1.919-38.43, p = 0.005) were independent risk factors for CCE. Besides, we proposed a cutoff value of 418 pg/mL for serum sortilin level, which was able to predict the occurrence of CCE with 75.0% sensitivity and 71.9% specificity. The area under the curve was 0.778 (95% CI: 0.673-0.883). CONCLUSION: Sortilin is newly found to be independently associated with CAC and CCE in MHD patients.

Long Non-coding RNA ENST00000453774.1 Confers an Inhibitory Effect on Renal Fibrosis by Inhibiting miR-324-3p to Promote NRG1 Expression.

Progressive or chronic renal diseases arise from a process of destructive renal fibrosis. Therefore, the molecular basis of renal fibrosis has attracted increasing attention. In this investigation, we set out to elucidate the potential interaction among long non-coding RNA ENST00000453774.1 (lncRNA 74.1), microRNA-324-3p (miR-324-3p), and NRG1, and to investigate their roles in the context of cellular autophagy and renal fibrosis. We collected 30 renal fibrosis tissue samples for analysis. In other studies, HK-2 cells were stimulated with TGF-ß1 to induce a cell model of renal fibrosis, followed by alteration on the expression of lncRNA 74.1, miR-324-3p, or NRG1, or by the addition of AKT activator SC79 in the HK-2 cells. The expression levels of lncRNA 74.1, miR-324-3p, NRG1, autophagy-related proteins (ATG5, ATG7, LC3II/I, and P62), and the corresponding fibrosis markers (Collagen I, Fibronectin, and α-SMA) were subsequently determined using various assay methods. In addition, the proportion of LC3 positive cells and number of autophagosomes were recorded. Results revealed that lncRNA 74.1 and NRG1 were poorly expressed and miR-324-3p was highly expressed in renal fibrosis tissues and modeled cells. LncRNA 74.1 could bind to miR-324-3p, which led to upregulated NRG1 expression and inhibition of the PI3K/AKT signaling pathway. Meanwhile, overexpression of lncRNA 74.1 or down-regulation of miR-324-3p increased the levels of ATG5, ATG7, LC3II, and LC3I, and decreased levels of P62, Collagen I, Fibronectin, and α-SMA, accompanied by elevated proportions of LC3 positive cells and autophagosomes. Findings concur in showing that lncRNA 74.1 could induce cellular autophagy and alleviate renal fibrosis by regulating the miR-324-3p-mediated NRG1/PI3K/AKT axis. This axis may thus present a potential molecular target in renal fibrosis treatment.

Antiviral treatment and prognosis in patients undergoing maintenance hemodialysis due to hepatitis C virus. / ç»´æŒæ€§è¡€æ¶²é€æžä¸™åž‹è‚ç‚Žç— æ¯’æ„ŸæŸ“æ‚£è€ çš„æŠ—ç— æ¯’æ²»ç–—åŠé¢„åŽ.

OBJECTIVES: Maintenance hemodialysis (MHD) is one of the important renal replacement therapies for patients with end-stage renal disease. Hepatitis C virus (HCV) infection is a serious global public health problem. The proportion of MHD patients complicated with HCV infection and the risk of adverse prognosis are higher than those in the general population. Active antiviral treatment and prevention of reinfection is a combined treatment by nephrology and infection physicians. It is a widely accepted preventive measure to set hemodialysis buffer area for patients in treating HCV infection, but its effectiveness and safety still need to be further explored. Thus, the aim of this study is to explore the antiviral treatment and prognosis of MHD patients with HCV infection during hemodialysis. METHODS: A retrospective analysis for renal disease patients at 10 end-stage with long-term hemodialysis in the HCV area of the Blood Purification Center of Xiangya Hospital, Central South University. After standard antiviral drug treatment, the patient reached the cure standard for HCV infection. The buffer zone was set up in the Blood Purification Center by the Department of Nephrology of Xiangya Hospital since April 2017. Patients cured of HCV infection were transferred from the HCV area to the buffer zone for continuous dialysis, accompanied by monitoring serum HCV-RNA, anti-HCV antibody levels and changes in clinical biochemical indicators following the status of reinfection. RESULTS: Ten patients with HCV infection were finally cured after antiviral treatment, and there were no significant changes in clinical biochemical indicators before and after treatment. In the followed-up period after the transfer, the patient continued to be negative for HCV-RNA and positive for anti-HCV antibody. CONCLUSIONS: Direct antiviral therapy is safe and effective in MHD patients with HCV infection. Active antiviral therapy and transferring to the buffer area for dialysis are new and effective treatment modes for HCV patients during MHD.

Urinary magnesium predicts risk of cardiovascular disease in Chronic Kidney Disease stage 1-4 patients.

Observational studies on dietary or circulating magnesium and risk of cardiovascular disease (CVD) in Chronic Kidney Disease (CKD) stage 1-4 have reported no-to-modest inverse associations. 24 h Urinary magnesium concentration (24 h UMg), an indicator of intestinal magnesium absorption, may provide better insight into the connection of CKD progression. We examined 3179 participants aged 18-74 years with CKD stage 1-4 in the Chinese Cohort Study of Chronic Kidney Disease (C-STRIDE) study, a prospective population-based cohort study. Data were analysed using Spearman rank-order correlation coefficients for all comparisons. We also performed a time-to-event analysis of the data using the Kaplan-Meier survival model, Cox proportional hazard model and competing risk Fine and Gray subdistribution hazard model. During a median follow-up of 4.19 years (interquartile range, 3.43-5.09 years), when modelling end-stage renal disease (ESRD), CVD and death, 24 h UMg was associated with risk of CVD (HR, 1.612 (95% CI, 1.056-2.460)), while no significant association with ESRD and death endpoints could be detected. 24 h UMg risk variants display a modest association with CVD in CKD stage 1-4 patients. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT03041987. Registered January 1, 2012. (retrospectively registered) (https://www.clinicaltrials.gov/ct2/show/NCT03041987?term=Chinese+Cohort+Study+of+Chronic+Kidney+Disease+%28C-STRIDE%29&rank=1).

A meta-analysis of the clinical efficacy and safety of Bailing capsules in the treatment of nephrotic syndrome.

BACKGROUND: Nephrotic syndrome (NS) is extremely harmful to human health. Bailing capsules can reduce proteinuria and improve renal function in patients with NS. This meta-analysis aimed to evaluate the clinical efficacy and safety of Bailing capsules in the treatment of NS. METHODS: Systematic searches of the English-language databases PubMed, Cochrane, Embase, Medline, and Web of Science, as well as the Chinese-language databases China Academic Journals Full-text Database (CJFD), Wanfang Data, and Weipu (VIP), were performed. Randomized controlled trials (RCTs) of Bailing capsules in the treatment of NS were included in the meta-analysis. The total effective rate and adverse reaction rate were evaluated with relative risk (RR) and the quantitative data was evaluated with standardized mean difference (SMD) and 95% confidence interval (CI). The quality of the included articles was evaluated using RevMan5.3 software, and the "meta" package of R3.5.1 software was used for all other statistical analysis. RESULTS: A total of 20 papers involving 819 and 824 patients in the treatment group and the control group, respectively, were included. The total effective rate and adverse reaction rate after treatment were reported in 17 and 2 articles, respectively. The total effective rate of the treatment group was 1.22 times that of the control group (I2 =0%, fixed-effects model, 95% CI: 1.16, 1.27), and the adverse reaction rate of the treatment group was 0.22 times that of the control group (I2 =0%, fixed-effects model, 95% CI: 0.08, 0.63). The levels of blood urea nitrogen (BUN) and serum creatinine (SCr) before and after treatment were reported in 15 articles, with SMDs of -0.98 (I2 =50%, fixed-effects model, 95% CI: -1.10, -0.87) and -1.47 (I2 =96%, random-effects model, 95% CI: -2.08, -0.86), respectively. Meanwhile, 13 articles reported the level of 24-hour proteinuria before and after treatment, with an SMD of -1.25 (I2 =92%, fixed effects model, 95% CI: -1.73, -0.78). CONCLUSIONS: For NS patients, treatment with Bailing capsules can achieve higher clinical efficacy and a lower adverse reaction rate than conventional treatment in improving the function of kidney.

Retrospective Analysis of Clinical Outcomes in Patients with Immunoglobulin A Nephropathy and Persistent Hematuria Following Renin-Angiotensin System Blockade.

BACKGROUND Recent guidelines recommend that patients with immunoglobulin A nephropathy (IgAN) and proteinuria 0.5-1 g/d and >1 g/d be treated with long-term renin-angiotensin system blockade (RASB). This study investigated whether patients with IgAN and persistent hematuria, but without proteinuria, can benefit from RASB. MATERIAL AND METHODS IgAN patients with persistent hematuria at four centers were recruited from January 2013 to December 2018. Patients were divided into those who did and did not receive long-term RASB. The primary outcome was the appearance of proteinuria, and the secondary outcomes were the decreased percentage of hematuria, rate of decline in estimated glomerular filtration rate (eGFR) and final blood pressure. The effects of RASB on these outcomes were assessed by multivariate Cox regression models and propensity score matching. RESULTS Of the 110 eligible patients, 44 (40.0%) received RASB and 66 (60.0%) did not. Treated patients had higher diastolic pressure. The unadjusted primary outcome, the appearance of proteinuria, was significantly less frequent in individuals who were than who were not treated with RASB. Multivariate Cox regression showed that RASB reduced the risk of the primary outcome and the levels of hematuria. The rate of eGFR decline and final blood pressure did not differ in the two groups. CONCLUSIONS RASB reduced the risk of proteinuria development and increased the remission of hematuria in patients with IgAN who presented with persistent hematuria alone. RASB, however, did not affect blood pressure in patients without hypertension and did not affect the rate of eGFR decline.

Development of prognostic model for patients at CKD stage 3a and 3b in South Central China using computational intelligence.

BACKGROUND: Chronic kidney disease (CKD) stage 3 was divided into two subgroups by eGFR (45 mL/ min 1.73 m2). There is difference in prevalence of CKD, racial differences, economic development, genetic, and environmental backgrounds between China and Western countries. METHODS: We used a computational intelligence model (CKD stage 3 Modeling, CSM) to distinguish CKD stage 3 with CKD stage 3a/3b by data distribution rules, pearson correlation coefficient (PCC), spearman correlation (SCC) analysis, logistic regression (LR), random forest (RF), support vector machine (SVM), and neural network (Nnet) to develop Prognostic Model for patients with CKD stage 3a/3b in South Central China. Furthermore, we used RF to discover risk factors of progression of CKD stage 3a and 3b to CKD stage 5. 1090 cases of CKD stage 3 patients in Xiangya Hospital were collected. Among them, 455 patients progressed to CKD stage 5 in a median follow-up of 4 years (IQR 4.295, 4.489). RESULTS: We found that the common risk factors for progression of CKD stage 3a/3b to CKD stage 5 included albumin, creatinine, total protein, etc. Proteinuria, direct bilirubin, hemoglobin, etc. accounted for the progression from stage CKD stage 3a to stage 5. The risk factors for CKD stage 3b progression to stage 5 included low-density lipoprotein cholesterol, diabetes, eosinophil percentage, etc. CONCLUSIONS: CSM could be used as a point-of-care test to screen patients at high risk for disease progression, might allowing individualized therapeutic management.

Clinical characteristics of acute glomerulonephritis with presentation of nephrotic syndrome at onset in children.

BACKGROUND: Acute glomerulonephritis (AGN) is a common disease in children, which places a huge burden on developing countries. The prognosis of it may not always be good. However, the clinical characteristics of AGN with nephrotic syndrome (NS) at onset have not been fully clarified. METHODS: One hundred and thirteen cases were analyzed retrospectively. Clinical data, pathological results and prognosis between AGN with NS (AGN-NS) and AGN without NS (AGN-no-NS) were compared. RESULTS: Twenty (17.7%) of 113 patients were AGN-NS. The patients with AGN-NS were more likely to have hypertension (55.0% vs. 25.8%) and acute kidney injury (AKI) (50.0% vs. 17.2%). AKI was significantly related to the manifestation of AGN-NS in children (OR = 3.812, P = 0.040). Compared with the AGN-no-NS, the immunosuppressive treatments were more common in AGN-NS. A more severe pathological grade was significantly related to lower C3 fraction, estimated glomerular filtration rate (eGFR), and AKI, but not to the performance of AGN-NS. There was no difference in prognosis between the two groups. CONCLUSIONS: AKI was significantly associated with AGN-NS. The prognosis of AGN-NS and AGN-no-NS in our study was almost good. Given the fact that AGN-NS patients are more likely to use immunosuppressive therapy, the long-term outcome of AGN-NS warrants further research.

Role of Artificial Intelligence in Kidney Disease.

Artificial intelligence (AI), as an advanced science technology, has been widely used in medical fields to promote medical development, mainly applied to early detections, disease diagnoses, and management. Owing to the huge number of patients, kidney disease remains a global health problem. Challenges remain in its diagnosis and treatment. AI could take individual conditions into account, produce suitable decisions and promise to make great strides in kidney disease management. Here, we review the current studies of AI applications in kidney disease in alerting systems, diagnostic assistance, guiding treatment and evaluating prognosis. Although the number of studies related to AI applications in kidney disease is small, the potential of AI in the management of kidney disease is well recognized by clinicians; AI will greatly enhance clinicians' capacity in their clinical practice in the future.

The epidemiology and clinical information about COVID-19.

In December 2019, pneumonia of unknown cause occurred in Wuhan, Hubei Province, China. On 7 January 2020, a novel coronavirus, named as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was identified in the throat swab sample of one patient. The World Health Organization (WHO) announced the epidemic disease caused by SARS-CoV-2 as coronavirus disease 2019 (COVID-19). Currently, COVID-19 has spread widely around the world, affecting more than seventy countries. China, with a huge burden of this disease, has taken strong measures to control the spread and improve the curative rate of COVID-19. In this review, we summarized the epidemiological characteristics, clinical features, diagnosis, treatment, and prognosis of COVID-19. A comprehensive understanding will help to control the disease.

Efficacy of steroid and immunosuppressant combined therapy in Chinese patients with Henoch-Schönlein purpura nephritis: A retrospective study.

Suitable and efficient treatments for Henoch-Schönlein purpura nephritis (HSPN) with proteinuria remains unclear. Whether steroids combined with immunosuppressive agents improves prognosis compared to steroid therapy alone also remains controversial. This study explored whether combined therapy reduces proteinuria in HSPN patients with different pathological features. Chinese patients (n = 84) diagnosed with HSPN with proteinuria by renal biopsy between 2010 and 2019 were retrospectively studied. Patients were grouped into the steroid group (control) or the combined steroid and immunosuppressant group. Estimated glomerular filtration rate (eGFR) (mL/min/1.73 m2/y) and proteinuria were measured. The primary outcome progression was analyzed using Kaplan-Meier survival curves. The effect of the combined therapy on renal outcome was analyzed by multivariable Cox regression. Propensity score matching and sensitivity analysis were used to explore whether pathological features impacted prognosis. Patients who received combined steroid and immunosuppressant therapy were more likely to recover from HSPN and had proteinuria <3 g/24 h (P = 0.02) or 1 g/24 h (P = 0.03). Multiple Cox regression analysis confirmed that this decrease was independent of renin-angiotensin system blockers. Further sensitivity analysis showed that combined therapy was effective in patients with crescents (P = 0.02). However, combined steroid and immunosuppressant therapy was not more effective in patients with endocapillary hypercellularity (E), tubular atrophy/interstitial fibrosis (T), or segmental sclerosis (S). Combined steroid and immunosuppressant therapy was significantly associated with HSPN remission, and more effectively decreased proteinuria during the initial disease phase.

Oxidative stress contributes to vascular calcification in patients with chronic kidney disease.

Vascular calcification (VC) is a major cause of mortality in patients with chronic kidney disease (CKD). While elevations in serum phosphorus contribute to VC, we provide evidence here for a major role of oxidative stress (OS) in VC pathogenesis without an apparent increase in serum phosphorus in early CKD. In a rat model for stage 5 CKD (CKD5), we observed 1) robust increases of VC and OS, 2) significant reductions of smooth muscle 22 alpha (SM22α) and calponin, and 3) upregulations in Runt-related transcription factor 2 (RUNX2) and collagen I in vascular smooth muscle cells (VSMCs). Inhibition of OS using MnTMPyP dramatically reduced these events without normalization of hyperphosphatemia. In CKD5 patients with VC (n = 11) but not in those without VC (n = 13), OS was significantly elevated. While the serum levels of calcium and phosphate were not altered in the animal model for early stage CKD (ECKD), OS, VC, SM22α, calponin, RUNX2, collagen I and NADPH oxidase 1 (NOX1) in VSMCs were all significantly changed. More importantly, serum (5%) derived from patients with ECKD (n = 30) or CKD5 (n = 30) induced SM22α and calponin downregulation, and RUNX2, collagen I, NOX1 upregulation along with a robust elevation of OS and calcium deposition in primary rat VSMCs. These alterations were all reduced by MnTMPyP, ML171 (a NOX1 inhibitor), and U0126 (an inhibitor of Erk signaling). Collectively, we provide a comprehensive set of evidence supporting an important role of OS in promoting VC development in CKD patients (particularly in those with ECKD); this was at least in part through induction of osteoblastic transition in VSMCs which may involve the Erk singling. Our research thus suggests that reductions in OS may prevent VC in CKD patients.