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AbstractAims Diabetic kidney disease (DKD) is the most common cause of end-stage kidney disease (ESKD). The identification of risk factors involved in the progression of DKD to ESKD is expected to result in early detection and appropriate intervention and improve prognosis. This study aimed to explore whether plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) was associated with kidney outcomes in patients with type 2 diabetes mellitus (T2DM) and biopsy-proven DKD.Methods Patients with biopsy-proven DKD who were followed up at West China Hospital over 12 months were enrolled. The kidney outcome was defined as progression to ESKD. The cutoff value of plasma NT-proBNP concentration was calculated by using receiver operating characteristic (ROC) curve analysis. The influence of NT-proBNP levels on kidney outcome in patients with DKD was assessed using Cox regression analysis.Results A total of 30 (24.5%) patients reached ESKD during a median follow-up of 24.1 months. The baseline serum NT-proBNP level had a significant correlation with baseline proteinuria, kidney function, glomerular lesions, interstitial fibrosis tubular atrophy (IFTA), and arteriolar hyalinosis. Multivariate Cox regression analysis indicated that increased NT-proBNP level was significantly associated with a higher risk of progression to ESKD (HR 6.43; 95% CI (1.65–25.10, p = 0.007), and each 1 SD increase in LG (NT-proBNP) was also associated with a higher risk (HR 2.43; 95% CI 1.94–5.29, p = 0.047) of an adverse kidney outcome after adjusting for confounding factors.Conclusions A higher level of plasma NT-proBNP predicts kidney prognosis in patients with biopsy-proven DKD. This warrants further investigation into the potential mechanisms.

Objectives This study aimed to analyze histological and clinical characteristics of patients with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) showing renal involvement to investigate the associations between immune complexes (IC) and clinicopathological indicators, and explore the renal outcomes of AAV.Methods We retrospectively evaluated the histopathological features and clinical characteristics of 80 renal biopsies of patients with AAV with renal involvement. Renal morphology was classified into two (with and without the presence of IC and complement deposition). Endpoints included end-stage kidney disease (ESKD) and death.Results Compared with patients without IC, patients with immune deposition had lower complement C3 (0.80 ± 0.27 vs. 0.93 ± 0.20, p = 0.024), more severe hematuria [133 (46–299) vs. 33 (15–115), p = 0.001] but had milder chronic pathology, including chronic tubular atrophy (p = 0.03), chronic interstitial fibrosis (p = 0.049). Patients in the immune deposition group showed a tendency to have more severe crescent formation and less glomerulosclerosis, but the difference was not statistically significant. Endpoints such as death and ESKD were not significantly different between the two groups.Conclusions Immune deposition may indicate lower complement C3, more severe hematuria and glomerular lesions, milder tubular atrophy, and interstitial fibrosis, but it cannot predict the renal outcome.

We aimed to determine the utility of biopsy data and anemia for the prediction of renal outcomes in Chinese patients with type 2 diabetes. In total, 441 Chinese patients with type 2 diabetes and biopsy-confirmed diabetic nephropathy (DN) were enrolled in a retrospective study. Their renal pathology was assessed using the Renal Pathology Society system. Cox proportional hazards models were used to estimate hazard ratios (HRs) for end-stage renal disease (ESRD), and immunofluorescence staining was used to assess the expression of hypoxia-inducible factor (HIF)-α in patients’ kidneys. We found that glomerular pathology classification was an independent pathological predictor of low hemoglobin concentration, according to linear and logistic regression analyses. Each 1 g/dL decrease in baseline hemoglobin concentration was associated with a 42% higher risk of an adverse renal outcome, after adjustment for clinical and pathologic covariates. In patients with severe glomerular lesions, the risk of progression to ESRD was significantly higher if mild or moderate/severe anemia was present, but in patients with mild glomerular lesions, the risk was only significantly higher in those with moderate or severe anemia than in the absence of anemia. Harrell’s C Concordance was improved, but the Akaike information criterion was worsened by adding the glomerular pathology classification to the use of anemia status and clinical data. Immunofluorescence staining revealed that renal HIF-1α and HIF-2α expression was significantly higher in classes II–IV than class I. Thus, the addition of glomerular pathology classification increases the value of anemia status for the prediction of the progression to ESRD.

Aims Diabetic kidney disease (DKD) is the most common cause of end-stage renal disease (ESRD) and is associated with increased morbidity and mortality in patients with diabetes. Identification of risk factors involved in the progression of DKD to ESRD is expected to result in early detection and appropriate intervention and improve prognosis. Therefore, this study aimed to establish a risk prediction model for ESRD resulting from DKD in patients with type 2 diabetes mellitus (T2DM).Methods Between January 2008 and July 2019, a total of 390 Chinese patients with T2DM and DKD confirmed by percutaneous renal biopsy were enrolled and followed up for at least 1 year. Four machine learning algorithms (gradient boosting machine, support vector machine, logistic regression, and random forest (RF)) were used to identify the critical clinical and pathological features and to build a risk prediction model for ESRD.Results There were 158 renal outcome events (ESRD) (40.51%) during the 3-year median follow up. The RF algorithm showed the best performance at predicting progression to ESRD, showing the highest AUC (0.90) and ACC (82.65%). The RF algorithm identified five major factors: Cystatin-C, serum albumin (sAlb), hemoglobin (Hb), 24-hour urine urinary total protein, and estimated glomerular filtration rate. A nomogram according to the aforementioned five predictive factors was constructed to predict the incidence of ESRD.Conclusion Machine learning algorithms can efficiently predict the incident ESRD in DKD participants. Compared with the previous models, the importance of sAlb and Hb were highlighted in the current model.HighlightsWhat is already known? Identification of risk factors for the progression of DKD to ESRD is expected to improve the prognosis by early detection and appropriate intervention.What this study has found? Machine learning algorithms were used to construct a risk prediction model of ESRD in patients with T2DM and DKD. The major predictive factors were found to be CysC, sAlb, Hb, eGFR, and UTP.What are the implications of the study? In contrast with the treatment of participants with early-phase T2DM with or without mild kidney damage, major emphasis should be placed on indicators of kidney function, nutrition, anemia, and proteinuria for participants with T2DM and advanced DKD to delay ESRD, rather than age, sex, and control of hypertension and glycemia.

Aims Chronic kidney disease (CKD) and diabetes mellitus increase atherosclerotic cardiovascular diseases (ASCVD) risk. However, the association between renal outcome of diabetic kidney disease (DKD) and ASCVD risk is unclear. Methods This retrospective study enrolled 218 type 2 diabetic patients with biopsy-proven DKD, and without known cardiovascular diseases. Baseline characteristics were obtained and the 10-year ASCVD risk score was calculated using the Pooled Cohort Equation (PCE). Renal outcome was defined as progression to end-stage renal disease (ESRD). The association between ASCVD risk and renal function and outcome was analyzed with logistic regression and Cox analysis. Results Among all patients, the median 10-year ASCVD risk score was 14.1%. The median of ASCVD risk score in CKD stage 1, 2, 3, and 4 was 10.9%, 12.3%, 16.5%, and 14.8%, respectively (p = 0.268). Compared with patients with lower ASCVD risk (＜14.1%), those with higher ASCVD risk had lower eGFR, higher systolic blood pressure, and more severe renal interstitial inflammation. High ASCVD risk (>14.1%) was an independent indicator of renal dysfunction in multivariable-adjusted logistic analysis (OR, 3.997; 95%CI, 1.385–11.530; p = 0.010), though failed to be an independent risk factor for ESRD in patients with DKD in univariate and multivariate Cox analysis. Conclusions DKD patients even in CKD stage 1 had comparable ASCVD risk score to patients in CKD stage 2, 3, and 4. Higher ASCVD risk indicated severe renal insufficiency, while no prognostic value of ASVCD risk for renal outcome was observed, which implied macroangiopathy and microangiopathy in patients with DKD were related, but relatively independent.

This retrospective study included 299 patients with type 2 diabetes mellitus and biopsy-confirmed diabetic nephropathy (DN) to investigate the prognostic value of alkaline phosphatase (ALP) for renal outcome. Cox proportional hazards models were used to estimate the hazard ratios (HRs) for the serum ALP level on renal outcome, which was defined as end-stage renal disease (ESRD) or a 50% decline in estimated glomerular filtration rate (eGFR) from baseline. The median baseline ALP was 80 IU/L with an interquartile range of 64–97 IU/L. Serum ALP was negatively associated with eGFR but positively associated with proteinuria and renal interstitial fibrosis. During a median follow-up period of 23 months, ESRD or a 50% declined in the eGFR occurred in 156 (52.2%) patients. The highest quartile of ALP was significantly associated with poor renal outcome, as defined above (HR 2.38, 95% confidence interval [CI] 1.09–5.17), when adjusted for sociodemographics, baseline eGFR, proteinuria, liver function parameters, parathyroid hormone levels, and renal pathological findings. Each standard deviation higher in the natural log-transformed ALP was associated with a 25% increased risk for poor renal outcome. Additionally, there was a graded increase in the risk for poor renal outcome with higher ALP in patients with nephrotic-range proteinuria. However, no significant associations were observed between serum ALP levels and renal outcome in patients with non-nephrotic-range proteinuria. In conclusion, an elevated ALP level was independently associated with poor renal outcome in patients with type 2 diabetes mellitus and nephrotic-range proteinuria after multivariate adjustment.