Identification of AKI signatures and classification patterns in ccRCC based on machine learning.

Background: Acute kidney injury can be mitigated if detected early. There are limited biomarkers for predicting acute kidney injury (AKI). In this study, we used public databases with machine learning algorithms to identify novel biomarkers to predict AKI.

New-onset glucose disorders in peritoneal dialysis patients: a meta-analysis and systematic review.

Background: Peritoneal dialysis (PD) patients are at high risk of developing glucose metabolism disturbance (GMD). The incidence and prevalence of new-onset GMD, including diabetes mellitus (DM), impaired glucose tolerance (IGT) and impaired fast glucose (IFG), after initiation of PD, as well as their correlated influence factors, varies among studies in different areas and of different sample sizes. Also, the difference compared with hemodialysis (HD) remained unclear.