Acute kidney injury in solitary kidney patients after partial nephrectomy: incidence, risk factors and prediction.

ABSTRACT:

Background

To analyze the incidence and risk factors of acute kidney injury (AKI) after partial nephrectomy (PN) in patients with solitary kidney, and to build AKI prediction models using logistic regression and machine learning (ML) approaches.

Methods

Clinical data of 87 solitary kidney patients with renal mass who received PN from January 2003 to March 2019 were collected. The diagnosis of AKI was based on KDIGO criteria. Logistic regression analysis and ML method were used to build prediction models.

Results

AKI developed in 52 (59.8%) patients. The logistic regression model had three variables: ischemia time (P=0.003), surgery time (P=0.001) and preoperative fasted blood glucose level (FBG) (P=0.049). The area under curve (AUC) was 0.826, with the specificity and

SUBMITTER: Zhu K 

PROVIDER: S-EPMC7354300 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature