Construction and validation of a risk prediction model for acute kidney injury in patients after cardiac arrest.

ABSTRACT:

Objective

Identifying patients at high risk for cardiac arrest-associated acute kidney injury (CA-AKI) helps in early preventive interventions. This study aimed to establish and validate a high-risk nomogram for CA-AKI.

Methods

In this retrospective dataset, 339 patients after cardiac arrest (CA) were enrolled and randomized into a training or testing dataset. The Student's t-test, non-parametric Mann-Whitney U test, or χ2 test was used to compare differences between the two groups. Optimal predictors of CA-AKI were determined using the Least Absolute Shrinkage and Selection Operator (LASSO). A nomogram was developed to predict the early onset of CA-AKI. The performance of the nomogram was assessed using metrics such as area under the curve (AUC), calibr

SUBMITTER: Lin L 

PROVIDER: S-EPMC11018071 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature