-
- Academic Editor
-
-
-
†These authors contributed equally.
Background: Acute kidney injury (AKI) frequently occurs after aortic
surgery and has a significant impact on patient outcomes. Early detection or
prediction of AKI is crucial for timely interventions. This study aims to develop
and validate a novel model for predicting AKI following aortic surgery.
Methods: We enrolled 156 patients who underwent on-pump aortic surgery
in our hospital from February 2023 to April 2023. Postoperative levels of eight
cytokines related to macrophage polarization analyzed using a multiplex cytokine
assay. All-subset regression was used to select the optimal cytokines to predict
AKI. A logistic regression model incorporating the selected cytokines was used
for internal validation in combination with a bootstrapping technique. The
model’s ability to discriminate between cases of AKI and non-AKI was assessed
using receiver operating characteristic (ROC) curve analysis. Results:
Of the 156 patients, 109 (69.87%) developed postoperative AKI. Interferon-gamma
(IFN-