Nomogram as a Predictor for Postoperative Acute Kidney Injury in Super-Elderly Patients Undergoing Noncardiac Surgery

Abstract

Objective: There has been increase the incidence of postoperative acute kidney injury (AKI), especially among super-elderly patients. The study aimed to identify risk factors and develop a nomogram among super elderly patients undergoing noncardiac surgery. Material and Methods: A single-center retrospective cohort study of patients aged greater than or equal to 80 years that underwent non-cardiac surgery between January 2018 to December 2020. Acute kidney injury (AKI) was identified by Kidney Disease Improving Global Outcome (KDIGO) during seven days after surgery. Multivariate logistic regression was constructed from preoperative and intraoperative data with variables with P-value<0.2 included in the final model. The performance of model function was conducted by area under the receiver curve (AUC) and calibration curves. Results: Eight hundred and twenty patients were included; 124 (15%) developed postoperative AKI. A multivariate logistic regression model consisting of COPD, ASA classification, part of surgery, propofol and Succinylated gelatin was displayed as the nomogram. The model showed good discrimination with an AUC 0.746. The cutoff point of 63, which had the highest Youden index, was chosen with sensitivity and specificity of 82% and 46%, respectively. The nomogram showed good performance by the Hosmer-Lameshow goodness-of-fit test. (X2= 6.0697 and P value = 0.6394) Conclusion: The nomogram predicted model for predicting postoperative AKI among super-elderly patients showed moderate discrimination ability and was instituted. It can help physicians to detect high-risk patients early and promptly prevent episodes of AKI.

Keywords

• postoperative acute kidney injury
• super-elderly patient
• nomogram