Postoperative Nomogram and Risk Calculator of Acute Renal Failure for Stanford Type A Aortic Dissection Surgery

Overview

Journal Gen Thorac Cardiovasc Surg

Specialties Cardiology & Vascular Diseases
General Surgery
Pulmonary Medicine

Date 2023 May 22

PMID 37212922

Authors

Chong Zhang

Song Chen

Jianguo Yang

Gaofeng Pan

Affiliations

Soon will be listed here.

Abstract

Background: This study aimed to explore the risk factors of acute renal failure (ARF) after Stanford type A aortic dissection (AAD) surgery, establish a nomogram prediction model and calculate the risk of ARF.

Material And Methods: 241 AAD patients who received aortic surgery in the department of cardiovascular surgery, Zhongnan Hospital of Wuhan University were enrolled in this study. All enrolled patients were divided into the ARF group and non-ARF group. The clinical data of the two groups were collected and compared. The independent risk factors of ARF after aortic surgery were analyzed by univariate and multivariate logistic regression analyses. Moreover, a nomogram prediction model was generated. The calibration curve, ROC curve and independent external validation were performed to evaluate the nomogram prediction model.

Results: 67 patients were diagnosed with ARF within 48 h after the operation. Univariate and multivariate logistic regression analyses showed that hypertension, preoperative renal artery involvement, CPB time extension and postoperative decreased platelet lymphocyte ratio were the independent risk factors of ARF after AAD surgery. The nomogram model could predict the risk of ARF with a sensitivity of 81.3% and a specificity of 78.6%. The calibration curve displayed good agreement of the predicted probability with the actual observed probability. AUC of the ROC curve was 0.839. External data validation was performed with a sensitivity of 79.2% and a specificity of 79.8%.

Conclusions: Hypertension, preoperative renal artery involvement, CPB time extension and postoperative decreased platelet lymphocyte ratio could predict the risk of ARF after AAD surgery.

Citing Articles

Machine Learning Model-Based Prediction of In-Hospital Acute Kidney Injury Risk in Acute Aortic Dissection Patients.

Wei Z, Liu S, Chen Y, Liu H, Liu G, Hu Y Rev Cardiovasc Med. 2025; 26(2):25768.

PMID: 40026497 PMC: 11868902. DOI: 10.31083/RCM25768.

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