Prediction of Acute Kidney Injury for Acute Type A Aortic Dissection Patients Who Underwent Sun’s Procedure by a Perioperative Nomogram

Author:

Zhang Yuhui,Lan Yongrong,Chen Tongyun,Chen Qingliang,Guo Zhigang,Jiang Nan

Abstract

<b><i>Introduction:</i></b> Postoperative acute kidney injury (AKI) occurs in 20–40% of acute type A aortic dissection (ATAAD) patients undergoing cardiac surgery. A predictive model could be developed to assess the probability of AKI in patients with ATAAD before and after cardiac surgery in a timely manner. <b><i>Methods:</i></b> This retrospective study enrolled a total of 224 patients with ATAAD. Patients were subjected to total arch replacement using a tetrafurcate graft with stented elephant trunk implantation according to Sun’s procedure. Statistical comparison for the collected data was done with Student’s <i>t</i> test or Mann-Whitney U test (continuous variables) and χ<sup>2</sup> test (categorical variables). The independent predictors were screened by multivariate logistic regression analysis and then incorporated into a nomogram. The reliability of cardiac surgery-associated AKI (CSA-AKI) models was evaluated using the area under the receiver operating characteristic curve (AUC). <b><i>Results:</i></b> This study enrolled 224 ATAAD patients, including 53 patients with AKI and 171 patients without AKI. The incidence of ATAAD-induced AKI in the cohort was 23.66%. The screened predictors for AKI include iliac artery involvement, creatinine, D-dimer, autotransfusion, platelet-rich plasma reinfusion, nasal temperature, red blood cells, fresh frozen plasma, drainage, and mechanical ventilation. The calculated AUC values for model 1, model 2, model 3, and model 4 were 0.710, 0.777, 0.827, and 0.848, respectively. Model 4 was optimum for AKI risk scoring compared with model 1, model 2, and model 3. <b><i>Conclusions:</i></b> AKI prediction models were established for ATAAD patients using preoperative, intraoperative, and postoperative information. Particularly, model 4 shows superiority in risk prediction for CSA-AKI.

Publisher

S. Karger AG

Subject

Urology,Cardiology and Cardiovascular Medicine

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