Pan Ling, Deng Yang, Dai Shichen, Feng Xu, Feng Li, Yang Zhenhua, Liao Yunhua, Zheng Baoshi
Department of Nephrology, The First Affiliated Hospital of Guangxi Medical University, China.
Department of Cardiac surgery, The First Affiliated Hospital of Guangxi Medical University, China.
Int J Cardiol. 2023 Jan 1;370:345-350. doi: 10.1016/j.ijcard.2022.10.147. Epub 2022 Oct 25.
Acute kidney injury (AKI) is a common complication after cardiac surgery. This study aims to develop and validate a risk model for predicting AKI after cardiac valve replacement surgery.
Data from patients undergoing surgical valve replacement between January 2015 and December 2018 in our hospital were retrospectively analyzed. The subjects were randomly divided into a derivation cohort and a validation cohort at a ratio of 7:3. The primary outcome was defined as AKI within 7 days after surgery. Logistic regression analysis was conducted to select risk predictors for developing the prediction model. Receiver operator characteristic curve (ROC), calibration plot and clinical decision curve analysis (DCA) will be used to evaluate the discrimination, precision and clinical benefit of the prediction model.
A total of 1159 patients were involved in this study. The prevalence of AKI following surgery was 37.0% (429/1159). Logistic regression analysis showed that age, hemoglobin, fibrinogen, serum uric acid, cystatin C, bicarbonate, and cardiopulmonary bypass time were independent risk factors associated with AKI after surgical valve replacement (all P < 0.05). The areas under the ROC curves (AUCs) in the derivation cohort and the validation cohort were 0.777 (95% CI 0.744-0.810) and 0.760 (95% CI 0.706-0.813), respectively. The calibration plots indicated excellent consistency between the prediction probability and actual probability. DCA demonstrated great clinical benefit of the prediction model.
We developed a prediction model for predicting AKI after cardiac valve replacement surgery that was internally validated to have good discrimination, calibration, and clinical practicability.
急性肾损伤（AKI）是心脏手术后常见的并发症。本研究旨在建立并验证一种预测心脏瓣膜置换术后AKI的风险模型。
回顾性分析2015年1月至2018年12月在我院接受外科瓣膜置换术患者的数据。将受试者按7:3的比例随机分为推导队列和验证队列。主要结局定义为术后7天内发生AKI。进行逻辑回归分析以选择用于建立预测模型的风险预测因素。将使用受试者工作特征曲线（ROC）、校准图和临床决策曲线分析（DCA）来评估预测模型的辨别力、准确性和临床效益。
本研究共纳入1159例患者。术后AKI的患病率为37.0%（429/1159）。逻辑回归分析显示，年龄、血红蛋白、纤维蛋白原、血清尿酸、胱抑素C、碳酸氢盐和体外循环时间是外科瓣膜置换术后与AKI相关的独立危险因素（均P<0.05）。推导队列和验证队列的ROC曲线下面积（AUC）分别为0.777（95%CI 0.744-0.810）和0.760（95%CI 0.706-0.813）。校准图表明预测概率与实际概率之间具有良好的一致性。DCA显示该预测模型具有很大的临床效益。
我们建立了一种预测心脏瓣膜置换术后AKI的预测模型，经内部验证具有良好的辨别力、校准度和临床实用性。
