Lin Hongyuan, Hou Jianfeng, Tang Hanwei, Chen Kai, Sun Hansong, Zheng Zhe, Hu Shengshou
Cardiac Surgery Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 167, North Lishi street, Xicheng District, Beijing, 100037, China.
BMC Cardiovasc Disord. 2020 Dec 10;20(1):517. doi: 10.1186/s12872-020-01799-1.
Heart failure (HF) is a global health issue, and coronary artery bypass graft (CABG) is one of the most effective surgical treatments for HF with coronary artery disease. Unfortunately, the incidence of postoperative acute kidney injury (AKI) is high in HF patients following CABG, and there are few tools to predict AKI after CABG surgery for such patients. The aim of this study is to establish a nomogram to predict the incidence of AKI after CABG in patients with impaired left ventricular ejection fraction (LVEF).
From 2012 to 2017, Clinical information of 1208 consecutive patients who had LVEF< 50% and underwent isolated CABG was collected to establish a derivation cohort. A novel nomogram was developed using the logistic regression model to predict postoperative AKI among these patients. According to the same inclusion criteria and the same period, we extracted the data of patients from 6 other large cardiac centers in China (n = 540) from the China Heart Failure Surgery Registry (China-HFSR) database for external validation of the new model. The nomogram was compared with 3 other available models predicting renal failure after cardiac surgery in terms of calibration, discrimination and net benefit.
In the derivation cohort (n = 1208), 90 (7.45%) patients were diagnosed with postoperative AKI. The nomogram included 7 independent risk factors: female, increased preoperative creatinine(> 2 mg/dL), LVEF< 35%, previous myocardial infarction (MI), hypertension, cardiopulmonary bypass(CPB) used and perioperative blood transfusion. The area under the receiver operating characteristic curve (AUC) was 0.738, higher than the other 3 models. By comparing calibration curves and decision curve analyses (DCA) with other models, the novel nomogram showed better calibration and greater net benefit. Among the 540 patients in the validation cohort, 104 (19.3%) had postoperative AKI, and the novel nomogram performed better with respect to calibration, discrimination and net benefit.
The novel nomogram is a reliable model to predict postoperative AKI following isolated CABG for patients with impaired LVEF.
心力衰竭(HF)是一个全球性的健康问题,冠状动脉旁路移植术(CABG)是治疗冠心病合并心力衰竭最有效的外科手术方法之一。不幸的是,CABG术后HF患者急性肾损伤(AKI)的发生率很高,且几乎没有工具可用于预测此类患者CABG术后的AKI。本研究的目的是建立一种列线图,以预测左心室射血分数(LVEF)受损患者CABG术后AKI的发生率。
收集2012年至2017年期间1208例连续接受单纯CABG且LVEF<50%患者的临床信息,建立一个推导队列。使用逻辑回归模型开发一种新型列线图,以预测这些患者术后的AKI。根据相同的纳入标准和同一时期,我们从中国心力衰竭外科注册数据库(China-HFSR)中提取了中国其他6个大型心脏中心患者的数据(n=540),用于新模型的外部验证。将该列线图与其他3种预测心脏手术后肾衰竭的可用模型在校准、区分度和净效益方面进行比较。
在推导队列(n=1208)中,90例(7.45%)患者被诊断为术后AKI。该列线图包括7个独立危险因素:女性、术前肌酐升高(>2mg/dL)、LVEF<35%、既往心肌梗死(MI)、高血压、使用体外循环(CPB)和围手术期输血。受试者操作特征曲线(AUC)下面积为0.738,高于其他3种模型。通过与其他模型比较校准曲线和决策曲线分析(DCA),新型列线图显示出更好的校准和更大的净效益。在验证队列的540例患者中,104例(19.3%)发生术后AKI,新型列线图在校准、区分度和净效益方面表现更好。
新型列线图是预测LVEF受损患者单纯CABG术后AKI的可靠模型。