Liu Yu, Wang Xing, Chen Zi-Ying, Zhang Wen-Li, Guo Lin, Sun Yong-Quan, Cui Hong-Zhan, Bu Ji-Qiang, Cai Jian-Hui
Department of Surgery, Hebei Medical University, Shijiazhuang, China.
Department of Cardiac Surgery, the Second Hospital of Hebei Medical University, Shijiazhuang, China.
J Geriatr Cardiol. 2021 Jun 28;18(6):449-461. doi: 10.11909/j.issn.1671-5411.2021.06.006.
Severe bleeding following cardiac surgery remains a troublesome complication, but to date, there is a lack of comprehensive predictive models for the risk of severe bleeding following off-pump coronary artery bypass grafting (OPCABG). This study aims to analyze relevant indicators of severe bleeding after isolated OPCABG and establish a corresponding risk assessment model.
The clinical data of 584 patients who underwent OPCABG from January 2018 to April 2020 were retrospectively analyzed. We gathered the preoperative baseline data and postoperative data immediately after intensive care unit admission and used multifactor logistic regression to screen the potential predictors of severe bleeding, upon which we established a predictive model. Using the consistency index and calibration curve, decision curve, and clinical impact curve analysis, we evaluated the performance of the model.
This study is the first to establish a risk assessment and prediction model for severe bleeding following isolated OPCABG. Eight independent risk factors were identified: male sex, aspirin/clopidogrel withdrawal time, platelet count, fibrinogen level, C-reactive protein, serum creatinine, and total bilirubin. Among the 483 patients in the training group, 138 patients (28.6%) had severe bleeding; among the 101 patients in the verification group, 25 patients (24.8%) had severe bleeding. Receiver operating characteristic (ROC) curve analysis for the internal training group revealed a convincing performance with a concordance index (C-index) of 0.859, while the area under the ROC curve for the external validation data was 0.807. Decision curve analysis showed that the model was useful for both groups.
Although there are some limitations, the model can effectively predict the probability of severe bleeding following isolated OPCABG and is therefore worthy of further exploration and verification.
心脏手术后的严重出血仍然是一个棘手的并发症，但迄今为止，缺乏用于非体外循环冠状动脉旁路移植术（OPCABG）后严重出血风险的综合预测模型。本研究旨在分析单纯OPCABG术后严重出血的相关指标，并建立相应的风险评估模型。
回顾性分析2018年1月至2020年4月期间接受OPCABG的584例患者的临床资料。收集术前基线数据和重症监护病房入院后即刻的术后数据，并使用多因素逻辑回归筛选严重出血的潜在预测因素，在此基础上建立预测模型。通过一致性指数、校准曲线、决策曲线和临床影响曲线分析，评估模型的性能。
本研究首次建立了单纯OPCABG术后严重出血的风险评估和预测模型。确定了8个独立危险因素：男性、阿司匹林/氯吡格雷停药时间、血小板计数、纤维蛋白原水平、C反应蛋白、血清肌酐和总胆红素。训练组的483例患者中，138例（28.6%）发生严重出血；验证组的101例患者中，25例（24.8%）发生严重出血。内部训练组的受试者工作特征（ROC）曲线分析显示性能令人信服，一致性指数（C指数）为0.859，而外部验证数据的ROC曲线下面积为0.807。决策曲线分析表明该模型对两组均有用。
尽管存在一些局限性，但该模型可以有效预测单纯OPCABG术后严重出血的概率，因此值得进一步探索和验证。
