Chung Paul J, Carter Timothy I, Burack Joshua H, Tam Sophia, Alfonso Antonio, Sugiyama Gainosuke
Department of Surgery, State University of New York Downstate Medical Center, 450 Clarkson Ave, Brooklyn, NY, 11203, USA.
Department of Cardiothoracic Surgery, State University of New York Downstate Medical Center, Brooklyn, 11203, USA.
J Cardiothorac Surg. 2015 Apr 29;10:62. doi: 10.1186/s13019-015-0269-y.
Risk models to predict 30-day mortality following isolated coronary artery bypass graft is an active area of research. Simple risk predictors are particularly important for cardiothoracic surgeons who are coming under increased scrutiny since these physicians typically care for higher risk patients and thus expect worse outcomes. The objective of this study was to develop a 30-day postoperative mortality risk model for patients undergoing CABG using the American College of Surgeons National Surgical Quality Improvement Program database.
Data was extracted and analyzed from the American College of Surgeons National Surgical Quality Improvement Program Participant Use Files (2005-2010). Patients that had ischemic heart disease (ICD9 410-414) undergoing one to four vessel CABG (CPT 33533-33536) were selected. To select for acquired heart disease, only patients age 40 and older were included. Multivariate logistic regression analysis was used to create a risk model. The C-statistic and the Hosmer-Lemeshow goodness-of-fit test were used to evaluate the model. Bootstrap-validated C-statistic was calculated.
A total of 2254 cases met selection criteria. Forty-nine patients (2.2%) died within 30 days. Six independent risk factors predictive of short-term mortality were identified including age, preoperative sodium, preoperative blood urea nitrogen, previous percutaneous coronary intervention, dyspnea at rest, and history of prior myocardial infarction. The C-statistic for this model was 0.773 while the bootstrap-validated C-statistic was 0.750. The Hosmer-Lemeshow test had a p-value of 0.675, suggesting the model does not overfit the data.
The American College of Surgeons National Surgical Quality Improvement Program risk model has good discrimination for 30-day mortality following coronary artery bypass graft surgery. The model employs six independent variables, making it easy to use in the clinical setting.
预测单纯冠状动脉搭桥术后30天死亡率的风险模型是一个活跃的研究领域。对于心胸外科医生来说，简单的风险预测指标尤为重要，因为这些医生受到的审查日益增加，因为他们通常照顾高风险患者，因此预期结果更差。本研究的目的是利用美国外科医师学会国家外科质量改进计划数据库，为接受冠状动脉搭桥术（CABG）的患者建立一个术后30天死亡率风险模型。
从美国外科医师学会国家外科质量改进计划参与者使用文件（2005 - 2010年）中提取并分析数据。选择患有缺血性心脏病（ICD9 410 - 414）且接受一至四支血管冠状动脉搭桥术（CPT 33533 - 33536）的患者。为了选择获得性心脏病患者，仅纳入年龄在40岁及以上的患者。采用多因素逻辑回归分析建立风险模型。使用C统计量和Hosmer-Lemeshow拟合优度检验来评估模型。计算经自展验证的C统计量。
共有2254例病例符合选择标准。49例患者（2.2%）在30天内死亡。确定了六个预测短期死亡率的独立风险因素，包括年龄、术前钠、术前血尿素氮、既往经皮冠状动脉介入治疗、静息时呼吸困难和既往心肌梗死病史。该模型的C统计量为0.773，而经自展验证的C统计量为0.750。Hosmer-Lemeshow检验的p值为0.675，表明该模型没有过度拟合数据。
美国外科医师学会国家外科质量改进计划风险模型对冠状动脉搭桥术后30天死亡率具有良好的区分能力。该模型采用六个独立变量，便于在临床环境中使用。
