一种用于预测左心室射血分数降低的冠状动脉旁路移植术后院内死亡率的新型风险分层系统。

A Novel Risk Stratification System for Predicting In-Hospital Mortality Following Coronary Artery Bypass Grafting Surgery with Impaired Left Ventricular Ejection Fraction.

机构信息

Cardiac Surgery Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

出版信息

Heart Surg Forum. 2020 Aug 28;23(5):E621-E626. doi: 10.1532/hsf.3089.

DOI:10.1532/hsf.3089

PMID:32990579

Abstract

BACKGROUND

Coronary artery disease (CAD) is the most common cause of heart failure (HF), and impaired ejection fraction (EF<50%) is a crucial precursor to HF. Coronary artery bypass grafting (CABG) is an effective surgical solution to CAD-related HF. In light of the high risk of cardiac surgery, appropriate scores for groups of patients are of great importance. We aimed to establish a novel score to predict in-hospital mortality for impaired EF patients undergoing CABG.

METHODS

Clinical information of 1,976 consecutive CABG patients with EF<50% was collected from January 2012 to December 2017. A novel system was developed using the logistic regression model to predict in-hospital mortality among patients with EF<50% who were to undergo CABG. The scoring system was named PGLANCE, which is short for seven identified risk factors, including previous cardiac surgery, gender, load of surgery, aortic surgery, NYHA stage, creatinine, and EF. AUC statistic was used to test discrimination of the model, and the calibration of this model was assessed by the Hosmer-lemeshow (HL) statistic. We also evaluated the applicability of PGLANCE to predict in-hospital mortality by comparing the 95% CI of expected mortality to the observed one. Results were compared with the European Risk System in Cardiac Operations (EuroSCORE), EuroSCORE II, and Sino System for Coronary Operative Risk Evaluation (SinoSCORE).

RESULTS

By comparing with EuroSCORE, EuroSCORE II and SinoSCORE, PGLANCE was well calibrated (HL P = 0.311) and demonstrated powerful discrimination (AUC=0.846) in prediction of in-hospital mortality among impaired EF CABG patients. Furthermore, the 95% CI of mortality estimated by PGLANCE was closest to the observed value.

CONCLUSION

PGLANCE is better with predicting in-hospital mortality than EuroSCORE, EuroSCORE II, and SinoSCORE for Chinese impaired EF CABG patients.

摘要

背景

冠心病（CAD）是心力衰竭（HF）最常见的病因，射血分数（EF<50%）降低是心力衰竭的关键前兆。冠状动脉旁路移植术（CABG）是治疗 CAD 相关 HF 的有效手术方法。鉴于心脏手术的高风险，对于患者群体的适当评分非常重要。我们旨在建立一种新的评分系统，以预测接受 CABG 的 EF 降低患者的住院死亡率。

方法

收集了 2012 年 1 月至 2017 年 12 月期间 1976 例连续接受 EF<50% CABG 治疗的患者的临床信息。使用逻辑回归模型开发了一种新的系统，以预测接受 CABG 的 EF 降低患者的住院死亡率。该评分系统命名为 PGLANCE，是七个确定的危险因素的缩写，包括既往心脏手术、性别、手术负荷、主动脉手术、NYHA 分期、肌酐和 EF。AUC 统计量用于测试模型的判别能力，通过 Hosmer-lemeshow（HL）统计量评估模型的校准。我们还通过比较预期死亡率的 95%CI 与观察到的死亡率来评估 PGLANCE 预测住院死亡率的适用性。结果与欧洲心脏手术风险系统（EuroSCORE）、EuroSCORE II 和中国冠状动脉手术风险评估系统（SinoSCORE）进行了比较。