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

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.

Risk-Predictive Models for Adverse Events in Cardiac Surgery: A Review

“…After all patients were grouped according to whether patients undergoing CABG were combined with other surgeries, and their data were analyzed, all AUC values were less than 0.7, thus indicating SinoSCORE's poor discriminatory power. Lin et al [43] have applied SinoSCORE to evaluate the in-hospital mortality of 1976 patients receiving CABG with preoperative heart failure, and have found poor performance, with an AUC of 0.698; the actual mortality rate was 1.41, and the predicted mortality rate was 7.66.…”

Combination of the triglyceride‐glucose index and EuroSCORE II improves the prediction of long‐term adverse outcomes in patients undergoing coronary artery bypass grafting

“…The AUC of the EuroSCORE II was relatively low, which was consistent with previous studies conducted among the Chinese population. 38,39 Therefore, the predictive ability of the EuroSCORE II may be affected by racial/ethnic differences in cardiovascular risk factors.…”

Acute Kidney Injury following Cardiopulmonary Bypass: A Challenging Picture

“…The incidence and prognosis of CPB-associated AKI are influenced by multiple factors. Hence, predictive risk models must be established to comprehensively assess the general condition of patients [91,92]. Several predictive risk models have been established, including the use of Mehta scores with the C statistic of 0.83 (10 variables: preoperative sCr level, age, race, type of surgery, diabetes, shock, New York Heart Association class, lung disease, recent myocardial infarction, and prior cardiovascular surgery are included in this bedside tool that is aimed at evaluating the need for postoperative dialysis) [93], Cleveland Clinic scores with an overall area under the receiver operating characteristic (ROC) curve of 0.81 (10 variables have been validated for a maximum score of 17: female gender, congestive heart failure, LVEF, preoperative use of intra-aortic balloon pump, COPD, diabetes, previous cardiac surgery, emergency surgery, type of surgery, and preoperative creatinine level) [94], and Simplified Renal Index scores with an overall area under the ROC curve of 0.81 (7 variables are identified for a maximum score of 8: GFR, diabetes, ejection fraction, previous cardiac surgery, procedure other than coronary artery bypass grafting, intra-aortic balloon pump, and nonelective case) [95].…”