From January 2010 to December 2016, 1616 consecutive patients who underwent isolated coronary artery bypass grafting (CABG) were evaluated for their predicted mortality according to the online Sino System for Coronary Operative Risk Evaluation (SinoSCORE), European System for Cardiac Operative Risk Evaluation II (EuroSCORE II) and Society of Thoracic Surgeons (STS) risk evaluation system. The calibration and discrimination in the total and in the subsets were assessed by the Hosmer-Lemeshow (H-L) statistics and by the C statistics respectively, to evaluate the efficiency of the three risk evaluation systems. The realized mortality was 1.92% (31/1616). The predictive mortality of SinoSCORE, EuroSCORE II and STS risk evaluation system were 1.35%, 1.74% and 1.05%, respectively. SinoSCORE achieved best discrimination. When grouping by risk, SinoSCORE also achieved the best discrimination in high-risk group, followed by STS risk evaluation system and EuroSCORE II while SinoSCORE and EuroSCORE II had excellent performance in low-risk group. In terms of calibration, SinoSCORE, EuroSCORE II and STS risk evaluation system all achieved positive calibrations (H-L: P > 0.05) in the overall population and grouped subsets. SinoSCORE achieved good predictive efficiency in East China patients undergoing isolated CABG and showed no compromise when compared with EuroSCORE II and STS risk evaluation system.
ObjectivesTo assess and compare the predictive ability of three risk evaluation systems (SinoSCORE, EuroSCORE II and the STS risk evaluation system) in patients aged ≥70, and who underwent coronary artery bypass grafting (CABG) in East China.MethodsThree risk evaluation systems were applied to 1,946 consecutive patients who underwent isolated CABG from January 2004 to September 2016 in two hospitals. Patients were divided into two subsets according to their age: elderly group (age ≥70) with a younger group (age <70) used for comparison. The outcome of interest in this study was in-hospital mortality. The entire cohort and subsets of patients were analyzed. The calibration and discrimination in total and in subsets were assessed by the Hosmer–Lemeshow and the C statistics respectively.ResultsInstitutional overall mortality was 2.52%. The expected mortality rates of SinoSCORE, EuroSCORE II and the STS risk evaluation system were 0.78(0.64)%, 1.43(1.14)% and 0.78(0.77)%, respectively. SinoSCORE achieved the best discrimination (the area under the receiver operating characteristic curve (AUC) = 0.829), followed by the STS risk evaluation system (AUC = 0.790) and EuroSCORE II (AUC = 0.769) in the entire cohort. In the elderly group, the observed mortality rate was 4.82% while it was 1.38% in the younger group. SinoSCORE (AUC = .829) also achieved the best discrimination in the elderly group, followed by the STS risk evaluation system (AUC = .730) and EuroSCORE II (AUC = 0.640) while all three risk evaluation systems all had good performances in the younger group. SinoSCORE, EuroSCORE II and the STS risk evaluation system all achieved positive calibrations in the entire cohort and subsets.ConclusionThe performance of the three risk evaluation systems was not ideal in the entire cohort. In the elderly group, SinoSCORE appeared to achieve better predictive efficiency than EuroSCORE II and the STS risk evaluation system.
Background Preoperative risk evaluation systems are significant and important to the allocation of medical resources and the communication between doctors and patients. The European System for Cardiac Operative Risk Evaluation II (EuroSCORE II) is widely used in clinical practice. Cardiac troponin T (cTnT) can specifically and accurately reflect myocardial injury. Whether EuroSCORE II can improve the predictive power after integrating with cTnT is still unclear. This study was a retrospective single center study designed to assess the predictive ability of EuroSCORE II integrated with cTnT for patients undergoing isolated off-pump coronary artery bypass grafting (OPCABG). Methods This retrospective and observational cohort study included 1887 patients who underwent first isolated OPCABG. cTnT was detected within 48 h before operation in each patient. According to myocardial injury, patients were divided by cTnT into 4 stages. A new risk evaluation system was created through logistic regression with EuroSCORE II and myocardial injury classification as covariates. Then the two risk evaluation systems were comparatively assessed by regression analysis, receiver operator characteristic curves, net reclassification index, Bland–Altman plots and decision curve analysis. Results There were 43 in-hospital deaths, with a mortality of 2.30% (43/1887). The logistic regression analysis showed that preoperative myocardial injury classification was a significant risk factor for in-hospital mortality in both total cohort (OR 1.491, 95%CI 1.049–2.119) and subsets (OR 1.761, 95%CI 1.102–2.814). The new risk evaluation system has higher calibration and discrimination power than EuroSCORE II, both for overall cohort and subsets. Especially, the new system has obvious advantages in discrimination power in the subset of acute myocardial infarction (AUC 0.813 vs. 0.772, 0.906 vs. 0.841, and 0.715 vs. 0.646, respectively). Conclusions Both myocardial injury classification and EuroSCORE II are independent risk factors of in-hospital mortality in OPCABG patients. The new risk evaluation system has higher predictive ability than EuroSCORE II, especially in patients with a recent history of AMI.
IntroductionTo analyze the outcomes of off-pump coronary artery bypass grafting (OPCABG) and esophagectomy simultaneously for patients with coronary artery disease (CAD) and coexisting esophageal cancer.MethodsTwenty-two patients with CAD and coexisting esophageal cancer underwent combined surgical interventions were subjected to the study. OPCABG was performed first, followed by esophagectomy. All the corresponding data including clinicopathological characteristics and postoperative outcomes were all investigated.ResultsAll the combined procedures were performed successfully. The average number of grafts was 2.36. Tumors were located at the middle third of the esophagus in 5 patients, at the lower third of the esophagus in 8 patients, at the esophageal gastric junction (EGJ) in 9 patients, respectively. The operations were carried out through a left lateral thoracotomy approach in 21 patients while a median sternotomy and left lateral thoracotomy approach was used in 1 patient for his condition rapidly worsened. Postoperatively, pneumonia occurred in 4 patients (18.2%). During the follow-up, three patients died of cancer metastasis /recurrence (6, 18, 37 months) and one died of pneumonia (1 month). The cumulative 5 years survival rate is 52.9%.ConclusionsThe combined procedure of OPCABG and esophagectomy is a safe and effective treatment option for patients with severe CAD and esophageal cancer.
Background Cardiac troponin T (cTnT) is currently one of the important indicators for clinical diagnosis of myocardial injury, which is inevitable in cardiac surgery, especially coronary artery bypass grafting (CABG). Describing the release profile of cTnT and finding out the risk factors of postoperative myocardial injury (PMI) are of great significance. The purposes of this study are to explore the release profile of cTnT in patients undergoing CABG and to search for independent risk factors of PMI. Methods In this retrospective study, clinical data of CABG patients were collected. The cTnT was measured at 24 hours before and 6, 12, 24, 48, 72, 96 and 120 hours after operation separately. The release profiles and peak time of cTnT in total cohort and sub-cohorts were observed. Independent risk factors of PMI were explored via univariate and multivariate logistic regression analyses. Results In total, 2084 patients were enrolled, including 998 patients in a cTnT group and 1086 patients in a high-sensitive cTnT (hs-cTnT) group. PMI was recognized in 797 patients. In both groups, cTnT showed a trend of rising first and then falling within 120 hours after operation. The peak cTnT appeared within 12–24 hours after operation, while the peak hs-cTnT occurred mostly within 24–48 hours after operation. Univariate logistic analysis showed that body mass index (BMI), New York Heart Association (NYHA) classification, coronary artery disease (CAD) classification, cerebrovascular disease, left ventricular ejection fraction, number of diseased vessels, valvular disease, intra-aortic balloon pump (IABP) implantation, chronic obstructive pulmonary disease, pulmonary hypertension, previous percutaneous coronary intervention (PCI), BMI, bypass graft number, cardiopulmonary bypass, and preoperative cTnT were related risk factors. Multivariate logistic regression analysis showed that NYHA classification, CAD classification, valvular disease, IABP implantation, pulmonary hypertension, previous PCI, bypass graft number, cardiopulmonary bypass, and preoperative cTnT were independent risk factors of PMI. Conclusion NYHA classification, CAD classification, valvular disease, IABP implantation, pulmonary hypertension, previous PCI, bypass graft number, cardiopulmonary bypass, and preoperative cTnT are independent risk factors of PMI in patients undergoing CABG.
Background Acute kidney injury (AKI) after coronary artery bypass grafting (CABG) surgery is associated with poor outcomes. The objective of this study was to apply a new machine learning (ML) method to establish prediction models of AKI after CABG. Methods Totally 2780 patients from two medical centers in East China who underwent primary isolated CABG were enrolled. Then the dataset was randomly divided for model training (80%) and model testing (20%). Four ML models based on LightGBM, Support vector machine (SVM), Softmax and random forest (RF) algorithms respectively were established on Python. A total of 2051 patients from two other medical centers were assigned to an external validation group to verify the performances of the ML prediction models. The models were evaluated using the area under the receiver operating characteristics curve (AUC), Hosmer-Lemeshow goodness-of-fit statistic, Bland-Altman plots, and decision curve analysis. The outcome of the LightGBM model was interpreted using SHapley Additive exPlanations (SHAP). Results The incidence of postoperative AKI in the modeling group was 13.4%. Similarly, the incidence of postoperative AKI of the two medical centers in the external validation group was 8.2% and 13.6% respectively. LightGBM performed the best in predicting, with an AUC of 0.8027 in internal validation group and 0.8798 and 0.7801 in the external validation group. The SHAP revealed the top 20 predictors of postoperative AKI ranked according to the importance, and the top three features on prediction were the serum creatinine in the first 24h after operation, the last preoperative Scr level, and body surface area. Conclusion This study provides a LightGBM predictive model that can make accurate predictions for AKI after CABG surgery. This ML model shows good predictive ability in both internal and external validation. It can help cardiac surgeons identify high-risk patients who may experience AKI after CABG surgery.
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