BACKGROUND 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.
METHODS 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.
RESULTS 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.
CONCLUSIONS 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.
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