Establishment Of A Scoring Model For New-onset Postoperative Atrial Fibrillation After Off-pump Coronary Artery Bypass Grafting: Using R Studio To Draw Dynamic Nomogram

Objective:To explore the incidence and individualized risk factors of new-onset atrial fibrillation in patients undergoing off-pump coronary artery bypass grafting(OPCAB-POAF).Established an OPCAB-POAF scoring system to provide reference for the prevention and treatment of OPCAB-POAF.Content:Collected clinical data of patients undergoing elective off-pump coronary artery bypass grafting(OPCAB),counted the number of new postoperative atrial fibrillation(POAF)cases,and calculate the incidence;According to POAF diagnostic criteria,we divided the collected data into the POAF group and the Non-POAF group which subjected to statistical description and difference analysis,and then regression analysis was carried out to explore the risk factors of OPCAB-POAF;according to the risk factors of OPCAB-POAF,the dynamic nomogram was drawn using R language to construct OPCAB-POAF Scoring model,and evaluate the discrimination and calibration of the model.Methods:This study was designed in a case-control study.A review of the clinical data of456 patients undergoing elective OPCAB at the Department of Cardiac Surgery,Union Hospital of Fujian Medical University from June 2018 to December 2020.According to the clinical diagnostic criteria of POAF,patients were divided into POAF group(n=101)and Non-POAF group(n=355),and the differences in clinical data between the two groups were compared.Single factor Logistic regression was used to screen the factors related to OPCAB-POAF,and multivariate Logistic regression analysis was used to find out independent risk factors for OPCAB-POAF.Using R Studio to establish a Nomogram prediction model for the selected independent risk factors,and verify the predictability and accuracy of the model.Result:1.The overall incidence of new atrial fibrillation after off-pump coronary artery bypass grafting was 22.15%;2.Single factor Logistic regression found that diabetes,hypertension,history of cerebrovascular accidents,previous PCI history,NYHA grade ≥ grade III,left ventricular ejection fraction <55%,left atrial diameter increase(>35mm),low potassium concentration(<4.5mmol/L)of last blood gas analysis in the operation is related to the occurrence of POAF;3.Multivariate logistic regression found that diabetes,previous PCI history,left atrial diameter enlargement(>35mm),and low potassium concentration(<4.5mmol/L)of last blood gas analysis in the operation were independent risk factors for POAF;4.Using R language to establish a dynamic nomogram model of POAF risk score,Hosmer-Lemeshow and ROC curve proved that the model has good predictive ability;Calibration curve and Bootstrap proved that the model has good accuracy and distinguishability.Conclusion:1.The independent risk factors of OPCAB-POAF are mainly diabetes,previous PCI history,left atrial inner diameter increase(>35mm),and last intraoperative blood potassium concentration(<4.5mmol/L).2.Establish a dynamic Nomogram model based on the independent risk factors of OPCAB-POAF,which has a good degree of discrimination and calibration.