Background: Atrial fibrillation is the most common complication after cardiac surgery and is associated with an increased risk of postoperative adverse events. The objective of this study was to develop a risk index to predict atrial fibrillation after cardiac surgery. Methods: We performed a prospective cohort study. A total of 405 patients who had undergone adult cardiac surgery from 2015 September to 2016 August at Heart Institute of HCMC and Cho Ray Hospital. Results: In the overall, 98 patients developed POAF (24.2%). The risk score included three significant risk factors (age, left atrial diameter > 41mm, Coronary Artery Bypass Graft with concomitant mitral valve replacement or repair). The point values for were 1 for the age  60, 1 for CABG with concomitant mitral valve replacement or repair and 1 for left atrial diameter > 41mm, and the total risk score ranges from 0 to 3 (AUC = 0.69, 95% CI: 0.63 – 0.75), the best cutoff point was 1 The incidences of POAF associated with scores were: patient with a score of 0, predicted probabilities of POAF was 8.6%; a score of 1: 30.1%; a score of 2: 40.8%; a score of 3: 58.3%. Bootstrapping with 5,000 samples confirmed the final model provided consistent predictions. Conclusions: We developed a simple risk score based on clinical variables and these variables can be collected easily before surgery. This risk score may help accurately stratifies the risk of POAF to identify patients at high risk of POAF before cardiac surgery.

Background: Minimally invasive mitral valve replacement has become popular across the world. However, annular rupture and patient – prosthetic mismatch (PPM) are still problematic, particularly in the Asian population. To avoid this, a predictor model could be beneficial. Our study aimed to assess the value of mitral valve diameters measured on TTE and CT scan on predicting the actual mitral prostheses. Methods: From January 2018 to December 2019, a total number of 96 patients underwent minimally invasive mitral valve replacement. The association between imaging measurements with the outcome was checked by scatter plot and Pearson’s correlation coefficient. Univariable linear regression was used to build the prediction model. Results: The three strongest correlation for the whole population are the following features: Mean TTE diameter (0.702), mean diameter on CT lowest plane through the mitral annulus (0.679), area-derived diameter on CT highest plane through the mitral annulus (0.665). The prosthetic size of the tissue valve group seemed to be more correlated to the calculated annulus diameters than that of the mechanical valve group. Tissue valve size predictor models based on these calculated diameters were 16.19 + 0.27  d (r = 0.744), 12.74 + 0.44  d (r = 0.756) and 12.79 + 0.38  d (r = 0.730), respectively. Conclusion: Mitral prosthetic size could be predicted with the mitral diameters measured on TTE and CT scan. The overall correlation coefficient varied from 0.665 (CT Scan) to 0.702 (TTE). These models performed better when applied to bioprosthesis.