Background: Postoperative atrial fibrillation (POAF) is the most common complication after surgery for atherosclerotic cardiovascular disease (ASCVD) and leads to extended hospital stays and increased mortality. Myeloperoxidase (MPO) in postoperative pericardial drainage fluid is associated with an increased risk of POAF; however, the correlations between MPO in intraoperative pericardial fluid and POAF remain largely unknown. The aim of the study was to evaluate whether MPO is associated with POAF. Methods: A total of 97 patients with no history of atrial arrhythmia who had undergone coronary artery bypass surgery (CABG) were identified. We prospectively measured the levels of MPO in intraoperative pericardial fluid and blood using the human magnetic Luminex assay. Then, the occurrence of atrial fibrillation was continuously observed by postoperative ECG and telemetry strips until discharge. Results: Our data showed that POAF occurred in 24 of 97 patients (24.74%). MPO levels in blood were higher in the POAF group than the SR group (p = 0.064). Patients with POAF had significantly higher intraoperative pericardial fluid MPO levels than patients who remained in SR (p = 0.021). There was no significant correlation between pericardial fluid MPO levels and blood MPO levels (r = −0.47, p = 0.770). In a multivariable logistic regression model, pericardial fluid MPO levels were significantly associated with a higher risk of POAF (odds ratio = 1.016, 95% confidence interval, 1.001–1.031; p = 0.031). Conclusions: Higher intraoperative pericardial fluid MPO levels are linked with POAF in patients undergoing CABG. This finding provides insight into a possible mechanism of MPO in pericardial fluid increase susceptibility to developing POAF in patients undergoing CABG.

Notoginseng and safflower are commonly used traditional Chinese medicines for benefiting qi and activating blood circulation. A previous study by our group showed that the compatibility of the effective components of total saponins of notoginseng (NS) and total flavonoids of safflower (SF), named NS–SF, had a preventive effect on isoproterenol (ISO)-induced myocardial infarction (MI) in rats. However, the therapeutic effect on MI and the synergistic mechanism of NS–SF are still unclear. Therefore, integrated metabolomics, combined with immunohistochemistry and other pharmacological methods, was used to systematically research the therapeutic effect of NS–SF on MI rats and the synergistic mechanism of NS and SF. Compared to NS and SF, the results demonstrated that NS–SF exhibited a significantly better role in ameliorating myocardial damage, apoptosis, easing oxidative stress and anti-inflammation. NS–SF showed a more significant regulatory effect on metabolites involved in sphingolipid metabolism, glycine, serine, and threonine metabolism, primary bile acid biosynthesis, aminoacyl-tRNA biosynthesis, and tricarboxylic acid cycle, such as sphingosine, lysophosphatidylcholine (18:0), lysophosphatidylethanolamine (22:5/0:0), chenodeoxycholic acid, L-valine, glycine, and succinate, than NS or SF alone, indicating that NS and SF produced a synergistic effect on the treatment of MI. This study will provide a theoretical basis for the clinical development of NS–SF.

Postoperative atrial fibrillation (POAF) is a common complication after coronary artery bypass grafting (CABG) surgery. Gut microbiota and its metabolites have been implicated in the development of AF. However, whether the gut–host metabolic interaction contributes to POAF is still unknown. This study aimed to investigate the POAF-associated gut microbiota metabolism biomarkers and related risk model. The POAF (N = 30) patients and non-POAF (N = 60) patients from the discovery cohort exhibited significantly different microbiome and metabolome profiles. The differentiated features were mainly implicated in the bile acids (BAs) and short-chain fatty acids metabolism, inflammation, and oxidative stress. Random forest analysis identified the combination of five secondary BAs showed a powerful performance on predicting POAF in the discovery cohort, highlighting significant values of area under the curve (AUC = 0.954) and correct classification rate (CCR, 93.3%). In addition, the five secondary BAs-based risk model also exhibited good performance in differentiating the POAF (N = 114) and non-POAF individuals (N = 253) in an independent validation cohort (AUC = 0.872; CCR = 90.4%). This work revealed perturbed microbial and metabolic traits in POAF, providing potential avenues for the prediction and prevention of POAF after CABG.