Myocardial infarction caused by surgery: Blame inflammation not the surgeon

Changes in haemostasis and inflammatory markers after mRNA BNT162b2 and vector Ad26.CoV2.S SARS-CoV-2 vaccination

INTRODUCTION

Reported thromboembolic events after SARS-CoV-2 vaccinations are still raising concerns, predominantly in non-scientific population. The aim of our study was to investigate the differences between haemostasis and inflammatory markers in the subjects vaccinated with mRNA BNT162b2 and vector Ad26.CoV2.S vaccine.

MATERIALS AND METHODS

The study included 87 subjects vaccinated with mRNA BNT162b2 and 84 with Ad26.CoV2.S vaccine. All the laboratory parameters (TAT, F 1 + 2, IL-6, CRP, big endothelin-1, platelets, fibrinogen, D-dimers, VWF activity) were investigated for the mRNA vaccine at five (before the first dose, 7 and 14 days after the first and second vaccine dose), and three time points (before the first dose, 7 and 14 days after) for the vector vaccine, respectively. All the markers were measured by well-established laboratory methods.

RESULTS

Our results have shown statistically higher CRP levels in the vector group 7 days after vaccination (P = 0.014). Furthermore, study has revealed statistically significant rise in D-dimers (P = 0.004) between tested time points in both vaccine groups but without clinical repercussions.

CONCLUSION

Although statistically significant changes in haemostasis markers have been obtained, they remained clinically irrelevant. Thus, our study implicates that there is no plausible scientific evidence of a significant disruption in the coagulation and inflammatory processes after vaccination with BNT162b2 mRNA and Ad26.CoV2.S vector SARS-CoV-2 vaccines.

Medical record data-enabled machine learning can enhance prediction of left atrial appendage thrombosis in nonvalvular atrial fibrillation

BACKGROUND

As a major complication of non-valvular atrial fibrillation (NVAF), left atrial appendage (LAA) thrombosis is associated with cerebral ischemic strokes, as well as high morbidity. Due to insufficient incorporation of risk factors, most current scoring methods are limited to the analysis of relationships between clinical characteristics and LAA thrombosis rather than detecting potential risk. Therefore, this study proposes a clinical data-driven machine learning method to predict LAA thrombosis of NVAF.

METHODS

Patients with NVAF from January 2014 to June 2022 were enrolled from Southwest Hospital. We selected 40 variables for analysis, including demographic data, medical history records, laboratory results, and the structure of LAA. Three machine learning algorithms were adopted to construct classifiers for the prediction of LAA thrombosis risk. The most important variables related to LAA thrombosis and their influences were recognized by SHapley Addictive exPlanations method. In addition, we compared our model with CHADS2 and CHADS2-VASc scoring methods.

RESULTS

A total of 713 participants were recruited, including 127 patients with LAA thrombosis and 586 patients with no obvious thrombosis. The consensus models based on Random Forest and eXtreme Gradient Boosting LAA thrombosis prediction (RXTP) achieved the best accuracy of 0.865, significantly outperforming CHADS2 score and CHA2DS2-VASc score (0.757 and 0.754, respectively). The SHAP results showed that B-type natriuretic peptide, left atrial appendage width, C-reactive protein, Fibrinogen and estimated glomerular filtration rate are closely related to the risk of LAA thrombosis in nonvalvular atrial fibrillation.

CONCLUSIONS

The RXTP-NVAF model is the most effective model with the greatest ROC value and recall rate. The summarized risk factors obtained from SHAP enable the optimization of the treatment strategy, thereby preventing thromboembolism events and the occurrence of cardiogenic ischemic stroke.

Spark That Lights the Fire: Infection Triggers Cardiovascular Events

See Article by https://doi.org/10.1161/JAHA.118.009683

Beneficial Effects of Vaccination on Cardiovascular Events: Myocardial Infarction, Stroke, Heart Failure

Influenza and pneumococcal infections have been suggested to be potential risk factors for causing adverse cardiovascular events, especially in high-risk patients. Vaccination against respiratory infections in patients with established cardiovascular disease (CVD) could serve as a potential cost-effective intervention to improve their clinical outcomes and cardiac societies have encouraged it. Previous studies have shown that influenza vaccination reduce mortality, acute coronary syndromes and hospitalization in patients with coronary heart disease (CHD) and/or heart failure (HF). However, there is a paucity of randomized prospective clinical trials in the field of the pneumococcal vaccination, and additional higher-quality evidence is needed. Furthermore, questions around the role of vaccination in the primary prevention of CVD, the optimal dose and timing are largely unanswered. The pathophysiologic mechanism in which vaccination provides cardiovascular protection may be related to the modification of the immune-inflammatory model of atherogenesis. The present review summarizes the current evidence and understanding for vaccination against influenza and streptococcus pneumoniae in CHD, HF and stroke and highlights its beneficial effect in the reduction of adverse cardiovascular events.