Coronary Artery Disease and Atrial Fibrillation: A Bidirectional Mendelian Randomization Study

NSTEMI mortality and hospital outcomes in patients with atrial fibrillation: A propensity score-matched analysis

Background

Atrial fibrillation (AF) is associated with increased cardiovascular mortality. Data regarding the relationship between coronary artery disease (CAD) and AF is mixed. It is uncertain if AF directly increases the risk for future coronary events and if such patients are appropriately evaluated for CAD.

Methods

This cross-sectional study was performed on hospitalized patients with NSTEMI and concurrent AF in 2019 using the National Inpatient Sample. In-hospital mortality, rates of diagnostic cardiac angiography, percutaneous coronary intervention, ventricular tachycardiac (VT), ventricular fibrillation (VF), cardiogenic shock, cardiac arrest, length of stay (LOS), and total hospitalization charges were studied.

Results

A total of 433,965 patients met inclusion criteria (169,725 females [39.1 %], 307,985 Caucasian [71 %], 51,570 African American [11.8 %], 37,265 Hispanic [8.6 %]; mean [SD] age, 67.9 [6.2] years). 86,200 (19.8 %) patients with NSTEMI had AF, including 32,775 (38 %) female patients before propensity matching. Patients with NSTEMI and AF had increased odds of mortality (adjusted Odds ratio, 1.32; CI, 1.21-1.43; p < 0.001). AF patients were less likely to undergo diagnostic coronary angiography and PCI and had higher odds of VT, VF, cardiogenic shock, cardiac arrest, tracheal intubation, mechanical ventilation, increased LOS, and higher hospital charges than those without AF.

Conclusion

AF was independently associated with increased mortality and serious cardiac complications in patients admitted with NSTEMI.

New-onset atrial fibrillation among COVID-19 patients: A narrative review

Over the last three years, research has focused on examining cardiac issues arising from coronavirus disease 2019 (COVID-19) infection, including the emergence of new-onset atrial fibrillation (NOAF). Still, no clinical study was conducted on the persistence of this arrhythmia after COVID-19 recovery. Our objective was to compose a narrative review that investigates COVID-19-associated NOAF, emphasizing the evolving pathophysiological mechanisms akin to those suggested for sustaining AF. Given the distinct strategies involved in the persistence of atrial AF and the crucial burden of persistent AF, we aim to underscore the importance of extended follow-up for COVID-19-associated NOAF. A comprehensive search was conducted for articles published between December 2019 and February 11, 2023, focusing on similarities in the pathophysiology of NOAF after COVID-19 and those persisting AF. Also, the latest data on incidence, morbidity-mortality, and management of NOAF in COVID-19 were investigated. Considerable overlaps between the mechanisms of emerging NOAF after COVID-19 infection and persistent AF were observed, mostly involving reactive oxygen pathways. With potential atrial remodeling associated with NOAF in COVID-19 patients, this group of patients might benefit from long-term follow-up and different management. Future cohort studies could help determine long-term outcomes of NOAF after COVID-19.

Roles of gut microbiota in atrial fibrillation: insights from Mendelian randomization analysis and genetic data from over 430,000 cohort study participants

BACKGROUND

Gut microbiota imbalances have been suggested as a contributing factor to atrial fibrillation (AF), but the causal relationship is not fully understood.

OBJECTIVES

To explore the causal relationships between the gut microbiota and AF using Mendelian randomization (MR) analysis.

METHODS

Summary statistics were from genome-wide association studies (GWAS) of 207 gut microbial taxa (5 phyla, 10 classes, 13 orders, 26 families, 48 genera, and 105 species) (the Dutch Microbiome Project) and two large meta-GWASs of AF. The significant results were validated in FinnGen cohort and over 430,000 UK Biobank participants. Mediation MR analyses were conducted for AF risk factors, including type 2 diabetes, coronary artery disease (CAD), body mass index (BMI), blood lipids, blood pressure, and obstructive sleep apnea, to explore the potential mediation effect of these risk factors in between the gut microbiota and AF.

RESULTS

Two microbial taxa causally associated with AF: species Eubacterium ramulus (odds ratio [OR] 1.08, 95% confidence interval [CI] 1.04-1.12, P = 0.0001, false discovery rate (FDR) adjusted p-value = 0.023) and genus Holdemania (OR 1.15, 95% CI 1.07-1.25, P = 0.0004, FDR adjusted p-value = 0.042). Genus Holdemania was associated with incident AF risk in the UK Biobank. The proportion of mediation effect of species Eubacterium ramulus via CAD was 8.05% (95% CI 1.73% - 14.95%, P = 0.008), while the proportion of genus Holdemania on AF via BMI was 12.01% (95% CI 5.17% - 19.39%, P = 0.0005).

CONCLUSIONS

This study provided genetic evidence to support a potential causal mechanism between gut microbiota and AF and suggested the mediation role of AF risk factors.

The bidirectional association between atrial fibrillation and myocardial infarction

Atrial fibrillation (AF) is associated with an increased risk of myocardial infarction (MI) and vice versa. This bidirectional association relies on shared risk factors as well as on several direct and indirect mechanisms, including inflammation, atrial ischaemia, left ventricular remodelling, myocardial oxygen supply-demand mismatch and coronary artery embolism, through which one condition can predispose to the other. Patients with both AF and MI are at greater risk of stroke, heart failure and death than patients with only one of the conditions. In this Review, we describe the bidirectional association between AF and MI. We discuss the pathogenic basis of this bidirectional relationship, describe the risk of adverse outcomes when the two conditions coexist, and review current data and guidelines on the prevention and management of both conditions. We also identify important gaps in the literature and propose directions for future research on the bidirectional association between AF and MI. The Review also features a summary of methodological approaches for the study of bidirectional associations in population-based studies.

Epidemiology, Trends, Utilization Disparities, and Outcomes of Catheter Ablation and Its Association With Coronary Vasospasm Amongst Patients With Non-valvular Atrial Fibrillation: A Nationwide Burden of Last Decade

BACKGROUND

Catheter ablation (CA) is an important curative treatment for non-valvular atrial fibrillation (NVAF), however, nationwide data on its utilization and disparities is limited. Coronary vasospasm is a rare, life-threatening, peri-operative complication of CA with limited literature in Caucasians.

METHODS

We performed a retrospective study on adult hospitalizations in the USA from 2007 to 2017 by obtaining the data from National Inpatient Sample. The primary endpoints of our study were to identify the utilization rate of CA, disparities in utilization, and study the outcomes associated with CA. The secondary endpoints of the study were to identify the incidence of coronary vasospasm amongst patients who underwent CA, evaluate their association, and identify the predictors of coronary vasospasm.

RESULTS

From 35,906,946 patients with NVAF, 343641 (0.96%) underwent CA. Its utilization decreased from 1% in 2007 to 0.71% in 2017. Patients who underwent CA, compared to those without CA, fared better in terms of hospital length of stay, mortality rate, disability rate, and discharge to the non-home facility. Patients in the 50-75 years age group, Native Americans, those with private insurance, and median household income of 76-100th percentile were associated with higher odds of CA utilization. Urban teaching hospitals and large-bedded hospitals performed more ablations, while the Mid-West region fared lower than the South, the West, and the Northeast. The prevalence of coronary vasospasm was higher amongst CA in comparison without CA, however, in regression analysis, no significant association was demonstrated between CA and coronary vasospasm.

CONCLUSION

CA is an important treatment modality that is associated with improved clinical outcomes. Identification of factors associated with lower utilization of CA and its disparities will help to mitigate the burden associated with NVAF.

Atrial fibrillation and coronary artery disease: An integrative review focusing on therapeutic implications of this relationship

The incidence of both atrial fibrillation (AF) and coronary artery disease (CAD) increases with advancing age. They share common risk factors and very often coexist. Evidence points to an intricate relationship between atrial tissue excitability and neuronal remodeling with ischemia at the microcirculatory level. In this review, we delineated this complex relationship, identified a common theme between the two, and discussed how the knowledge of this relationship translates into a positive and meaningful impact in patient management. Recent research indicates a high prevalence of CAD among AF patients undergoing coronary angiography. Further, the incidence of AF is much higher in those suffering from CAD compared to age-matched adults without CAD underlying this reciprocal relationship. CAD adversely affects AF by promoting progression via re-entry and increasing excitability of atrial tissue as a result of ischemia and electrical inhomogeneity. AF in turn accelerates atherosclerosis via endothelial dysfunctional and inflammation and together with enhanced thrombogenicity and hypercoagulability contribute to micro and macrothrombi throughout cardiovascular system. In a nutshell, the two form a vicious cycle wherein one disease promotes the other. Most AF recommendations focuses on rate/rhythm control and prevention of thromboembolism. Very few studies have discussed the importance of unmasking coexistent CAD and how the treatment of underlying ischemia will impact the burden of AF in these patients. Inflammation and endothelial dysfunction remain central to both disease processes and form a handsome therapeutic target in the management of the two diseases. The relationship between AF and CAD is complex and much more than mere coincidence. The two diseases share common risk factor and pathophysiology. Hence, it is impractical to treat them in isolation. Accordingly, we share the implications of managing underlying ischemia and inflammation to positively impact and improve quality of life among AF patients.

New Perspectives on Risk Stratification and Treatment in Patients with Atrial Fibrillation: An Analysis of Recent Contributions on the Journal of Cardiovascular Disease and Development

The medical approach to atrial fibrillation (AF) underwent a paradigm shift over time, evolving from considering AF as a simple arrhythmic phenomenon to a complex nosological entity [...].

Predictive Classifier for Cardiovascular Disease Based on Stacking Model Fusion

The etiology of cardiovascular disease is still an unsolved world problem, and high morbidity, disability, and mortality are the main characteristics of cardiovascular diseases. There is, therefore, a need for effective and rapid early prediction of likely outcomes in patients with cardiovascular disease using artificial intelligence (AI) techniques. The Internet of Things (IoT) is becoming a catalyst for enhancing the capabilities of AI applications. Data are collected through IoT sensors and analyzed and predicted using machine learning (ML). Existing traditional ML models do not handle data inequities well and have relatively low model prediction accuracy. To address this problem, considering the data observation mechanism and training methods of different algorithms, this paper proposes an ensemble framework based on stacking model fusion, from Support Vector Machines (SVM), K-Nearest Neighbor (KNN), Logistic Regression (LR), Random Forest (RF), Extra Tree (ET), Gradient Boosting Decision Tree (GBDT), XGBoost, LightGBM, CatBoost, and Multilayer Perceptron (MLP) (10 classifiers to select the optimal base learners). In order to avoid the overfitting phenomenon generated by the base learners, we use the Logistic Regression (LR) simple linear classifier as the meta learner. We validated the proposed algorithm using a fused Heart Dataset from several UCI machine learning repositories and another publicly available Heart Attack Dataset, and compared it with 10 single classifier models. The experimental results show that the proposed stacking classifier outperforms other classifiers in terms of accuracy and applicability.