Atrial fibrillation and heart failure are common cardiovascular conditions that are intricately linked to each other, with a significant impact on morbidity, mortality, and quality of life. These two conditions can create a vicious pathophysiologic milieu associated with neurohormonal changes, elevated cardiac filling pressure, myocardial remodeling, systemic and regional inflammation, fibrosis, and diminished myocardial contractility. It is well known that cardiomyopathy can cause atrial fibrillation and vice-versa, but often it is difficult to sort which came first. Unfortunately, the disease burden will only continue to rise with an aging population, and understanding the epidemiology of the disease and the interplay of these two conditions is vital to improved patient care.
Key points
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Atrial fibrillation and heart failure each affect approximately 60 million individuals globally, and the incidence is only expected to grow.
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The presence of heart failure increases the risk of atrial fibrillation by 4-6-fold, which in turn increases the risk of the latter and leads to a vicious cycle that is challenging to manage.
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Understanding risk factors is crucial to minimizing the risk of developing atrial fibrillation in these patients.
Introduction
Atrial fibrillation (AF) is characterized by irregular atrial activity and is the most common cardiac arrhythmia, affecting over 59 million people worldwide. The development of AF also increases the risks for several other comorbidities, including heart failure (HF), which is a significant health challenge in itself. HF arises from functional or structural dysfunction in the left ventricle (LV), affecting approximately 64 million people worldwide. The diagnosis of AF and HF is particularly noteworthy due to well-known synergistic effects on hospital admissions, healthcare costs, poor quality of life, and mortality.
The incidence of AF and HF steeply rises after 60 years of age. With an aging population, improved cardiovascular survival, and improvements in diagnostic tools, the incidence of AF and HF is expected to increase. Recognizing and understanding the epidemiology of these complex diseases at their intersection is crucial to improving survival and reducing mortality. Consequently, this review summarizes the pathophysiology, risk factors, epidemiology, screening strategies, prognosis, and future directions of AF and HF.
Relevant definitions
Guidelines for AF and HF management are periodically updated. Recognizing the most recent definitions for both is essential to best understanding their relationship, especially since the disease burden and treatment may depend on the varying degrees of disease.
HF is frequently classified by LV ejection fraction (LVEF; Table 1 ). Nevertheless, the 2022 American Heart Association/American College of Cardiology/Heart Failure Society of America guidelines emphasize the development and progression of disease ( Fig. 1 ). When combined with symptoms and functionality, as assessed by the New York Heart Association classification, worsening stages are linked to reduced survival and influence therapeutic strategies. , Similarly, AF was previously defined solely on its duration, but the 2023 American College of Cardiology/American Heart Association/European Society of Cardiology guidelines now consider it a spectrum of diseases ( Fig. 2 ). This shift in staging underscores the need to address the diseases at earlier stages upstream before significant pathophysiologic changes set in.
| HF Classification According to LVEF | Criteria |
|---|---|
| HFrEF (HF with reduced LVEF) |
|
| HFimpEF (HF with improved LVEF) |
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| HFmrEF (HF with mildly reduced LVEF) |
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| HFpEF (HF with preserved LVEF) |
|
Pathophysiology
Bidirectional Pathogenesis
The pathophysiology linking AF and HF is complex and often bidirectional ( Fig. 3 ). In HF, the increased risk of AF is due to factors that facilitate re-entry and ectopic firing. Multiple proposed mechanisms also involve neurohormonal, electrical, structural, and cellular-level remodeling. The effects of a pro-inflammatory state, widespread fibrosis, elevated LV filling pressure, and dysfunction can lead to atrial anisotropy and further activation of recognized focal triggers for AF in the right and left atria, including but not limited to the pulmonary veins, posterior wall, and crista terminalis. Likewise, AF potentiates the risk for HF through atrioventricular dyssynchrony, elevated filling pressures, tachycardia-induced myocardial dysfunction, diminished myocardial relaxation, and systemic inflammation. The relationship between AF and HF is one of the best examples of a “Chicken or Egg” phenomenon in medicine, in which one condition leads to the other, and sometimes both conditions may have a common underlying perpetrator. Distinguishing whether HF occurred due to AF or vice versa remains challenging.
Tachycardia and Atrial Fibrillation Induced Cardiomyopathy
Tachycardia-induced cardiomyopathy is a reversible systolic dysfunction that develops within days to weeks of experiencing supraventricular tachyarrhythmias. It is a well-recognized condition associated with uncontrolled AF with rapid ventricular rates. Biventricular dilatation, LV dysfunction, decreased LV contractile function, and increased LV wall stress contribute to its development. Recent data has revealed that AF-related cardiomyopathies can also occur despite appropriate rate control. In arrhythmia-induced cardiomyopathy, AF is the sole reason for LV dysfunction in a patient with no underlying heart disease ( Fig. 4 ). Whereas in arrhythmia-mediated cardiomyopathy, AF causes worsening of LV dysfunction in a patient with concomitant systolic or diastolic HF. The underlying mechanism, prevalence, and factors associated with AF-related cardiomyopathy are still unclear. Calcium dysregulation is thought to be a factor for both due to its role in cellular adhesion and proarrhythmic properties. This is supported by evidence that genetic mutations affecting its cycling can lead to dysregulated calcium homeostasis and cardiac arrhythmias.
Risk factors
AF and HF share several common risk factors. Many of these risk factors are well known to significantly influence the development of AF and HF individually, as well as each other (see Fig. 3 ). Prominent risk factors include age, obesity, hypertension, diabetes, coronary artery disease, and obstructive sleep apnea. Other important risk factors include male gender, White race, alcohol and smoking use, and decreased physical activity. There are also conditions like infiltrative and inflammatory cardiomyopathic disorders that can cause both AF and HF. Risks can be separated into modifiable – those that patients can reduce – and non-modifiable risk factors. Many times, these risk factors accumulate over decades without being adequately addressed. By the time AF or HF is present, aggressive risk factor modification is needed. For this reason, the new AF guidelines emphasize a category of individuals at risk for AF and continued modification of underlying risk factors remains key to addressing this major public health calamity.
Burden of disease
General Epidemiology
The global prevalence of both AF and HF is significant and continues to increase. Between 2030 and 2034, approximately 33 million individuals are projected to develop AF, and the prevalence will continue to grow over the next 30 years. , The incidence of HF is also anticipated to rise by 46% by 2030. The lifetime risk of AF and HF ranges from 20% to 48% and 11% to 46%, influenced by various comorbidities. This contributes to significant disability; AF alone resulted in an estimated 8.39 million disability-adjusted life years in 2019. This number is likely even higher considering the impact of HF.
Presence in Preserved Versus Reduced Ejection Fraction
Studies revealed the prevalence of AF in HF varies from 10% to 57% ( Fig. 5 ). , AF is associated with preserved LVEF (HFpEF) and reduced LVEF (HFrEF). Results from a community-based study, though, found that AF occurred 61% in HFpEF and 39% in HFrEF. These results further suggested that patients with newly diagnosed AF were more likely to develop HFpEF than HFrEF. Other studies have suggested the prevalence of HFpEF ranges from 25% to 39% and rises with worsening diastolic dysfunction. Likewise, in HFrEF, the prevalence of AF increases from 4% to 50% as the New York Heart Association functional class increases. Contrary to belief, AF in HFrEF did not result in worse outcomes. More recently, HF with a moderately reduced LVEF (HFmrEF) is recognized. The impact of AF on LV function ranges from HFrEF to HFpEF, including HFmrEF. It is influenced by many factors, including underlying baseline LV function before AF onset, AF duration, heartrates, age, concurrent valvular dysfunction, and left atrial chamber characteristics such as size, stiffness and contractility. Data regarding the incidence and prevalence of AF in HFmrEF are limited. Only a few studies suggest an incidence of AF ranging from 26% to 60% in HFmrEF. ,
Atrial Fibrillation and Heart Failure in Historical Trials
The intersection of AF and HF has been measured in several large registries. In the Framingham Heart Study, 37% of participants who developed AF had previously been diagnosed with HF, while 57% of those who developed HF were diagnosed with AF. Trials that evaluate optimal treatment options for either AF or HF also reported baseline prevalence of the respective diseases in their cohort ( Table 2 ). For example, the AFFIRM and EAST-AFNET-4 trials – two seminal trials for AF management – report that 23.1% and 28.6% of all patients had HF, respectively. , Specific trials have evaluated the optimal treatment strategy for AF within the context of HF, such as CASTLE-AF and CABANA trials. , More recently, the CASTLE-HTx trial also assessed treatment options for AF in patients with end-stage HF, demonstrating superior outcomes with ablation as compared to medical therapy. While a discussion of the trial results is beyond the scope of this article, these trials highlight the continued prevalence of the problem.
| Year | Trial | Prevalence of Heart Failure |
|---|---|---|
| Atrial Fibrillation Trials | ||
| 2002 | AFFIRM | 23.1% 475/2027 (Rate Control) vs 464/2033 (Rhythm Control) |
| 2011 | ARISTOTLE | 35.4% 3235/9120 (Apixaban) vs 3216/9081 (Warfarin) |
| 2014 | PROTECT-AF | 26.9% 124/463 (Device) vs 66/244 (Warfarin) |
| 2018 | CASTLE-AF a | 97.2% Class I: 10.7% (20/174 (Ablation) vs 19/179 (Medical Therapy)) Class II: 57.8% (101/174 (Ablation) vs 109/179 (Medical Therapy)) Class III: 27.3% (50/174 (Ablation) vs 49/179 (Medical Therapy)) Class IV: 1.4% (3/174 (Ablation) vs 2/179 (Medical Therapy)) |
| 2019 | CABANA a | 47.9% Class I: 12.7% (153/1108 (CA) vs 126/1096 (Medication) Class II/III: 35.2% (376/1108 (CA) vs 400/1096 (Medication)) |
| 2020 | EAST-AFNET-4 | 28.6% 396/1395 (Early Rhythm Control) vs 402/1394 (Usual Care) |
| 2020 | PRAGUE-17 | 44.3% 90/201 (DOAC) vs 88/201 (LAAC) |
| 2021 | AMULET IDE a | 51.4% Class I: 16.8% (147/934 (Amulet) vs 169/944 (Watchman) Class II: 27.2% (251/934 (Amulet) vs 259/944 (Watchman)) Class III: 3.7% (63/934 (Amulet) vs 76/944 (Watchman)) |
| 2023 | ADVENT | 19.4% 59/305 (PFA) vs 59/302 (Thermal Ablation) |
| 2023 | CASTLE-HTx a | 68.6% Class II: 33.0% (33/97 (Ablation) vs 28/97 (Medical Therapy)) Class III: 54.6% (52/97 (Ablation) vs 54/97 (Medical Therapy)) Class IV: 13.9% (12/97 (Ablation) vs 15/97 (Medical Therapy)) |
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