Long-term effects of radiofrequency ablation on symptom severity, depression, anxiety and quality of life in patients with atrial fibrillation: a longitudinal observational study

Abstract

Introduction

Atrial fibrillation (AF) is the most common cardiac arrhythmia, significantly affecting patients’ quality of life (QoL) and increasing the risk of complications such as heart failure, stroke and dementia. In addition to the physical burden, psychological distress, including depression and anxiety, is prevalent among patients with AF and can exacerbate clinical symptoms and worsen overall well-being. While radiofrequency ablation (RFA) is widely used for rhythm control in AF, its long-term effects on both physical and psychological outcomes, including symptom severity, anxiety, depression and QoL, remain underexplored. This study aims to investigate the long-term impact of RFA on both physical and psychological health in patients with AF, using network analysis to explore symptom interrelationships and their collective influence on QoL.

Methods and analysis

This longitudinal observational study will investigate the evolution of symptom severity, depression, anxiety and QoL in patients with AF undergoing RFA. Data will be collected at four time points: preprocedure (T0), 3 months (T1), 6 months (T2) and 12 months (T3) postprocedure. The study will employ network analysis to examine the dynamic interactions between physical and psychological symptoms, focusing on core symptoms and their impact on patient outcomes. To assess symptom severity, depression, anxiety and QoL, the following standardised tools will be used: the Atrial Fibrillation Severity Scale, Patient Health Questionnaire-9, Generalised Anxiety Disorder-7 and WHO Quality of Life—Brief Version, respectively. Statistical analyses will include network analysis with R software to explore the interrelationships between symptoms, as well as repeated measures multivariate analysis of variance (MANOVA) to assess changes over time and interactions among variables.

Ethics and dissemination

The study was approved by the Ethics Committee of the Second Affiliated Hospital, Zhejiang University School of Medicine (SAHZU, No 20250128) and will be conducted in accordance with the Helsinki Declaration and its amendments. Results will be published in peer-reviewed journals, presented at scientific conferences and shared through various popular science forums and patient organisations.

STRENGTHS AND LIMITATIONS OF THIS STUDY.

• The study tracks data over four time points, offering insights into the dynamic relationship between anxiety, depression, physical symptoms and quality of life (QoL) in patients with AF.

• A range of validated scales is used to measure anxiety, depression, physical symptoms and QoL, ensuring a well-rounded evaluation of the patients’ health.

• The study has strong statistical power, increasing the reliability of the results.

• Potential limitations include attrition bias due to participant dropouts over time, as well as response bias related to social desirability when completing self-reported questionnaires.

• Conducting the study at a single hospital in Hangzhou may limit its applicability to other populations or regions.

Introduction

Atrial fibrillation (AF) is the most common cardiac arrhythmia, caused by multiple re-entry circuits within the atrial tissue that disrupt normal heart rhythm, resulting in irregular atrial contractions.¹ As one of the foremost global health challenges, AF continues to rise in prevalence, particularly among ageing populations, further intensifying the societal burden associated with this condition.2,4 In China, AF affects approximately 1.6% of the adult population, corresponding to an estimated 20 million individuals.⁵ AF is strongly associated with a spectrum of severe complications, including heart failure, cerebrovascular thromboembolism, dementia and myocardial infarction.⁶ In addition to these life-threatening conditions, AF significantly elevates the risk of mortality.^{3 7} The clinical manifestations of AF, such as irregular heart rhythms, palpitations and chest discomfort, can be profoundly distressing, with some patients experiencing a debilitating sense of impending death.^{8 9} However, the symptom burden of AF varies significantly among patients. While some individuals endure severe symptoms, others may remain asymptomatic or report only mild discomfort.¹⁰

Beyond its physiological impact, AF also significantly impairs patients’ quality of life (QoL). Studies have shown that the incidence of anxiety and depression in AF patients is significantly higher compared with the general population.^{11 12} These psychological health issues not only exacerbate the severity of AF symptoms but also considerably affect patients’ overall well-being and long-term health outcomes.^{13 14} The symptoms and complications of AF often limit patients’ ability to perform daily activities and engage in social interactions, further contributing to heightened emotional distress. As a result, patients become more susceptible to developing anxiety and depression.^{15 16} Moreover, many patients misattribute their physical discomfort to cardiac dysfunction, given the heart’s pivotal role in sustaining life.¹⁷ This misattribution often amplifies their anxiety and psychological distress, intensifying the emotional burden associated with AF.^{16 18 19} Reports indicate that over one-third of AF patients experience clinically significant depression and anxiety during the course of their disease management.^{20 21}

Beyond its physiological impact, AF significantly impairs patients’ QoL. As a chronic and recurrent arrhythmia, AF causes a range of physical symptoms—such as palpitations, fatigue and dyspnoea—that interfere with daily functioning and social participation, even in the absence of structural heart disease.^{8 22} The unpredictable nature of AF further contributes to a sense of loss of control and reduced well-being.⁹ Disease-specific assessments, including the Atrial Fibrillation Effect on QualiTy-of-life (AFEQT) questionnaire, consistently show that symptom burden and psychological distress are major determinants of QoL impairment in AF patients.²³ Among these, anxiety and depression are particularly prevalent and act as both consequences and drivers of poor QoL.^{13 14} These conditions heighten symptom perception, reduce treatment adherence²⁴ and perpetuate emotional and physical deterioration.²⁵ Moreover, misinterpretation of benign symptoms as life-threatening events often amplifies psychological distress. Studies indicate that over one-third of AF patients experience clinically significant levels of depression and anxiety,^{20 21} which independently correlate with reduced QoL and adverse outcomes.²⁶ Therefore, comprehensive AF management should address both physical and psychological domains to optimise QoL.

Radiofrequency ablation (RFA) is a widely used and effective treatment for AF. However, its benefits and outcomes remain subjects of ongoing debate. While some studies suggest that RFA significantly improves symptom severity, depression, anxiety and QoL in AF patients,^{27 28} other studies present contrasting views, indicating that the effects may not be as substantial as expected.^{20 29} Conversely, other research has found that, over time, patients experience a gradual improvement in QoL following RFA.³⁰ Therefore, it is essential to explore the longitudinal trajectories of disease severity, depression, anxiety and QoL in Chinese patients undergoing RFA for AF.

Network analysis is a novel approach that offers a more profound insight into the relationships and interactions between various symptoms.³¹ By assessing and visualising symptom clusters as dynamic systems of interacting elements, network analysis allows for exploring symptoms in their full complexity.32,34 It also offers a framework for comparing clustering patterns across different populations or at various measurement time points.³³ Core symptoms within a network are those with the strongest associations with other symptoms, and they may play a critical role in triggering or exacerbating the symptoms.³⁵ Consequently, targeting these core symptoms could facilitate the design of more cost-effective interventions that impact the entire symptom cluster. However, despite the growing interest in network analyses of symptoms, there is no consensus on which symptoms are considered core in patients with AF who experience symptom severity, depression, anxiety and impaired QoL. This lack of consensus is likely due to the variability of core symptoms, which can differ based on factors such as the specific population studied, the phase of the AF trajectory and the methodology employed.

This study will be a longitudinal observational study designed to assess the evolution of symptoms (ie, symptom severity, depression and anxiety) and their relationship with QoL in patients with AF both preprocedure and 12 months postprocedure, using network analyses. The primary hypothesis is that certain core symptoms, identified through network analysis, will have a significant impact on patient outcomes, including the overall QoL and mental health status. Given the growing recognition of the psychological burden of AF, particularly in relation to depression and anxiety, this study aims to fill a gap in the current literature by providing a nuanced understanding of how these symptoms evolve over time. It is important to note that the findings from this study, particularly the core symptoms identified at each stage, will inform a future study focused on developing targeted psychological interventions for patients with AF. This research also has the potential to guide clinical practices in improving patient care, particularly in the management of psychological comorbidities, ultimately leading to enhanced patient outcomes. The results could influence clinical guidelines, with a focus on integrating psychological assessments and interventions into the standard care regimen for patients with AF.

Methods

Design and procedures

This single-arm observational study aims to evaluate the progression of symptom severity, depression, anxiety and QoL in patients with AF. The primary objective is to explore the long-term effects of RFA on the physical and psychological well-being of patients with AF by revealing the interrelationships and evolution of these symptoms over time. Given the ongoing debate regarding the extent to which RFA can significantly improve the psychological health (particularly depression and anxiety) of patients with AF, this study will specifically focus on identifying the patterns of psychological changes that occur before and after RFA. By doing so, it aims to provide empirical evidence that can inform the development of more effective clinical interventions, ultimately enhancing the quality of care provided and improving the overall QoL for patients with AF.

Outcome data will be collected from March 2025 to December 2026. Patients will be assessed at four key time points: preprocedure (T0), 3 months (T1), 6 months (T2), and 12 months (T3) postprocedure, as outlined in table 1. These time points have been strategically selected to capture both the immediate and longer-term psychological effects of the intervention. In addition to symptom-related measures, two time-varying covariates—newly developed comorbidities and medication changes—will be collected at T1, T2 and T3. These variables are included to account for clinical changes that may influence psychological outcomes and symptom networks over time. With the inclusion of 18 variables, the network model will comprise a total of 171 parameters. Following the recommended guideline of 3–5 patients per parameter,³⁶ and accounting for a 10% dropout rate, the sample size will need to be increased by 10%. Consequently, the adjusted sample size will range from 564 to 940 participants, ensuring sufficient statistical power to detect meaningful associations and provide reliable insights into the psychological outcomes for patients with AF.

Table 1. Overview of variables collected at each time point.

Category	Measurement tool/variable	T0	T1	T2	T3
Demographics	Including age, gender, education level, occupation and other basic characteristics	✔️	–	–	–
Clinical data	Including AF type, comorbidities, medication use and other clinical information	✔️	–	–	–
AF symptoms	Atrial Fibrillation Severity Scale	✔️	✔️	✔️	✔️
Depression	Patient Health Questionnaire	✔️	✔️	✔️	✔️
Anxiety	Generalised Anxiety Disorder Scale	✔️	✔️	✔️	✔️
Quality of life	WHO Quality of Life—Brief Version	✔️	✔️	✔️	✔️
New comorbidities	Newly diagnosed physical or mental health conditions	–	✔️	✔️	✔️
Medication changes	Initiation, discontinuation or adjustment of treatment	–	✔️	✔️	✔️

AF, atrial fibrillation.

A single-arm design was adopted for this study due to both practical and ethical considerations. In the participating hospital, RFA is typically scheduled shortly after hospital admission, and there is no formal or systematic waiting list for the procedure. As a result, it is not feasible to identify a clinically comparable patient group that remains untreated during the study period. Additionally, ethical concerns prevent intentionally delaying a standard treatment for research purposes. Therefore, a longitudinal design without a control group was deemed most appropriate to explore the symptom trajectories and psychological outcomes associated with RFA in real-world clinical settings.

Primary outcomes

This study’s primary outcomes are designed to evaluate both the physical and psychological impact of AF on patients. These include: (1) symptom severity: evaluating the severity of common AF symptoms, such as palpitations, fatigue and shortness of breath, to understand the burden on daily functioning. (2) Depression: measuring the severity of depressive symptoms, reflecting the psychological burden of AF on patients’ QoL. (3) Anxiety: anxiety levels will be assessed, as anxiety is a common issue in AF patients and can worsen physical symptoms, further diminishing QoL. (4) QoL: this outcome evaluates overall well-being, encompassing both physical and psychological health, and how AF affects patients’ daily activities, emotional state and social interactions.

Secondary outcomes

The secondary outcomes include: (1) changes in depression and anxiety: monitoring the changes in depression and anxiety symptoms over time. (2) Impact of medication changes: evaluating how adjustments in medication affect symptoms, depression, anxiety and QoL. (3) Impact of new comorbidities: assessing how newly developed comorbidities affect symptoms, depression, anxiety and QoL.

Setting

This study will be conducted at a tertiary hospital in Hangzhou, Zhejiang Province, a renowned public institution recognised for its comprehensive management systems. These systems ensure that all inpatients are integrated into the electronic medical record system, facilitating efficient and accurate data collection. Additionally, questionnaires will be distributed through the Questionnaire Star platform, ensuring smooth and seamless participant engagement. The study will focus on patients with AF who are hospitalised in the cardiovascular medicine departments between March and December 2025, and who meet the inclusion criteria. These patients will be closely followed up until December 2026, allowing for a thorough longitudinal assessment of their health outcomes and responses to the intervention.

Recruitment

The inclusion criteria for this study will be as follows: patients aged 18 years or older; hospitalised with a diagnosis of AF; able to participate in follow-up assessments via telephone and use a smartphone; capable of understanding the study’s purpose and willing to provide written informed consent.

The exclusion criteria will include: patients with terminal or severely compromised health that would hinder their ability to complete the questionnaires; individuals who are unable to read, understand or complete the questionnaires in Chinese; and those with a history of depression, anxiety or other organic mental disorders. Information on psychiatric history will be obtained through a combination of medical record review and direct inquiries to the patient and/or their caregiver during the baseline assessment.

Assessments

Atrial Fibrillation Severity Scale (AFSS)

The AFSS is a disease-specific tool designed to assess the severity of AF and monitor symptom progression over time.³⁷ This study will use Part C of the AFSS, which includes seven items that evaluate the severity of symptoms experienced over the past 4 weeks. Each item is scored from 0 to 5, with higher scores indicating more severe symptoms. The AFSS has demonstrated strong reliability and validity across various populations.^{38 39} As no officially published Chinese version is currently available, a pilot validation will be conducted to evaluate its psychometric properties, including content validity, internal consistency (Cronbach’s α), and test–retest reliability, to ensure suitability for use in the Chinese clinical context.⁴⁰

Patient Health Questionnaire (PHQ-9)

To assess depressive symptoms among patients with AF, we will use the Chinese version of the PHQ-9.⁴¹ This instrument includes items based on the nine criteria for major depressive disorder as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. These criteria encompass anhedonia, depressed mood, sleep disturbances, low energy, appetite changes, feelings of guilt, difficulty concentrating, motor symptoms and suicidal thoughts. Each item on the PHQ-9 is rated on a 4-point Likert scale, with responses ranging from 0 (indicating ‘not at all’) to 3 (indicating ‘almost every day’). The total score, which ranges from 0 to 27, reflects the severity of depressive symptoms, with higher scores indicating more severe depression. The Chinese version of the PHQ-9 has been validated for use in Chinese populations, and this version has previously been employed effectively for screening depressive symptoms in patients with AF.⁴²

Generalised Anxiety Disorder Scale (GAD-7)

Building on the widespread use of the PHQ-9 for assessing and monitoring depression severity, the GAD-7 was developed as a seven-item tool for screening panic and anxiety symptoms. The GAD-7 includes items that evaluate common anxiety symptoms, specifically nervousness, uncontrollable worry, excessive worry, difficulty relaxing, restlessness, irritability and fear. Each item is rated on a 4-point Likert scale: 0 (not at all), 1 (several days), 2 (more than half the days) and 3 (nearly every day). The total score on the GAD-7 ranges from 0 to 21, with higher scores reflecting more severe anxiety symptoms. Both the English and Chinese versions of the GAD-7 have been validated for use in clinical settings.^{43 44} Furthermore, the GAD-7 has been demonstrated to reliably measure anxiety symptoms in patients with AF, exhibiting strong internal consistency and composite reliability.⁴²

WHO Quality of Life—Brief Version (WHOQOL-BREF)

The WHOQOL-BREF is a widely used tool for assessing QoL across four domains: physical, psychological, social and environmental, along with two overall QoL items and health perceptions. It includes 26 items, scored from 1 to 5, where higher scores indicate better QoL. Raw scores for each domain are transformed into a 0–100 scale. The Chinese version of the WHOQOL-BREF will be used to evaluate the subjective QoL of patients with AF. The tool’s high internal consistency across domains ensures its effectiveness in assessing QoL, including in patients with AF.⁴⁵ It has been widely used among Chinese populations and has demonstrated satisfactory reliability and validity across various clinical and research settings.46,48

Statistical analyses

All data will be analysed using R V.4.4.2 (31 October 2024). Basic demographic characteristics, symptom severity, and measures of depression, anxiety and QoL will be summarised using frequencies, percentages, means and SD, providing a comprehensive overview of the sample. Data processing will use R packages compatible with V.4.4.2, focusing on those supporting network analysis and visualisation, such as qgraph, igraph and statnet.^{49 50} These tools will enable a clear visualisation of the symptom network, enhancing understanding of the structure and dynamic associations between symptoms over time.

To estimate the network structure, standardised z-scores will be calculated for each variable, ensuring comparability across different measures. This normalisation step will enable a more accurate representation of symptom relationships. The network’s characteristics will be assessed through three centrality indices: strength, closeness and betweenness. Strength quantifies the intensity of a symptom’s direct connections, with higher values indicating greater prominence within the network. Closeness assesses how strongly a symptom correlates with others, with more closely connected symptoms being central. Betweenness evaluates a symptom’s role in facilitating pathways between other symptoms, with higher betweenness indicating greater influence. Additionally, edge centrality will be used to examine the significance of the connections between symptom pairs, providing insight into the interrelationships driving the network’s overall structure.

Symptom networks will be constructed at four measurement time points: T0, T1, T2 and T3. Network comparison tests will be conducted to explore how these networks evolve over time, shedding light on potential shifts in symptom associations and whether certain symptoms become more central or exhibit stronger connections at specific time points. Such changes may reflect the evolving nature of conditions like AF and the impact of clinical interventions or treatment modalities.

To complement the symptom variables, newly developed comorbidities and medication changes during the follow-up period will be incorporated into the network analysis as time-varying covariates. These variables will be coded as binary (eg, presence versus absence of a new condition) or categorical (eg, types of medications or treatment changes) nodes, depending on their nature. In R, this will be implemented by expanding the node set at each time point to include these variables, followed by constructing joint symptom-covariate networks using the qgraph package, allowing for the estimation of conditional dependencies between clinical events and psychological outcomes.

In addition to network analysis, repeated measures multivariate analysis of variance (MANOVA) will be employed to examine the evolution of key variables, including symptom severity, depression, anxiety and QoL. This analysis will explore both the temporal changes in these variables and their interactions with the symptom networks. It will assess whether fluctuations in psychological factors influence the structure or dynamics of the symptom networks, potentially highlighting feedback loops between symptoms and overall well-being. If significant differences are found, post-hoc comparisons will identify the time points or variables driving these changes, offering insights into how psychological and behavioural factors shape the symptom network and their broader implications for the health outcomes and QoL of patients with AF.

Ethics and dissemination

All procedures in this study will be conducted in accordance with the ethical standards established by the institutional and national research committees, the General Data Protection Regulation, and the 1964 Declaration of Helsinki, along with its subsequent amendments or other comparable ethical guidelines. The study has been granted ethical approval by the Ethics Committee of the Second Affiliated Hospital of Zhejiang University School of Medicine (Ethics Approval No 20250128). Ethics approval was obtained prior to the recruitment of participants. Informed consent, in writing, is required from all participants.

The results of this study will be disseminated in a timely manner through academic conferences and peer-reviewed journals. The study protocol and clinical research data will be made publicly available following the publication of the primary manuscript in a peer-reviewed journal. These data will be provided on reasonable request, with further details to be included in the main manuscript.

Discussion

AF remains a complex clinical condition, not only due to its physiological manifestations but also because of the profound psychological impact it imposes on patients. Recent studies have brought to light the significant psychological burden experienced by individuals suffering from AF,^{12 13} particularly in terms of depression and anxiety, which are increasingly recognised as core components of the disease’s overall symptomatology.^{10 51} These emotional disturbances, far from being secondary or co-occurring symptoms, seem to exacerbate the physical manifestations of AF, compounding the overall burden on the patient and significantly impairing their QoL.⁵² However, despite growing recognition of this psychological burden, there is a notable lack of consensus on which specific symptom—whether physical, anxiety or depression—emerges as the most central in determining the patient’s QoL.

One of the critical questions that this study seeks to answer is the identification of the most ‘core’ symptom among symptom severity, depression and anxiety, with the hypothesis that one of these psychological disturbances may serve as the central node in the symptom network, thus playing a pivotal role in influencing the progression of the disease and the patient’s well-being. In particular, we propose that anxiety or depression, given their pervasive and often interdependent nature, will be the most central symptoms across multiple time points, exerting a direct influence on both physical symptom severity and overall QoL. This hypothesis is grounded in the observation that the psychological impact of AF is not merely a secondary concern but plays a substantial role in both disease progression and management. Anxiety and depression, common comorbidities in AF, can directly interfere with patients’ perceptions of their health, aggravating the physical symptoms they experience.⁵³ The mental toll of living with AF often amplifies the perception of physical symptoms, creating a feedback loop where psychological distress worsens physical health, and vice versa.^{12 54} Thus, anxiety and depression can form a network of interrelated symptoms that disproportionately influence both the severity of AF and the broader QoL outcomes.

In our study, we anticipate that the symptom network will evolve, with the relationships between physical and psychological symptoms likely becoming more complex as time progresses. For instance, the impact of RFA on symptom severity may lead to a reduction in physical discomfort, but whether this will translate into improvements in psychological well-being remains to be fully understood. Given the dynamic nature of symptom interaction, it is hypothesised that the psychological symptoms of anxiety and depression will maintain or even strengthen their centrality in the symptom network, especially if patients continue to struggle with the mental toll of living with AF despite improvements in physical symptoms.

The results of this study could have far-reaching implications for clinical practice, particularly in the management of AF patients. Currently, the focus in AF management tends to be primarily on physical symptoms, such as arrhythmia control and stroke prevention.⁵⁵ However, this study underscores the importance of integrating psychological health into the management paradigm for AF. Given that psychological symptoms—particularly anxiety and depression—may be central to the patient experience, it may be crucial for clinicians to implement more comprehensive, multi-disciplinary care approaches that address both the physical and psychological aspects of AF. A better understanding of how these symptoms interact with physical symptom severity could lead to more effective interventions, particularly in the development of psychological support strategies. Intervening early in the symptom trajectory, especially in managing anxiety and depression, could potentially halt or slow the progression of the disease by breaking the feedback loop that exacerbates both physical and emotional distress.^{56 57}

The present study has several limitations. First, the generalisability of the findings is constrained by the single-centre design, which may not reflect the broader population of patients with AF across various regions or healthcare settings. The reliance on self-reported measures introduces potential biases, including social desirability and recall bias, especially among patients with elevated anxiety or depression, and may fail to fully capture the psychological burden of patients with AF. Additionally, while a 10% dropout rate is anticipated, this could be higher, leading to attrition bias, as patients who drop out may differ in symptom severity or psychological health, which could affect the study’s conclusions. Finally, the absence of a control group of patients with AF who did not undergo RFA limits the ability to isolate the effects of RFA on symptom severity and psychological outcomes, as any observed improvements could result from factors such as spontaneous recovery or concurrent treatments.