Systemic immune inflammation index as a predictor for atrial fibrillation recurrence after catheter ablation

Abstract

Atrial fibrillation (Afib) is a common arrhythmia with significant public health implications, affecting millions of individuals worldwide. Catheter ablation (CA) is an established treatment for drug-resistant Afib, yet recurrence remains a major concern, impacting quality of life in a significant portion of patients. Inflammation plays a critical role in the recurrence of Afib after ablation, with systemic inflammatory markers such as C-reactive protein being linked to higher recurrence rates. In this editorial, we discuss the study by Wang et al, published in the latest issue, which investigates the predictive role of the systemic immune inflammation index (SII) in Afib recurrence following radiofrequency CA. Elevated pre-ablation SII levels are identified as an independent predictor of recurrence, significantly enhancing the predictive power of the APPLE score. Integration of SII improved the APPLE score’s predictive performance, as shown by enhanced area under the curve, net reclassification improvement, and integrated discrimination improvement. This combined model highlights the importance of both structural and inflammatory factors in Afib recurrence, offering a more personalized approach to patient management. Additionally, the affordability and accessibility of SII enhance its practicality in clinical workflows. The study by Wang et al underscores the potential of integrating SII with existing scoring systems to refine risk stratification and optimize treatment strategies. Future research should validate these findings across diverse populations, explore limitations such as the potential influence of comorbidities on SII reliability, and investigate additional biomarkers to enhance predictive accuracy.

Key Words: Atrial fibrillation; Catheter ablation; Inflammation; C-reactive protein; Systemic immune inflammation index

Core Tip: To optimize outcomes after catheter ablation for atrial fibrillation (Afib), understanding predictors of recurrence is crucial. The systemic immune inflammation index (SII) has emerged as a practical tool to identify patients at higher risk. This biomarker, based on neutrophil, lymphocyte, and platelet counts, reflects systemic inflammation-a key driver of atrial remodeling and recurrence. Integrating SII with existing scoring systems, like the APPLE score, enhances risk prediction and allows for personalized treatment strategies, promoting better long-term outcomes and targeted care for Afib patients.

INTRODUCTION

The “key” principle for effective treatment is a comprehensive understanding of the pathophysiological mechanisms underlying a disease. Atrial fibrillation (Afib) is a prevalent arrhythmia with significant public health implications, affecting over 46 million individuals globally. However, despite more than 100 years having passed since it was first identified in a patient, the pathophysiology of this condition remains inadequately understood[1,2]. Among the armamentarium of treatments, catheter ablation (CA) has emerged as an effective intervention. Both European and American guidelines support its use in specific populations, such as patients with drug – resistant Afib or those with heart failure where tachycardia-induced cardiomyopathy is suspected[3,4].

Despite enthusiasm from the electrophysiology community regarding this intervention, studies have shown that approximately 20% to 50% of patients who undergo CA experience a recurrence of Afib within 5 years following of the procedure. the procedure, something that has a serious impact on the quality of life of this population[5]. Identifying factors linked to higher recurrence rates is essential for improving patient selection and management. Although many predictors have been reported in the literature, only a subset has been evaluated across multiple studies and established as reliable predictors[6,7].

THE ROLE OF INFLAMMATION IN ATRIAL FIBRILLATION RECURRENCE POST-CATHETER ABLATION

While effective, CA induces local and systemic inflammation, evidenced by post-procedure elevations in inflammatory markers such as C-reactive protein (CRP)[8]. This inflammatory response plays a critical role in the development of atrial fibrosis-a process in which inflammation disrupts the myocardial architecture and activates cardiac fibroblasts through inflammatory mediators[9,10]. Such processes promote structural remodeling, which impairs the conduction properties of atrial tissue and contributes to electrical remodeling, thereby increasing susceptibility of Afib recurrence[11,12].

Moreover, studies linking elevated CRP level to higher rates of early recurrence underscore the role of inflammation in post-ablation outcomes[9]. The partial efficacy of anti-inflammatory therapies, such as corticosteroids, in reducing early recurrence episodes further supports the notion that inflammation has a critical role in the pathophysiology of recurrence following ablation[13]. This highlights the importance of identifying and quantifying inflammatory markers that could predict the likelihood of recurrence after ablation.

SYSTEMIC IMMUNE INFLAMMATION INDEX AND ATRIAL FIBRILLATION RECURRENCE POST-CATHETER ABLATION

Among these markers, the systemic immune inflammation index (SII) has gained attention as a promising biomarker. SII is a composite index derived from neutrophil, lymphocyte, and platelet counts, providing a comprehensive reflection of a patient's systemic inflammatory state. Elevated neutrophil counts reflect non-specific inflammatory responses and subclinical inflammation, while reduced lymphocytes indicate impaired immune regulation, often driven by inflammation-induced apoptosis[14]. Platelets contribute to inflammation by interacting with neutrophils and promoting pro-inflammatory pathways[15]. These combined factors contribute to atrial remodeling, a key driver of Afib recurrence.

The SII has several advantages, including its affordability and ease of detection in clinical settings[15]. Initially applied in oncology for its ability to predict outcomes in various cancers[16], SII has recently gained recognition in cardiovascular research. It has demonstrated better predictive ability for major cardiovascular events compared to traditional risk factors in coronary artery disease patients after percutaneous coronary intervention[17]. Moreover, it has been shown to predict poor outcomes after elective off-pump coronary artery bypass grafting[18], new-onset Afib following myocardial infarction[19], and Afib recurrence after procedures like cryomaze concomitant with mitral valve surgery[20] and direct current cardioversion[21]. However, its relationship with Afib recurrence after RFCA is an area of ongoing investigation.

In this context, Wang et al[22] aimed to investigate whether the SII has a predictive role in Afib recurrence by retrospectively analyzing data from 457 patients with non-valvular Afib who underwent first-time radiofrequency CA. After a 12-month follow-up, 24.7% of patients experienced recurrence, with high SII levels emerging as an independent predictor of this outcome[22]. The significance of SII in predicting outcomes is further supported by findings from Ekizler et al[23], who evaluated 370 patients undergoing cryoablation for symptomatic Afib. Their analysis identified pre-ablation SII levels as an independent predictor of recurrence following the blanking period, with a hazard ratio of 2.32 (95%CI: 1.35-3.98, P = 0.002). Using a cut-off value of 532, SII demonstrated a sensitivity of 71.4% and specificity of 67.9% in predicting recurrence [area under the curve (AUC): 0.88, 95%CI: 0.67-0.80, P < 0.001]. These findings were further supported by Kaplan-Meier survival curves, which revealed a significant correlation between higher SII levels and reduced freedom from AF recurrence (log-rank, P < 0.001). Moreover, a positive correlation was observed between SII levels and high-sensitivity CRP (r: 0.340, P < 0.001), emphasizing the role of systemic inflammation in arrhythmia recurrence[23].

Prognostic scoring systems have been developed to provide a standardized, holistic risk assessment for patients undergoing CA. Common predictors integrated into these scoring systems include age, Afib type, and LA parameters, such as LA diameter and volume. Among the available scoring systems, the APPLE score stands out for its ability to predict late recurrence after radiofrequency CA. This score integrates five components: Age ≥ 65 years, persistent AF, LA diameter ≥ 43 mm, impaired renal function (estimated glomerular filtration rate ≤ 60 mL/min/1.73 m²), and reduced left ventricular ejection fraction (< 50%). Each component contributes one point, creating a simple and effective tool for risk stratification[24]. The APPLE score has been validated across multiple studies, demonstrating reliable differentiation of low-, moderate-, and high-risk populations[24].

Expanding on these results, the Wang et al[22] went a step further by integrating SII with the established APPLE score to evaluate its combined predictive utility. This approach capitalizes on the strengths of both measures-SII as a marker of systemic inflammation and the APPLE score as a composite of structural and clinical risk factors. By Enhancing the APPLE score with SII, Wang et al[22] demonstrated a significant improvement in predictive performance, as reflected by an increased AUC of 0.662 (95%CI: 0.602-0.722, P < 0.001), a net reclassification improvement of 34.1% (P < 0.001), and integrated discrimination improvement values of 4.9% and 3.5% (P < 0.001).

CLINICAL IMPLICATIONS

Despite significant advancements in the treatment of Afib, the underlying mechanisms driving Afib and its recurrence remain inadequately elucidated. Understanding these mechanisms is essential for improving treatment outcomes. The role of predictive markers, such as the SII, offers valuable insights into personalizing treatment and mitigating risks associated with Afib recurrence. This combined model highlights the multifactorial nature of Afib recurrence, encompassing both structural remodeling and inflammatory pathways, allowing clinicians to better stratify risk and tailor therapeutic strategies. The accessibility and cost-effectiveness of SII may make it a practical addition to clinical workflows. This measure is relatively straightforward, as it relies on standard blood tests often included in routine clinical evaluations. Compared to other biomarkers, such as IL-6, SII may not incur additional costs for specialized assays or equipment. Additionally, the simplicity of calculating SII from commonly available parameters-neutrophil, lymphocyte, and platelet counts-could facilitate its integration into existing clinical practices, potentially making it an efficient and scalable option for broader use.

CONCLUSION

Future research should further validate these findings across diverse populations, but it is also crucial to address potential limitations of SII as an inflammatory biomarker. While SII is derived from standard blood parameters-neutrophils, lymphocytes, and platelets-its reliability may be influenced by confounding factors, such as comorbid conditions or active infections, which could elevate these values independently of Afib recurrence risk. Future studies should not only aim to validate SII in diverse patient populations but also explore the incorporation of additional biomarkers to refine and optimize risk prediction models. This approach would provide a more detailed understanding of the inflammatory processes underlying Afib recurrence and enhance the clinical utility of predictive tools. Incorporating these considerations into research designs would bolster the robustness and generalizability of SII as a biomarker.