Panayotis K Vlachakis, Panagiotis Theofilis, Athanasios Kordalis, Dimitris Tousoulis
{"title":"Systemic immune inflammation index as a predictor for atrial fibrillation recurrence after catheter ablation.","authors":"Panayotis K Vlachakis, Panagiotis Theofilis, Athanasios Kordalis, Dimitris Tousoulis","doi":"10.4330/wjc.v17.i3.103993","DOIUrl":null,"url":null,"abstract":"<p><p>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 <i>et al</i>, 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 <i>et al</i> 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.</p>","PeriodicalId":23800,"journal":{"name":"World Journal of Cardiology","volume":"17 3","pages":"103993"},"PeriodicalIF":1.9000,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11947955/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Journal of Cardiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4330/wjc.v17.i3.103993","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0
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.