Jaemin Sim
Korea University · Medicine
About the Lab
Professor Jaemin Sim's research lab specializes in interventional electrophysiology, focusing on optimizing radiofrequency catheter ablation (RFCA) for atrial fibrillation (AF). The lab investigates anatomical and physiological predictors of AF recurrence, including left atrial and left atrial appendage (LAA) remodeling, wall stress, and the impact of LAA isolation on stroke risk. Utilizing advanced imaging, computational modeling (*in-silico* ablation), and artificial intelligence, the lab aims to personalize ablation strategies to improve clinical outcomes and reduce complications such as atrioesophageal fistula. Their work bridges clinical cardiology with innovative technologies to enhance procedural efficacy and safety in AF management.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15BackgroundElectrical isolation of the left atrial appendage (LAA) is associated with a lower rate of atrial fibrillation (AF) recurrence in patients undergoing radiofrequency catheter ablation. However, LAA isolation can significantly impair LAA contractility.ObjectiveThis study was performed to evaluate whether electrical isolation of the LAA is associated with an increased risk of ischemic stroke or transient ischemic attack (TIA).MethodsConsecutive patients with AF undergoing radiofrequency c
RFCA is associated with a significant increase in the PCS and MCS in AF patients. Patients without AF recurrence after RFCA had a better improvement in the PCS and MCS than patients who had AF recurrence.
<b>Objective:</b> Radiofrequency catheter ablation for persistent atrial fibrillation (PeAF) still has a substantial recurrence rate. This study aims to investigate whether an AF ablation lesion set chosen using <i>in-silico</i> ablation (V-ABL) is clinically feasible and more effective than an empirically chosen ablation lesion set (Em-ABL) in patients with PeAF. <b>Methods:</b> We prospectively included 108 patients with antiarrhythmic drug-resistant PeAF (77.8% men, age 60.8 ± 9.9 years), and
Abstract Introduction Radiofrequency catheter ablation (RFCA) in atrial fibrillation (AF) patients can cause various complications and atrioesophageal (AE) fistula is one of the most catastrophic complications of RFCA. Methods and results RFCA registries from 3 cardiovascular centers in the Republic of Korea consisted of 5721 patients undergoing 6724 procedures. Before undergoing RFCA, patients underwent either computed tomography or magnetic resonance imaging. We evaluated clinical, anatomical,
Abstract Atrial fibrillation (AF) is known to cause adverse remodeling of left atrium (LA). Radiofrequency catheter ablation (RFCA) of AF is associated with decrease in LA volume. However, the impact of RFCA on left atrial appendage (LAA) volume and hemodynamic function is not fully understood. We analyzed 123 patients who underwent cardiac magnetic resonance imaging (MRI) evaluation before and after RFCA in Korea University Anam Hospital. LA and LAA volume were measured before and after RFCA ba
Atrial stretch may contribute to the mechanism of atrial fibrillation (AF) recurrence after atrial fibrillation catheter ablation (AFCA). We tested whether the left atrial (LA) wall stress (LAW-stress [ measured ] ) could be predicted by artificial intelligence (AI) using non-invasive parameters (LAW-stress [AI] ) and whether rhythm outcome after AFCA could be predicted by LAW-stress [AI] in an independent cohort. Cohort 1 included 2223 patients, and cohort 2 included 658 patients who underwent
Atrio-esophageal fistula (AEF) is one of the most devastating complication of radiofrequency catheter ablation (RFCA) of atrial fibrillation (AF) and surgical repair is strongly recommended. However, optimal surgical approach remains to be elucidated. We retrospectively reviewed AEF cases that occurred after RFCA in a single center and evaluated the clinical results of different surgical approach. Surgical or endoscopic repair was attempted in five AF patients who underwent RFCA. Atrio-esophagea
The application of artificial intelligence (AI) algorithms to 12-lead electrocardiogram (ECG) provides promising age prediction models. We explored whether the gap between the pre-procedural AI-ECG age and chronological age can predict atrial fibrillation (AF) recurrence after catheter ablation. We validated a pre-trained residual network-based model for age prediction on four multinational datasets. Then we estimated AI-ECG age using a pre-procedural sinus rhythm ECG among individuals on anti-a
Abstract Ischemic stroke after radiofrequency catheter ablation (RFCA) in atrial fibrillation (AF) patients is a great challenge for electrophysiologists. We performed this retrospective study to evaluate clinical and echocardiographic characteristics associated with increased risk of ischemic stroke following RFCA. A total of 2,352 consecutive patients with AF who underwent first-time RFCA were analyzed. Among 10,023 patient*year follow up, ischemic stroke occurred in 49 patients (0.49% per yea
Background: Little is known about the prognostic value of nutritional status among patients undergoing atrial fibrillation (AF) catheter ablation (AFCA). We compared the risk of procedure-related complications and long-term rhythm outcomes of AFCA according to nutritional status. Methods: We included 3,239 patients undergoing de novo AFCA in 2009-2020. Nutritional status was assessed using the controlling nutritional status (CONUT) score. The association between malnutrition and the risk of AFCA
Introduction We developed a prediction model for atrial fibrillation (AF) progression and tested whether machine learning (ML) could reproduce the prediction power in an independent cohort using pre-procedural non-invasive variables alone. Methods Cohort 1 included 1,214 patients and cohort 2, 658, and all underwent AF catheter ablation (AFCA). AF progression to permanent AF was defined as sustained AF despite repeat AFCA or cardioversion under antiarrhythmic drugs. We developed a risk stratific
Research Areas
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