Phenomapping in Atrioventricular Nodal Reentrant Tachycardia: Mechanistic Insights and Therapeutic Implications

ABSTRACT Background Traditional classifications of atrioventricular nodal reentrant tachycardia (AVNRT) based on cardiac symptomatology, electrocardiographic findings, and reentrant circuits do not capture the full heterogeneity of AVNRT. Objective This study sought to identify distinct phenotypes among patients with AVNRT by using two‐step cluster analysis and to determine differential effects of phenotypes on clinical and procedural outcomes. Methods All patients ( n = 305) underwent catheter ablation and ajmaline challenge testing. A two‐step cluster analysis was conducted using 17 demographic/clinical, anthropometric, electrocardiographic, echocardiographic, and anatomic variables. Results Three distinct clinically and mechanistically relevant clusters were identified. Cluster 1 (Metabolic/Structural Phenotype, n = 44) patients were characterized by older age of onset of AVNRT (53.5 ± 8.5, 43.5 ± 15, and 24.7 ± 10.5 years, p = 4.9 × 10 −31 ), shorter distance between coronary sinus floor and His bundle potential (22.7 ± 6.1, 24.7 ± 6.8, and 29 ± 7.5 mm, p = 1.3 × 10 −7 ), higher prevalence of “correlated” (diagnosed ≥ 4 years before AVNRT onset) type 2 diabetes (100%, 0%, and 0%, p = 5.9 × 10 −67 ) and “correlated” (diagnosed ≥ 6 years before AVNRT onset) structural heart disease (86.4%, 100%, 0%, p = 3.5 × 10 −62 ) compared to Cluster 2 (Structural Phenotype, n = 78) and Cluster 3 (Anatomic/Genetic Phenotype, n = 183) patients, respectively. Cluster 1 patients had higher prevalence of “pro‐arrhythmia” (new‐onset and/or symptom worsening/intolerance) with anti‐arrhythmic therapy and/or non‐cardiac drugs (74.2%, 46.5%, and 31.6%, p = 1.5 × 10 −4 ), AH prolongation/AV‐VA block (20.5%, 7.7%, and 2.2%, p = 8.9 × 10 −5 ) and aborted ablation (11.4%, 1.3%, and 0%, p = 8.6 × 10 −5 ) during EP study compared to Clusters 2 and 3 patients, respectively. Conclusion Phenomapping identified three clinically and mechanistically relevant phenotypes of AVNRT associated with clinical and procedural outcomes, underscoring the considerable heterogeneity of AVNRT and the importance of comorbidities and substrates.

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Journal
Journal of Cardiovascular Electrophysiology
Published
2026-07-26
DOI
https://doi.org/10.1111/jce.70439
Primary Topic
Cardiac Arrhythmias and Treatments
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article
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article

Phenomapping in Atrioventricular Nodal Reentrant Tachycardia: Mechanistic Insights and Therapeutic Implications

Charles Antzelevitch, Mehmet N. ORMAN, Umut Kocabaş, Can Hasdemir et al.
Journal of Cardiovascular Electrophysiology
Cardiac Arrhythmias and Treatments
article

Phenomapping in Atrioventricular Nodal Reentrant Tachycardia: Mechanistic Insights and Therapeutic Implications

Charles Antzelevitch, Mehmet N. ORMAN, Umut Kocabaş, Can Hasdemir, Burcu Yağmur, Gülden Hakverdi, Faruk Bulut
article en

Abstract

ABSTRACT Background Traditional classifications of atrioventricular nodal reentrant tachycardia (AVNRT) based on cardiac symptomatology, electrocardiographic findings, and reentrant circuits do not capture the full heterogeneity of AVNRT. Objective This study sought to identify distinct phenotypes among patients with AVNRT by using two‐step cluster analysis and to determine differential effects of phenotypes on clinical and procedural outcomes. Methods All patients ( n = 305) underwent catheter ablation and ajmaline challenge testing. A two‐step cluster analysis was conducted using 17 demographic/clinical, anthropometric, electrocardiographic, echocardiographic, and anatomic variables. Results Three distinct clinically and mechanistically relevant clusters were identified. Cluster 1 (Metabolic/Structural Phenotype, n = 44) patients were characterized by older age of onset of AVNRT (53.5 ± 8.5, 43.5 ± 15, and 24.7 ± 10.5 years, p = 4.9 × 10 −31 ), shorter distance between coronary sinus floor and His bundle potential (22.7 ± 6.1, 24.7 ± 6.8, and 29 ± 7.5 mm, p = 1.3 × 10 −7 ), higher prevalence of “correlated” (diagnosed ≥ 4 years before AVNRT onset) type 2 diabetes (100%, 0%, and 0%, p = 5.9 × 10 −67 ) and “correlated” (diagnosed ≥ 6 years before AVNRT onset) structural heart disease (86.4%, 100%, 0%, p = 3.5 × 10 −62 ) compared to Cluster 2 (Structural Phenotype, n = 78) and Cluster 3 (Anatomic/Genetic Phenotype, n = 183) patients, respectively. Cluster 1 patients had higher prevalence of “pro‐arrhythmia” (new‐onset and/or symptom worsening/intolerance) with anti‐arrhythmic therapy and/or non‐cardiac drugs (74.2%, 46.5%, and 31.6%, p = 1.5 × 10 −4 ), AH prolongation/AV‐VA block (20.5%, 7.7%, and 2.2%, p = 8.9 × 10 −5 ) and aborted ablation (11.4%, 1.3%, and 0%, p = 8.6 × 10 −5 ) during EP study compared to Clusters 2 and 3 patients, respectively. Conclusion Phenomapping identified three clinically and mechanistically relevant phenotypes of AVNRT associated with clinical and procedural outcomes, underscoring the considerable heterogeneity of AVNRT and the importance of comorbidities and substrates.

Journal of Cardiovascular Electrophysiology
Sivas Cumhuriyet Üniversitesi (TR), Thomas Jefferson University (US), Lankenau Institute for Medical Research (US), Ege University (TR), Lankenau Heart Institute (US), University of Kyrenia (CY)
Good health and well-being
Openalex Percentile: Top 9%
Cardiac Arrhythmias and Treatments
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