OBJECTIVE: To develop an intelligent model for differential diagnosis of atrioventricular nodal re-entrant tachycardia (AVNRT) and atrioventricular re-entrant tachycardia (AVRT) using 12-lead wearable electrocardiogram devices.
METHODS: A total of 356 samples of 12-lead supraventricular tachycardia (SVT) electrocardiograms recorded by wearable devices were randomly divided into training and validation sets using 5-fold cross validation to establish the intelligent classification model, and 101 patients with the diagnosis of SVT undergoing electrophysiological studies and radiofrequency ablation from October, 2021 to March, 2023 were selected as the testing set. The changes in electrocardiogram parameters before and during induced tachycardia were compared. Based on multiscale deep neural network, an intelligent diagnosis model for classifying SVT mechanisms was constructed and validated. The 3-lead electrocardiogram signals from Ⅱ, Ⅲ, and Ⅴ1 were extracted to build new classification models, whose diagnostic efficacy was compared with that of the 12-lead model.
RESULTS: Of the 101 patients with SVT in the testing set, 68 were diagnosed with AVNRT and 33 were diagnosed with AVRT by electrophysiological study. The pre-trained model achieved a high area under the precision-recall curve (0.9492) and F1 score (0.8195) for identifying AVNRT in the validation set. The total F1 scores of the lead Ⅱ, Ⅲ, Ⅴ1, 3-lead and 12-lead intelligent diagnostic models in the testing set were 0.5597, 0.6061, 0.3419, 0.6003 and 0.6136, respectively. Compared with the 12-lead classification model, the lead-Ⅲ model had a net reclassification index improvement of -0.029 (P=0.878) and an integrated discrimination index improvement of -0.005 (P=0.965).
CONCLUSIONS: The intelligent diagnostic model based on multiscale deep neural network using wearable electrocardiogram devices has an acceptable accuracy for classifying SVT mechanisms.

Para-Hisian pacing (PHP) is among the most useful maneuvers in cardiac electrophysiology during sinus rhythm and identifies whether retrograde conduction is dependent on the atrioventricular (AV) node. In this maneuver, the retrograde activation time and pattern are compared during capture and loss of capture of the His bundle while pacing from a para-Hisian position. A common misconception about PHP is that it is useful only for septal accessory pathways (APs). However, even with left or right lateral pathways, as long as pacing from the para-Hisian region conducts to the atrium with the activation sequence being analyzed, it can be used to determine whether that activation is AV node-dependent or AP-dependent.

UNASSIGNED: Accurately determining arrhythmia mechanism from a 12-lead electrocardiogram (ECG) of supraventricular tachycardia can be challenging. We hypothesized a convolutional neural network (CNN) can be trained to classify atrioventricular re-entrant tachycardia (AVRT) vs atrioventricular nodal re-entrant tachycardia (AVNRT) from the 12-lead ECG, when using findings from the invasive electrophysiology (EP) study as the gold standard.
UNASSIGNED: We trained a CNN on data from 124 patients undergoing EP studies with a final diagnosis of AVRT or AVNRT. A total of 4962 5-second 12-lead ECG segments were used for training. Each case was labeled AVRT or AVNRT based on the findings of the EP study. The model performance was evaluated against a hold-out test set of 31 patients and compared to an existing manual algorithm.
UNASSIGNED: The model had an accuracy of 77.4% in distinguishing between AVRT and AVNRT. The area under the receiver operating characteristic curve was 0.80. In comparison, the existing manual algorithm achieved an accuracy of 67.7% on the same test set. Saliency mapping demonstrated the network used the expected sections of the ECGs for diagnoses; these were the QRS complexes that may contain retrograde P waves.
UNASSIGNED: We describe the first neural network trained to differentiate AVRT from AVNRT. Accurate diagnosis of arrhythmia mechanism from a 12-lead ECG could aid preprocedural counseling, consent, and procedure planning. The current accuracy from our neural network is modest but may be improved with a larger training dataset.

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A 2-year-old male with right isomerism was referred for supraventricular tachycardias. Atrial pacing study revealed that anterograde conduction was only through the posterior atrioventricular node. During the mapping of ventriculoatrial conduction, we identified a sharp potential resembling a His-bundle electrogram with a decremental property at the anterior wall of the common atrium. Catheter ablation for the potential eliminated the anterior ventriculoatrial conduction, thereby indicating retrograde activation of the possible anterior atrioventricular node.

Differentiation between atrioventricular nodal re-entrant tachycardia (AVNRT), atrioventricular re-entrant tachycardia (AVRT), and atrial tachycardia (AT) is often challenging during electrophysiology studies. This study compared the sensitivity and specificity of identifying anterograde His bundle activation during entrainment with commonly used right ventricular (RV) pacing maneuvers to differentiate between these types of supraventricular tachycardia (SVT).
Out of 112 consecutive patients with SVT, 90 (36 males [40%], age 37 ± 16 years) were prospectively studied. After entrainment during RV pacing, atrial response upon cessation of pacing, anterograde His activation during entrainment, stimulus-atrial (SA), ventriculoatrial (VA) intervals, and post-pacing interval minus tachycardia cycle length (PPI-TCL) were determined. Ventricular extrastimulation during tachycardia and para-Hisian pacing were performed.
The final diagnosis was AVNRT in 54, AVRT in 33, and AT in 3 patients. Entrainment was achieved in 87(96%) patients. Anterograde His bundle activation predicted AVRT (sensitivity: 62.5%, specificity: 100%). PPI-TCL ≥129 ms predicted AVNRT (sensitivity: 83%, specificity: 84%), as did SA-VA value ≥85 ms (sensitivity: 91%, specificity: 87%). Atria were advanced during transition zone in 57% of AVRTs. Atrial pre-excitation in response to progressively premature ventricular extrastimuli identified AVRT (sensitivity: 90%, specificity: 85%). Pre-excitation index ≥87 ms identified AVNRT (sensitivity: 80%, specificity: 100%). Para-Hisian pacing identified AVRT (sensitivity: 25%, specificity: 100%).
RV pacing maneuvers, applied in isolation, can misclassify a significant proportion of SVTs. Identifying anterograde His bundle activation during entrainment can complement other discriminators in differential diagnosis of SVT, with greatest sensitivity in septal and right-sided accessory pathways.

The goal of this study was to describe the clinical characteristics of pediatric patients with lone atrial fibrillation (LAF) and their treatment outcomes. The authors focused on patients who underwent ablation and compared the recurrence after ablation of supraventricular tachycardia substrates as presumed triggers versus pulmonary vein isolation (PVI).
LAF in pediatrics is rare, and outcomes remain poorly defined. Current guidelines on ablation are based on a few small studies, and we present outcomes from the largest cohort of patients after ablation.
This retrospective review included patients ≤21 years of age diagnosed with LAF from 2004 to 2015. Relevant clinical data, including recurrence rates after treatment, were tracked and analyzed with a focus on patients who underwent ablation procedures.
Sixty-two patients were identified with LAF; 88% were male, and 63% were athletes. Of the 33 patients taking antiarrhythmic medication, 20 (61%) experienced recurrence. Overall, 16 patients (26%) underwent ablation: PVI in 10 (62.5%), ablation of an accessory pathway in 3 (19%), and modification of the slow atrioventricular nodal pathway in 3 (19%). One-half of patients who underwent PVI experienced documented recurrence. Of those who solely underwent supraventricular tachycardia substrate ablation, one-half also had symptomatic or documented recurrence.
Ablation recurrence within this pediatric cohort was higher than expected. These recurrence rates may be demonstrative of the technical challenge of pediatric ablation compared with adult counterparts, characteristics of these patients such as athletic conditioning, or inherent differences in their atrial tissue, rendering it more refractory to substrate modification.

Slow pathway (SP) ablation is an acceptable, standard method for atrioventricular nodal re-entrant tachycardia (AVNRT) ablation. The exact role of SP in the human heart and the possible negative implications of SP ablation are unknown. The current case report describes an unusual, brief, functional heart block, following radiofrequency ablation of the SP. Our findings highlight the peculiar property of the SP in maintaining conduction over an atrioventricular (AV) node, in circumstances of extreme autonomic imbalance. SP can be ablated without major conduction problems for AVNRT. Careful pre-ablation evaluation of the AV conduction pattern may assist in predicting occurrences of this type of heart block.