Citations

Abstract Aims Pulsed field ablation for atrial fibrillation offers shorter procedural times and improved safety compared with thermal ablation, but the optimal anaesthesia strategy remains uncertain. Most centres in the USA use general anaesthesia with endotracheal intubation, whereas monitored anaesthesia care without endotracheal intubation may be a safe and efficient alternative. Objectives To compare procedural efficiency and safety between monitored anaesthesia care and general anaesthesia for pulsed field ablation. Methods and results Consecutive adults who underwent pulsed field ablation for atrial fibrillation between 2024 and 2025 at Marshfield Clinic Health System were included. The anaesthesia approach was determined by operator preference. Procedural times, medication use, complications, and patient tolerance were recorded prospectively. Among 200 patients, 100 received monitored anaesthesia care without endotracheal intubation, and 100 received general anaesthesia. The mean age was 67 years, 42% were female, and the mean body mass index was 33 kilograms per square metre. Monitored anaesthesia care shortened case duration (77 vs. 95 min; P < 0.001) and laboratory time (118 vs. 153 min; P = 0.002) and required fewer adjunct medications (P < 0.001). Twenty-five procedures (25%) were challenging due to cough or motion but were all completed safely. Complications occurred in one monitored anaesthesia care case and six general anaesthesia cases (P = 0.054). Pulmonary vein isolation was achieved in all patients. Conclusion Monitored anaesthesia care without endotracheal intubation was safe, efficient, and resource-sparing compared with general anaesthesia for pulsed field atrial fibrillation ablation.

ABSTRACT Background Optimal management of direct oral anticoagulants (DOAC) prior to implantation of cardiac implantable electronic devices (CIED) remains controversial. Objective To determine whether a strategy of minimal interruption of DOAC before cardiac CIED implantation is associated with improved clinical outcomes compared to uninterrupted DOAC use. Methods The electronic clinical records of 310 patients who were on DOAC and underwent CIED implantation were evaluated. The patients were separated into 2 groups: patients in Group 1 had minimal DOAC interruption (DOAC held < 24 h before procedure), while patients in Group 2 continued DOAC before procedure. Resumption of DOAC in both groups was on the same day of the procedure or the next morning at the operator's discretion. Clinically significant pocket hematoma and thromboembolic events were compared. Results Among the 310 patients, 71 (22.9%) of them had DOAC held < 24 h before procedure, while DOAC was continued without interruption in 239 (77.1%) in the periprocedural period. Clinically significant pocket hematomas were found in 1 patient (1.4%) in the DOAC interrupted group and 24 (10.0%) in the DOAC continuous group ( p = 0.046). Low thromboembolic events were observed in both groups: 0 in the minimally interrupted group and 1 (0.4%) in the un‐interrupted group ( p > 0.05). Conclusion The bleeding risk in our cohort of patients who underwent CIED implantation with the uninterrupted DOAC approach is higher than previously reported in the literature. A minimally interrupted approach appears to mitigate this risk without significantly increasing the risk of thromboembolism.

ABSTRACT Background Optimal management in patients presenting with persistent atrial fibrillation, cardiomyopathy, and atrial as well as ventricular dyssynchrony with left bundle branch block is unclear. Results and Methods A 67‐year‐old female patient presented with persistent atrial fibrillation, cardiomyopathy with a newly reduced ejection fraction (EF), increased P wave duration on electrocardiogram (ECG) and left bundle branch block. After shared decision making, the patient elected to proceed with Bachman bundle/left bundle branch area pacing plus atrioventricular (AV) node ablation. At 6‐month follow‐up post procedure, a repeat echocardiogram showed normalized atrial size and EF (65%). Device interrogation demonstrated no recurrent atrial fibrillation with the patient off antiarrhythmic and heart failure medical therapy. Conclusions Integrated atrial and ventricular synchronization through Bachmann bundle and left bundle branch area pacing may help break the cycle of dyssynchrony, remodeling, and arrhythmia. In combination with AV node ablation, it may be considered as an alternative treatment option in certain cases after shared decision making.

Abstract Background Radiofrequency ablation (RFA) has been effective in managing premature ventricular contractions (PVCs). Despite improvement in ablation techniques, recurrence remains high for LV summit PVCs. Epicardial ablation here is often precluded due to fat and proximity to coronaries, thus, aggressive but safe endocardial options are needed. Purpose To evaluate the safety and effectiveness of ultra-long ablation (&gt;240 seconds) duration for refractory LV summit PVCs. Methods Patients with deep intramural LV summit PVCs were identified by lack of PVC elimination or late (&gt;60 s suppression) and recurrence post-lesion under the left aortic sinus of Valsalva. We included patients who received the longest RFA of at least 240 seconds (maximum 15 minutes). RFA power was titrated slowly from 20 to 35W, carefully ensuring that the impedance drop did not exceed 12 ohms. Acute procedure success was defined as clinical PVC suppression for ≥60 minutes after the last lesion. Short-term success was defined as symptom improvement, ejection fraction (EF) recovery, and drop in PVC burden at 3 months. Results Twenty patients (59.5 ± 16.4 years, 55% male) were included. Baseline features are shown in Table 1. All RFA were delivered endocardially. No steam pops were noted. PVC burden was significantly lower at 3-month follow-up (P&lt; 0.01), Figure 1A. Most patients had a normal ejection fraction (EF) at baseline; thus, no significant difference change in EF was observed (Figure 1B). One complication was recorded, which was tamponade likely caused by coronary sinus dissection requiring pericardiocentesis. Acute success was achieved in 95.0% of the cases, and all cases followed at 3 months (18/18) achieved short-term success. Conclusion Ultra-long duration RFA with lesions ≥ 240 seconds at 35W per lesion for LV summit PVCs appeared to be safe and effective in achieving acute and short-term success. The lack of acute suppression should not discourage operators, as there seems to be delayed suppression in some cases. Careful monitoring of biophysics is paramount when attempting this technique.

Abstract Objectives Heart failure (HF) impacts millions of patients worldwide, yet the variability in treatment responses remains a major challenge for healthcare professionals. The current treatment strategies, largely derived from population based evidence, often fail to consider the unique characteristics of individual patients, resulting in suboptimal outcomes. This study aims to develop computational models that are patient-specific in predicting treatment outcomes, by utilizing a large Electronic Health Records (EHR) database. The goal is to improve drug response predictions by identifying specific HF patient subgroups that are likely to benefit from existing HF medications. Materials and Methods A novel, graph-based model capable of predicting treatment responses, combining Graph Neural Network and Transformer was developed. This method differs from conventional approaches by transforming a patient's EHR data into a graph structure. By defining patient subgroups based on this representation via K-Means Clustering, we were able to enhance the performance of drug response predictions. Results Leveraging EHR data from 11 627 Mayo Clinic HF patients, our model significantly outperformed traditional models in predicting drug response using NT-proBNP as a HF biomarker across five medication categories (best RMSE of 0.0043). Four distinct patient subgroups were identified with differential characteristics and outcomes, demonstrating superior predictive capabilities over existing HF subtypes (best mean RMSE of 0.0032). Discussion These results highlight the power of graph-based modeling of EHR in improving HF treatment strategies. The stratification of patients sheds light on particular patient segments that could benefit more significantly from tailored response predictions. Conclusions Longitudinal EHR data have the potential to enhance personalized prognostic predictions through the application of graph-based AI techniques.

Abstract Aims Takotsubo syndrome (TTS) is a rare complication of vaccination. In this study, we sought to provide insight into the characteristics of reported TTS induced by vaccination. Methods and results We did a systematic review, searching PubMed, Embase, Web of Science, Ovid MEDLINE, Journals@Ovid, and Scopus databases up to 26 April 2023 to identify case reports or case series of vaccine-induced TTS. We then extracted and summarized the data from these reports. Eighteen reports were identified, with a total of 19 patients with TTS associated with vaccinations. Of the 19 included patients, the majority were female (n = 13, 68.4%) with a mean age of 56.6 ± 21.9 years. Seventeen patients developed TTS after coronavirus disease 2019 vaccination, 14 of whom received an mRNA vaccination. Two cases of TTS occurred after influenza vaccination. Among the 19 patients, 17 (89.5%) completed transthoracic echocardiography and 16 (84.2%) underwent angiography procedures. Seven patients (36.8%) completed cardiac magnetic resonance imaging. The median time to symptom onset was 2 (inter-quartile range, 1–4) days. The most common symptoms were chest pain (68.4%), dyspnoea (57.9%), and digestive symptoms (31.6%). A total of 57.9% of patients developed nonspecific symptoms such as fatigue, myalgia, diaphoresis, and fever. Among the 16 reported cases of TTS, 15 patients (93.8%) exhibited elevated cardiac troponin levels, while among the nine reported cases, eight patients (88.9%) had elevated natriuretic peptide levels. All patients had electrocardiographic changes: ST-segment change (47.1%), T-wave inversion (58.8%), and prolonged corrected QT interval (35.3%). The most common TTS type was apical ballooning (88.2%). Treatment during hospitalization typically included beta-blockers (44.4%), angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (33.3%), and diuretics (22.2%). After treatment, 81.3% of patients were discharged with improved symptoms. Among this group, nine patients (56.3%) were reported to have recovered ventricular wall motion during follow-up. Two patients (12.5%) died following vaccination without resuscitation attempts. Conclusions TTS is a rare but potentially life-threatening complication of vaccination. Typical TTS symptoms such as chest pain and dyspnoea should be considered alarming symptoms, though nonspecific symptoms are common. The risks of such rare adverse events should be balanced against the risks of infection.

Background: Catheter ablation is an effective tool to reduce ventricular tachycardia (VT) burden. There is a lack of robust data studying the characteristics and outcomes of VT ablation in patients with ischemic (ICM) versus non-ischemic cardiomyopathy (NICM). Aims: The aim of this study was to assess the impact of ICM vs NICM on outcomes of VT ablation. Methods: A single-center, retrospective study of patients undergoing catheter ablation for VT was conducted. Results: A total of 168 patients, undergoing 200 VT ablation procedures, were included in this study. NICM group (112 procedures) was compared to ICM group (88 procedures). Patients in the ICM group were older (66.6 ± 13.4 vs 58.9 ± 14.4 years) and had higher rates of prior myocardial infarction (65.9% vs 3.6) and coronary artery bypass graft surgery (40.9% vs 1.8%). Overall, ICM group had more comorbidities like hypertension (80.7% vs 52.7%), diabetes mellitus (23.9% vs 12.5%), chronic kidney disease (45.5% vs 35.7%), stroke (17% vs 7.1%), and lower left ventricular ejection fraction (36.8 ± 13.2% vs 43.1 ± 14.7%). The ICM group had lower incidence of prior cardiac valvular surgery (9.1% vs 29.5%). The inducibility of VT (93% vs 93.5%; p= 1.0) and the number of different VT morphologies induced during the case (1.9 ± 1.5 vs 2.3 ± 2.5; p=0.19) was similar between the two groups. There was no acute mortality in either group. There was a non-significant trend towards greater VT recurrence in the NICM group (43.2% vs 33.3%, p= 0.19). However, patients with NICM had a lower VT-free survival as determined by Kaplan-Meier analysis (p=0.05) [Figure]. Long term mortality was higher in ICM group when compared to NICM group (18.2% vs 8.9%, p<0.01). Conclusion: Patients undergoing VT ablation in the NICM group when compared to the ICM group were noted to be younger, had fewer comorbidities, and lower long-term mortality. However, they had significantly less VT-free survival, likely owing to more challenging substrate responsible for VT.

Introduction: Accurate pre-procedure localization of the premature ventricular contractions (PVCs) is critical in preparing for the ablation. So far, no tools exist for artificial intelligence guided PVC-localization. Hypothesis: Trained deep learning model will be able to predict the site of origin (SOO) of PVCs using 12 lead electrocardiogram (ECG). Methods: We analyzed 707 ECG-ablation pairs from 2403 patients who had at least one ECG flagged for PVCs in the 6 months prior to their procedure. First, we used a cohort of 100,000 ECGs without PVCs and 10,000 ECGs with PVCs to train a convolutional neural network (CNN) to isolate the ECG segments with PVCs in them from a 12-lead ECG (Figure 1). We then trained two models, one utilizing a 10-second 12-lead ECG, and the other with just the isolated PVC beats as input. The models were trained using the Keras framework with TensorFlow (Google). Results: The mean age of the patients in the cohort was 61.2 ± 15.0 years. 66.3 percent of patients underwent left ventricle ablation, 54.6 percent had outflow ablation, and 55.3 percent had ablation of sites with leftward axis (septal location for midline and left ventricle PVCs). The model trained on 10-second ECGs yielded validation and test AUCs of 0.941 and 0.931 for outflow, 0.898 and 0.891 for ventricle, and 0.863 and 0.846 for leftward axis (Figure 1A). The model trained on isolated segments containing PVC beats yielded validation and test AUCs of 0.966 and 0.957 for outflow, 0.879 and 0.907 for ventricle, and 0.846 and 0.829 for SOO for leftward axis (Figure 1B). Conclusions: We have trained an accurate convolutional neural network that can predict SOO using the surface ECG. Further fine-tuning would be needed to refine the model and develop prediction of specific sites.

Abstract Background Premature ventricular contractions (PVCs) are the most common arrhythmia affecting the ventricle. Frequent PVCs are associated with the development of PVC-cardiomyopathy (CM). It is known that the PVC burden has a direct correlation to the severity of left ventricular (LV) dysfunction. However, only 5% of patients with frequent PVCs (&gt;10,000 per day) have associated PVC-CM. Thus, selecting patients for therapy options with drugs or catheter ablation is challenging, especially, when patients are asymptomatic with the PVCs. Purpose To train a deep learning model to predict the probability of low LV ejection fraction (LVEF) in patients with PVCs on a 12-lead electrocardiogram (ECG). Methods Using 69,440 paired 12-lead ECGs (containing at least one PVC), and echocardiogram data, including the left ventricular ejection fraction at Mayo Clinic, we trained a convolutional neural network to identify patients with ventricular dysfunction, defined as ejection fraction ≤35%, using the ECG data alone. ECGs were acquired at a sampling rate of 500 Hz using a Marquette ECG machine (GE Healthcare) and stored using the MUSE data management system for later retrieval. Comprehensive 2-D or 3-D and Doppler echocardiography were available for all patients. We trained a convolutional neural network using the Keras framework with TensorFlow (Google). The ECG-echocardiogram pairs were divided into a 60:20:20 training:validation:test split. Results The mean age of the patients used to train the model was 69.9 ± 13.0 years, and 65.2 percent of patients were male. The mean LVEF for this population was 52 ± 14.9 %, and the proportion of patients with low LVEF was 16.8 percent. The model yielded values for area under the curve, sensitivity, specificity, and accuracy of 0.897, 0.830, 0.813, and 0.816, respectively (Figure 1). A representative example of model prediction of normal LVEF and low LVEF is shown in Figure 2. Conclusion Using large-scale data, we have trained a highly accurate convolutional neural network with excellent predictive accuracy for LV systolic dysfunction using the surface ECG. Such a tool would be invaluable for cardiologists when risk-stratifying patients with frequent PVCs, especially those that are asymptomatic. Patients at risk will benefit from early referral to electrophysiologists for drug therapy and catheter ablation to mitigate the risk of PVC-CM.Figure 1Figure 2