Competing Risks for Monomorphic versus Non-Monomorphic Ventricular Arrhythmias in Primary Prevention Implantable Cardioverter Defibrillator Recipients: Global Electrical Heterogeneity and Clinical Outcomes (GEHCO) Study.

BACKGROUND AND AIMS: Ablation of monomorphic ventricular tachycardia (MMVT) has been shown to reduce shock frequency and improve survival. We aimed to compare cause-specific risk factors of MMVT and polymorphic ventricular tachycardia (PVT)/ventricular fibrillation (VF) and to develop predictive models. METHODS: The multicenter retrospective cohort study included 2,668 patients (age 63.1±13.0 y; 23% female; 78% white; 43% nonischemic cardiomyopathy, left ventricular ejection fraction 28.2±11.1%). Cox models were adjusted for demographic characteristics, heart failure severity and treatment, device programming, and ECG metrics. Global electrical heterogeneity was measured by spatial QRS-T angle (QRSTa), spatial ventricular gradient elevation (SVGel), azimuth, magnitude (SVGmag), and sum absolute QRST integral (SAIQRST). We compared the out-of-sample performance of the lasso and elastic net for Cox proportional hazards and the Fine-Gray competing risk model. RESULTS: During a median follow-up of 4 years, 359 patients experienced their first sustained MMVT with appropriate ICD therapy, and 129 patients had their first PVT/VF with appropriate ICD shock. The risk of MMVT was associated with wider QRSTa (HR 1.16; 95%CI 1.01-1.34), larger SVGel (HR 1.17; 95%CI 1.05-1.30), and smaller SVGmag (HR 0.74; 95%CI 0.63-0.86) and SAIQRST (HR 0.84; 95%CI 0.71-0.99). The best-performing 3-year competing risk Fine-Gray model for MMVT (ROC(t)AUC 0.728; 95%CI 0.668-0.788) identified high-risk (> 50%) patients with 75% sensitivity, 65% specificity, and PVT/VF prediction model had ROC(t)AUC 0.915 (95%CI 0.868-0.962), both satisfactory calibration. CONCLUSION: We developed and validated models to predict the competing risks of MMVT or PVT/VF that could inform procedural planning and future RCTs of prophylactic VT ablation.

P-wave alternans rebound following pulmonary vein isolation predicts atrial arrhythmia recurrence.

INTRODUCTION: Numerous P-wave indices have been explored as biomarkers to assess atrial fibrillation (AF) risk and the impact of therapy with variable success. OBJECTIVE: We investigated the utility of P-wave alternans (PWA) to track the effects of pulmonary vein isolation (PVI) and to predict atrial arrhythmia recurrence. METHODS: This medical records study included patients who underwent PVI for AF ablation at our institution, along with 20 control subjects without AF or overt cardiovascular disease. PWA was assessed using novel artificial intelligence-enabled modified moving average (AI-MMA) algorithms. PWA was monitored from the 12-lead ECG at ~1 h before and ~16 h after PVI (n = 45) and at the 4- to 17-week clinically indicated follow-up visit (n = 30). The arrhythmia follow-up period was 955 ± 112 days. RESULTS: PVI acutely reduced PWA by 48%-63% (p < .05) to control ranges in leads II, III, aVF, the leads with the greatest sensitivity in monitoring PWA. Pre-ablation PWA was ~6 µV and decreased to ~3 µV following ablation. Patients who exhibited a rebound in PWA to pre-ablation levels at 4- to 17-week follow-up (p < .01) experienced recurrent atrial arrhythmias, whereas patients whose PWA remained reduced (p = .85) did not, resulting in a significant difference (p < .001) at follow-up. The AUC for PWA's prediction of first recurrence of atrial arrhythmia was 0.81 (p < .01) with 88% sensitivity and 82% specificity. Kaplan-Meier analysis estimated atrial arrhythmia-free survival (p < .01) with an adjusted hazard ratio of 3.4 (95% CI: 1.47-5.24, p < .02). CONCLUSION: A rebound in PWA to pre-ablation levels detected by AI-MMA in the 12-lead ECG at standard clinical follow-up predicts atrial arrhythmia recurrence.

The Spatial Ventricular Gradient is Associated with Inducibility of Ventricular Arrhythmias During Electrophysiology Study.

BACKGROUND: Myocardial electrical heterogeneity is critical for normal cardiac electromechanical function, but abnormal/excessive electrical heterogeneity is proarrhythmic. The spatial ventricular gradient (SVG), a vectorcardiographic measure of electrical heterogeneity, has been associated with arrhythmic events over long-term follow-up, but its relationship with short-term inducibility of ventricular arrhythmias (VAs) is unclear. OBJECTIVE: Determine associations between SVG and inducible VAs during electrophysiology study (EPS). METHODS: Retrospective study of adults without prior sustained VA, cardiac arrest, or implantable cardioverter-defibrillator (ICD), who underwent ventricular stimulation for evaluation of syncope, non-sustained VT, and/or risk-stratification prior to primary prevention ICD implantation. 12-lead ECGs were converted into vectorcardiograms and SVG magnitude (SVGmag) and direction (azimuth and elevation) were calculated. Odds of inducible VA were regressed using logistic models. RESULTS: Among 143 patients (median age 66, 80% male, median LVEF 47%, 52% myocardial infarction), 34 (23.8%) had inducible VAs. Inducible patients had lower median LVEF (38 vs 50%, p<0.0001), smaller SVGmag (29.5 vs 39.4mV*ms, p=0.0099), and smaller cosine SVG azimuth (cosSVGaz) (0.64 vs 0.89, p=0.0007). When LVEF, SVGmag, and cosSVGaz were dichotomized at their medians, there was a 39-fold increase in adjusted odds (p=0.002) between patients with all low LVEF, SVGmag, and cosSVGaz (65% inducible), compared to patients with all high LVEF, SVGmag, and cosSVGaz (4% [n=1] inducible). After multivariable adjustment, SVGmag, cosSVGaz, and sex, but not LVEF or other characteristics, remained associated with inducible VAs. CONCLUSION: Assessment of electrical heterogeneity via SVG, which reflects abnormal electrophysiological substrate, adds to LVEF and identifies patients at high and low risk of inducible VA at EPS.

Recovery and safety with prolonged high-frequency jet ventilation for catheter ablation of atrial fibrillation: A hospital registry study from a New England healthcare network.

STUDY OBJECTIVE: To investigate post-procedural recovery as well as peri-procedural respiratory and hemodynamic safety parameters with prolonged use of high-frequency jet ventilation (HFJV) versus conventional ventilation in patients undergoing catheter ablation for atrial fibrillation. DESIGN: Hospital registry study. SETTING: Tertiary academic teaching hospital in New England. PATIENTS: 1822 patients aged 18 years and older undergoing catheter ablation between January 2013 and June 2020. INTERVENTIONS: HFJV versus conventional mechanical ventilation. MEASUREMENTS: The primary outcome was post-anesthesia care unit (PACU) length of stay. In secondary analyses we assessed the effect of HFJV on intra-procedural hypoxemia, defined as the occurrence of peripheral hemoglobin oxygen saturation (SpO2) <90%, post-procedural respiratory complications (PRC) as well as intra-procedural hypocarbia and hypotension. Multivariable negative binomial and logistic regression analyses, adjusted for patient and procedural characteristics, were applied. MAIN RESULTS: 1157 patients (63%) received HFJV for a median (interquartile range [IQR]) duration of 307 (253-360) minutes. The median (IQR) length of stay in the PACU was 244 (172-370) minutes in patients who underwent ablation with conventional mechanical ventilation and 226 (163-361) minutes in patients receiving HFJV. In adjusted analyses, patients undergoing HFJV had a longer PACU length of stay (adjusted absolute difference: 37.7 min; 95% confidence interval [CI] 9.7-65.8; p = 0.008). There was a higher risk of intra-procedural hypocarbia (adjusted odds ratio [ORadj] 5.90; 95%CI 2.63-13.23; p < 0.001) and hypotension (ORadj 1.88; 95%CI 1.31-2.72; p = 0.001) in patients undergoing HFJV. No association was found between the use of HFJV and intra-procedural hypoxemia or PRC (p = 0.51, and p = 0.97, respectively). CONCLUSION: After confounder adjustment, HFJV for catheter ablation procedures for treatment of atrial fibrillation was associated with a longer length of stay in the PACU. It was further associated with an increased risk of intra-procedural abnormalities including abnormal carbon dioxide homeostasis, as well as intra-procedural arterial hypotension.

The Use of Local Activation Timing Histogram in Ablation of Focal and Re-Entrant Atrial Tachycardias.

BACKGROUND: Activation mapping is often used to differentiate focal from re-entrant arrhythmias. This can be challenging but is critical to ablation success. The local activation time (LAT) histogram, which depicts point distribution over isochronal segments, may help characterize arrhythmia mechanisms and identify an optimal ablation strategy. OBJECTIVES: This study aimed to investigate features of the LAT histogram associated with the focal vs re-entrant mechanism of atrial tachycardias (ATs) and the use of the LAT histogram in the identification of target ablation sites. METHODS: We retrospectively evaluated cases of focal and re-entrant ATs performed at a single academic tertiary care center for which activation mapping was performed using CARTO 3 version 7 software (Biosense Webster). Baseline patient, arrhythmia, and procedural characteristics as well as LAT histogram features were evaluated for each case. LAT histogram-guided ablation targets were also compared against actual ablation sites. RESULTS: Among 52 ATs assessed, 17 were focal, and 35 were re-entrant. Tachycardia cycle length was significantly shorter in re-entrant than in focal ATs (288.2 milliseconds [Q1-Q3: 250-306.5 milliseconds] vs 370 milliseconds [Q1-Q3: 285-400 milliseconds], respectively; P = 0.006). LAT histograms contained more "valleys" in re-entrant than in focal ATs (3 [Q1-Q3: 2-4] vs 1 [Q1-Q3: 1-1]; P < 0.001). No focal ATs contained >2 and no re-entrant ATs contained <1 LAT valley(s). All successful ablation sites correlated with LAT histogram-suggested sites. CONCLUSIONS: LAT histograms can help distinguish focal from re-entrant Ats and identify effective ablation sites.

BRAVEHEART: Open-source software for automated electrocardiographic and vectorcardiographic analysis.

BACKGROUND AND OBJECTIVES: Electrocardiographic (ECG) and vectorcardiographic (VCG) analyses are used to diagnose current cardiovascular disease and for risk stratification for future adverse cardiovascular events. With increasing use of digital ECGs, research into novel ECG/VCG parameters has increased, but widespread computer-based ECG/VCG analysis is limited because there are no currently available, open-source, and easily customizable software packages designed for automated and reproducible analysis. METHODS AND RESULTS: We present BRAVEHEART, an open-source, modular, customizable, and easy to use software package implemented in the MATLAB programming language, for scientific analysis of standard 12-lead ECGs acquired in a digital format. BRAVEHEART accepts a wide variety of digital ECG formats and provides complete and automatic ECG/VCG processing with signal denoising to remove high- and low-frequency artifact, non-dominant beat identification and removal, accurate fiducial point annotation, VCG construction, median beat construction, customizable measurements on median beats, and output of measurements and results in numeric and graphical formats. CONCLUSIONS: The BRAVEHEART software package provides easily customizable scientific analysis of ECGs and VCGs. We hope that making BRAVEHART available will allow other researchers to further the field of ECG/VCG analysis without having to spend significant time and resources developing their own ECG/VCG analysis software and will improve the reproducibility of future studies. Source code, compiled executables, and a detailed user guide can be found at http://github.com/BIVectors/BRAVEHEART. The source code is distributed under the GNU General Public License version 3.

Limits of the spatial ventricular gradient and QRST angles in patients with normal electrocardiograms and no known cardiovascular disease stratified by age, sex, and race.

INTRODUCTION: Measurement of the spatial ventricular gradient (SVG), spatial QRST angles, and other vectorcardiographic measures of myocardial electrical heterogeneity have emerged as novel risk stratification methods for sudden cardiac death and other adverse cardiovascular events. Prior studies of normal limits of these measurements included primarily young, healthy, White volunteers, but normal limits in older patients are unknown. The influence of race and body mass index (BMI) on these measurements is also unclear. METHODS: Normal 12-lead electrocardiograms (ECGs) from a single center were identified. Patients with abnormal cardiovascular, pulmonary, or renal history (assessed by International Classification of Disease [ICD-9/ICD-10] codes) or abnormal cardiovascular imaging were excluded. The SVG and QRST angles were measured and stratified by age, sex, and race. Multivariable linear regression was used to assess the influence of age, BMI, and heart rate (HR) on these measurements. RESULTS: Among 3292 patients, observed ranges of SVG and QRST angles (peak and mean) differed significantly based on sex, age, and race. Sex differences attenuated with increasing age. Men tended to have larger SVG magnitude (60.4 [46.1-77.8] vs. 52.5 [41.3-65.8] mv*ms, p < .0001) and elevation, and more anterior/negative SVG azimuth (-14.8 [-25.1 to -4.3] vs. 1.3 [-9.8 to 10.5] deg, p < .0001) compared to women. Men also had wider QRST angles. Observed ranges varied significantly with BMI and HR. SVG and QRST angle measurements were robust to different filtering bandwidths and moderate fiducial point annotation errors, but were heavily affected by changes in baseline correction. CONCLUSIONS: Age, sex, race, BMI, and HR significantly affect the range of SVG and QRST angles in patients with normal ECGs and no known cardiovascular disease, and should be accounted for in future studies. An online calculator for prediction of these "normal limits" given demographics is provided at https://bivectors.github.io/gehcalc/.

Temporal Trends and Lesion Sets for Persistent Atrial Fibrillation Ablation: A Meta-Analysis With Trial Sequential Analysis and Meta-Regression.

BACKGROUND: Ablation for persistent atrial fibrillation (PsAF) has been performed for over 20 years, although success rates have remained modest. Several adjunctive lesion sets have been studied but none have become standard of practice. We sought to describe how the efficacy of ablation for PsAF has evolved in this time period with a focus on the effect of adjunctive ablation strategies. METHODS: Databases were searched for prospective studies of PsAF ablation. We performed meta-regression and trial sequential analysis. RESULTS: A total of 99 studies (15 424 patients) were included. Ablation for PsAF achieved the primary outcome (freedom of atrial fibrillation/atrial tachycardia rate at 12 months follow-up) in 48.2% (5% CI, 44.0-52.3). Meta-regression showed freedom from atrial arrhythmia at 12 months has improved over time, while procedure time and fluoroscopy time have significantly reduced. Through the use of cumulative meta-analyses and trial sequential analysis, we show that some ablation strategies may initially seem promising, but after several randomized controlled trials may be found to be ineffective. Trial sequential analysis showed that complex fractionated atrial electrogram ablation is ineffective and further study of this treatment would be futile, while posterior wall isolation currently does not have sufficient evidence for routine use in PsAF ablation. CONCLUSIONS: Overall success rates from PsAF ablation and procedure/fluoroscopy times have improved over time. However, no adjunctive lesion set, in addition to pulmonary vein isolation, has been conclusively demonstrated to be beneficial. Through the use of trial sequential analysis, we highlight the importance of adequately powered randomized controlled trials, to avoid reaching premature conclusions, before widespread adoption of novel therapies.

Correlation Between Functional Substrate Mapping and Cardiac Computed Tomography-Derived Wall Thinning for Ventricular Tachycardia Ablation.

BACKGROUND: Functional substrate mapping during baseline rhythm can identify arrhythmogenic tissue during ventricular tachycardia (VT) ablation. Wall thinning and wall thickness channels (WTCs) derived from computed tomography angiography have been shown to correlate with low voltage and VT isthmuses. The correlation between functional substrate mapping, wall thinning, and WTCs in patients with infarct- or non-infarct-related cardiomyopathies (ICM and NICM, respectively) has not been previously described. OBJECTIVES: The purpose of this study was to correlate cardiac CTA-derived myocardial wall thinning with functional VT substrate mapping using isochronal late activation mapping. METHODS: In 34 patients with ICM or NICM undergoing VT ablation who had a preprocedure computed tomography angiography, myocardial wall thinning was segmented in layers of 1 to 5 mm. Areas of wall thinning and WTCs were then spatially correlated with deceleration zones (DZs) from registered left ventricular endocardial isochronal late activation maps. RESULTS: In 21 ICM patients and 13 NICM patients, ICM patients had greater surfaces areas of wall thinning (P < 0.001). In ICM patients, 94.1% of primary DZs were located on areas of wall thinning, compared to 20% of DZs in NICM patients overall but 50% if there was any wall thinning present. Fifty-nine percent of DZs in ICM patients and 56% of DZs in NICM patients were located near WTCs. The positive predictive value for WTC in localizing DZs was 22.5% and 37.8% in ICM and NICM patients, respectively. CONCLUSIONS: Wall thinning is highly sensitive for functional substrate in ICM patients. WTCs had modest sensitivity for functional substrate but low positive predictive value for identifying DZs in ICM and NICM patients. These findings suggest that wall thinning may facilitate more efficient mapping in ICM patients, but WTCs are insufficient to localize wavefront discontinuities.

Individuals with chronic epilepsy have elevated P-wave heterogeneity comparable to patients with atrial fibrillation.

OBJECTIVE: Identification of epilepsy patients with elevated risk for atrial fibrillation (AF) is critical given the heightened morbidity and premature mortality associated with this arrhythmia. Epilepsy is a worldwide health problem affecting nearly 3.4 million people in the United States alone. The potential for increased risk for AF in patients with epilepsy is not well appreciated, despite recent evidence from a national survey of 1.4 million hospitalizations indicating that AF is the most common arrhythmia in people with epilepsy. METHODS: We analyzed inter-lead heterogeneity of P-wave morphology, a marker reflecting arrhythmogenic nonuniformities of activation/conduction in atrial tissue. The study groups consisted of 96 patients with epilepsy and 44 consecutive patients with AF in sinus rhythm before clinically indicated ablation. Individuals without cardiovascular or neurological conditions (n = 77) were also assessed. We calculated P-wave heterogeneity (PWH) by second central moment analysis of simultaneous beats from leads II, III, and aVR ("atrial dedicated leads") from standard 12-lead electrocardiography (ECG) recordings from admission day to the epilepsy monitoring unit (EMU). RESULTS: Female patients composed 62.5%, 59.6%, and 57.1% of the epilepsy, AF, and control subjects, respectively. The AF cohort was older (66 ± 1.1 years) than the epilepsy group (44 ± 1.8 years, p < .001). The level of PWH was greater in the epilepsy group than in the control group (67 ± 2.6 vs. 57 ± 2.5 µV, p = .046) and reached levels observed in AF patients (67 ± 2.6 vs. 68 ± 4.9 µV, p = .99). In multiple linear regression analysis, PWH levels in individuals with epilepsy were mainly correlated with the PR interval and could be related to sympathetic tone. Epilepsy remained associated with PWH after adjustments for cardiac risk factors, age, and sex. SIGNIFICANCE: Patients with chronic epilepsy have increased PWH comparable to levels observed in patients with AF, while being ~20 years younger, suggesting an acceleration in structural change and/or cardiac electrical instability. These observations are consistent with emerging evidence of an "epileptic heart" condition.

Reduction in atrial and ventricular electrical heterogeneity following pulmonary vein isolation in patients with atrial fibrillation.

BACKGROUND: Pulmonary vein isolation (PVI) modulates the intrinsic cardiac autonomic nervous system and reduces atrial fibrillation (AF) recurrence. METHODS: In this retrospective analysis, we investigated the impact of PVI on ECG interlead P-wave, R-wave, and T-wave heterogeneity (PWH, RWH, TWH) in 45 patients in sinus rhythm undergoing clinically indicated PVI for AF. We measured PWH as a marker of atrial electrical dispersion and AF susceptibility and RWH and TWH as markers of ventricular arrhythmia risk along with standard ECG measures. RESULTS: PVI acutely (16 ± 8.9 h) reduced PWH by 20.7% (from 31 ± 1.9 to 25 ± 1.6 µV, p < 0.001) and TWH by 27% (from 111 ± 7.8 to 81 ± 6.5 µV, p < 0.001). RWH was unchanged after PVI (p = 0.068). In a subgroup of 20 patients with longer follow-up (mean = 47 ± 3.7 days after PVI), PWH remained low (25 ± 1.7 µV, p = 0.01), but TWH partially returned to the pre-ablation level (to 93 ± 10.2, p = 0.16). In three individuals with early recurrence of atrial arrhythmia in the first 3 months after ablation, PWH increased acutely by 8.5%, while in patients without early recurrence, PWH decreased acutely by 22.3% (p = 0.048). PWH was superior to other contemporary P-wave metrics including P-wave axis, dispersion, and duration in predicting early AF recurrence. CONCLUSION: The rapid time course of decreased PWH and TWH after PVI suggests a beneficial influence likely mediated via ablation of the intrinsic cardiac nervous system. Acute responses of PWH and TWH to PVI suggest a favorable dual effect on atrial and ventricular electrical stability and could be used to track individual patients' electrical heterogeneity profile.

Artificial intelligence-enabled electrocardiogram to distinguish atrioventricular re-entrant tachycardia from atrioventricular nodal re-entrant tachycardia.

Background: 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. Methods: 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. Results: 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. Conclusion: 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.

A Focus on the Right Atrium: Right Atrial Diverticulum and Atrial Flutter.

We report a case of a 70-year-old woman who presented for a cavotricuspid isthmus atrial flutter ablation that was aborted prematurely. On subsequent imaging, she was discovered to have a right atrial diverticulum, which was present on prior imaging but not reported, likely due to unfamiliarity with the entity. (Level of Difficulty: Intermediate.).

The spatial ventricular gradient is associated with adverse outcomes in acute pulmonary embolism.

BACKGROUND: The spatial ventricular gradient (SVG) is a vectorcardiographic measurement that reflects cardiac loading conditions via electromechanical coupling. OBJECTIVES: We hypothesized that the SVG is correlated with right ventricular (RV) strain and is prognostic of adverse events in patients with acute pulmonary embolism (PE). METHODS: Retrospective, single-center study of patients with acute PE. Electrocardiogram (ECG), imaging, and outcome data were obtained. SVG components were regressed on tricuspid annular plane systolic excursion (TAPSE), qualitative RV dysfunction, and RV/left ventricular (LV) ratio. Odds of adverse outcomes (30-day mortality, vasopressor requirement, or advanced therapy) after PE were regressed on demographics, RV/LV ratios, traditional ECG signs of RV dysfunction, and SVG components using a logit model. RESULTS: ECGs from 317 patients (48% male, age 63.1 ± 16.6 years) with acute PE were analyzed; 36 patients (11.4%) experienced an adverse event. Worse RV hypokinesis, larger RV/LV ratio, and smaller TAPSE were associated with smaller SVG X and Y components, larger SVG Z components, and smaller SVG vector magnitude (p < .001 for all). In multivariable logistic regression, odds of adverse events after PE decreased with increasing SVG magnitude and TAPSE (OR 0.32 and 0.54 per standard deviation increase; p = .03 and p = .004, respectively). Receiver operating characteristic (ROC) analysis showed that, when combined with imaging, replacing traditional ECG criteria with the SVG significantly improved the area under the ROC from 0.70 to 0.77 (p = .01). CONCLUSION: The SVG is correlated with RV dysfunction and adverse outcomes in acute PE and has a better prognostic value than traditional ECG markers.

A fully-automated paper ECG digitisation algorithm using deep learning.

There is increasing focus on applying deep learning methods to electrocardiograms (ECGs), with recent studies showing that neural networks (NNs) can predict future heart failure or atrial fibrillation from the ECG alone. However, large numbers of ECGs are needed to train NNs, and many ECGs are currently only in paper format, which are not suitable for NN training. We developed a fully-automated online ECG digitisation tool to convert scanned paper ECGs into digital signals. Using automated horizontal and vertical anchor point detection, the algorithm automatically segments the ECG image into separate images for the 12 leads and a dynamical morphological algorithm is then applied to extract the signal of interest. We then validated the performance of the algorithm on 515 digital ECGs, of which 45 were printed, scanned and redigitised. The automated digitisation tool achieved 99.0% correlation between the digitised signals and the ground truth ECG (n = 515 standard 3-by-4 ECGs) after excluding ECGs with overlap of lead signals. Without exclusion, the performance of average correlation was from 90 to 97% across the leads on all 3-by-4 ECGs. There was a 97% correlation for 12-by-1 and 3-by-1 ECG formats after excluding ECGs with overlap of lead signals. Without exclusion, the average correlation of some leads in 12-by-1 ECGs was 60-70% and the average correlation of 3-by-1 ECGs achieved 80-90%. ECGs that were printed, scanned, and redigitised, our tool achieved 96% correlation with the original signals. We have developed and validated a fully-automated, user-friendly, online ECG digitisation tool. Unlike other available tools, this does not require any manual segmentation of ECG signals. Our tool can facilitate the rapid and automated digitisation of large repositories of paper ECGs to allow them to be used for deep learning projects.

Feasibility and safety of same-day discharge and shortened bedrest after atrial fibrillation ablation.

BACKGROUND: While initial studies suggest that same-day discharge or shortened bedrest may be feasible for some patients following atrial fibrillation (AF) ablation, the risks and benefits of this approach remain unclear for patients undergoing hemostasis with figure-of-eight (FO8) suture technique. METHODS: We prospectively evaluated access site bleeding, length of hospitalization, urinary catheterization, and other clinical outcomes in patients undergoing AF ablation with 3 hours of bedrest between April and May 2021, and compared them to a control group that had undergone AF ablation with 6 hours of bedrest from April to July 2019. FO8 sutures were used for hemostasis in all patients. Independent risk factors for bleeding and urinary catheterization were determined using multiple logistic regression. RESULTS: Same-day discharge was achieved in 74% of patients in the 3-hour bedrest group compared to 7% of patients in the 6-hour bedrest group (p < 0.001). There were no differences between 3-hour and 6-hour bedrest groups in the rates of serious adverse events (2% vs. 1%, p = 0.45) or rehospitalizations or ED visits (1% vs. 3%, p = 0.45) within 30 days of ablation. The 3-hour bedrest group showed a non-significant trend toward more access site bleeding (15% vs. 8%, p = 0.10), but had a significant reduction in urinary catheterization (27% vs. 64%, p < 0.001) and opioid analgesia use (20% vs. 33%, p = 0.04). CONCLUSIONS: Same-day discharge after 3 hours of bedrest is safe and feasible following AF ablation and is not associated with higher rates of complications or rehospitalizations at 30 days. Reduced bedrest resulted in decreased opioid analgesia and urinary catheterization.

Wide Complex Tachycardia and Cardiac Arrest During Endoscopy.

A 59-year-old man presented for implantable cardioverter-defibrillator placement after a wide QRS complex tachycardia cardiac arrest at an outside hospital. In this case report, we discuss the differential diagnosis of this patient's tachyarrhythmia and the electrophysiological studies that established the diagnosis and guided management. (Level of Difficulty: Intermediate.).

Artificial intelligence-enabled electrocardiogram to distinguish cavotricuspid isthmus dependence from other atrial tachycardia mechanisms.

Aims: Accurately determining atrial arrhythmia mechanisms from a 12-lead electrocardiogram (ECG) can be challenging. Given the high success rate of cavotricuspid isthmus (CTI) ablation, identification of CTI-dependent typical atrial flutter (AFL) is important for treatment decisions and procedure planning. We sought to train a convolutional neural network (CNN) to classify CTI-dependent AFL vs. non-CTI dependent atrial tachycardia (AT), using data from the invasive electrophysiology (EP) study as the gold standard. Methods and results: We trained a CNN on data from 231 patients undergoing EP studies for atrial tachyarrhythmia. A total of 13 500 five-second 12-lead ECG segments were used for training. Each case was labelled CTI-dependent AFL or non-CTI-dependent AT based on the findings of the EP study. The model performance was evaluated against a test set of 57 patients. A survey of electrophysiologists in Europe was undertaken on the same 57 ECGs. The model had an accuracy of 86% (95% CI 0.77-0.95) compared to median expert electrophysiologist accuracy of 79% (range 70-84%). In the two thirds of test set cases (38/57) where both the model and electrophysiologist consensus were in agreement, the prediction accuracy was 100%. Saliency mapping demonstrated atrial activation was the most important segment of the ECG for determining model output. Conclusion: We describe the first CNN trained to differentiate CTI-dependent AFL from other AT using the ECG. Our model matched and complemented expert electrophysiologist performance. Automated artificial intelligence-enhanced ECG analysis could help guide treatment decisions and plan ablation procedures for patients with organized atrial arrhythmias.