A 12-Lead ECG Database to Identify Origins of Idiopathic Ventricular Arrhythmia Containing 334 Patients

Cardiac catheter ablation has shown the effectiveness of treating the idiopathic premature ventricular complex and ventricular tachycardia. As the most important prerequisite for successful therapy, criteria based on analysis of 12-lead ECGs are employed to reliably speculate the locations of idiopathic ventricular arrhythmia before a subsequent catheter ablation procedure. Among these possible locations, right ventricular outflow tract and left outflow tract are the major ones. We created a new 12-lead ECG database under the auspices of Chapman University and Ningbo First Hospital of Zhejiang University that aims to provide high quality data enabling detection of the distinctions between idiopathic ventricular arrhythmia from right ventricular outflow tract to left ventricular outflow tract. The dataset contains 334 subjects who successfully underwent a catheter ablation procedure that validated the accurate origins of idiopathic ventricular arrhythmia

An Artificial Intelligence-Based Noninvasive Solution to Estimate Pulmonary Artery Pressure

Aims: Design to develop an artificial intelligence (AI) algorithm to accurately predict the pulmonary artery pressure (PAP) waveform using non-invasive signal inputs. Methods and results: We randomly sampled training, validation, and testing datasets from a waveform database containing 180 patients with pulmonary atrial catheters (PACs) placed for PAP waves collection. The waveform database consisted of six hemodynamic parameters from bedside monitoring machines, including PAP, artery blood pressure (ABP), central venous pressure (CVP), respiration waveform (RESP), photoplethysmogram (PPG), and electrocardiogram (ECG). We trained a Residual Convolutional Network using a training dataset containing 144 (80%) patients, tuned learning parameters using a validation set including 18 (10%) patients, and tested the performance of the method using 18 (10%) patients, respectively. After comparing all multi-stage algorithms on the testing cohort, the combination of the residual neural network model and wavelet scattering transform data preprocessing method attained the highest coefficient of determination R2 of 90.78% as well as the following other performance metrics and corresponding 95% confidence intervals (CIs): mean square error of 11.55 (10.22–13.5), mean absolute error of 2.42 (2.06–2.85), mean absolute percentage error of 0.91 (0.76–1.13), and explained variance score of 90.87 (85.32–93.31). Conclusion: The proposed analytical approach that combines data preprocessing, sampling method, and AI algorithm can precisely predict PAP waveform using three input signals obtained by noninvasive approaches

A High Precision Machine Learning-Enabled System for Predicting Idiopathic Ventricular Arrhythmia Origins

Background: Radiofrequency catheter ablation (CA) is an efficient antiarrhythmic treatment with a class I indication for idiopathic ventricular arrhythmia (IVA), only when drugs are ineffective or have unacceptable side effects. The accurate prediction of the origins of IVA can significantly increase the operation success rate, reduce operation duration and decrease the risk of complications. The present work proposes an artificial intelligence-enabled ECG analysis algorithm to estimate possible origins of idiopathic ventricular arrhythmia at a clinical-grade level accuracy. Method: A total of 18,612 ECG recordings extracted from 545 patients who underwent successful CA to treat IVA were proportionally sampled into training, validation and testing cohorts. We designed four classification schemes responding to different hierarchical levels of the possible IVA origins. For every classification scheme, we compared 98 distinct machine learning models with optimized hyperparameter values obtained through extensive grid search and reported an optimal algorithm with the highest accuracy scores attained on the testing cohorts. Results: For classification scheme 4, our pioneering study designs and implements a machine learning-based ECG algorithm to predict 21 possible sites of IVA origin with an accuracy of 98.24% on a testing cohort. The accuracy and F1-score for the left three schemes surpassed 99%. Conclusion: In this work, we developed an algorithm that precisely predicts the correct origins of IVA (out of 21 possible sites) and outperforms the accuracy of all prior studies and human experts

Room-temperature ferromagnetism in epitaxial bilayer FeSb/SrTiO3(001) terminated with a Kagome lattice

Two-dimensional (2D) magnets exhibit unique physical properties for potential applications in spintronics. To date, most 2D ferromagnets are obtained by mechanical exfoliation of bulk materials with van der Waals interlayer interactions, and the synthesis of single or few-layer 2D ferromagnets with strong interlayer coupling remains experimentally challenging. Here, we report the epitaxial growth of 2D non-van der Waals ferromagnetic bilayer FeSb on SrTiO3(001) substrates stabilized by strong coupling to the substrate, which exhibits in-plane magnetic anisotropy and a Curie temperature above 300 K. In-situ low-temperature scanning tunneling microscopy/spectroscopy and density-functional theory calculations further reveal that a Fe Kagome layer terminates the bilayer FeSb. Our results open a new avenue for further exploring emergent quantum phenomena from the interplay of ferromagnetism and topology for application in spintronics

Optimal Multi-Stage Arrhythmia Classification Approach

Arrhythmia constitutes a problem with the rate or rhythm of the heartbeat, and an early diagnosis is essential for the timely inception of successful treatment. We have jointly optimized the entire multi-stage arrhythmia classification scheme based on 12-lead surface ECGs that attains the accuracy performance level of professional cardiologists. The new approach is comprised of a three-step noise reduction stage, a novel feature extraction method and an optimal classification model with finely tuned hyperparameters. We carried out an exhaustive study comparing thousands of competing classification algorithms that were trained on our proprietary, large and expertly labeled dataset consisting of 12-lead ECGs from 40,258 patients with four arrhythmia classes: atrial fibrillation, general supraventricular tachycardia, sinus bradycardia and sinus rhythm including sinus irregularity rhythm. Our results show that the optimal approach consisted of Low Band Pass filter, Robust LOESS, Non Local Means smoothing, a proprietary feature extraction method based on percentiles of the empirical distribution of ratios of interval lengths and magnitudes of peaks and valleys, and Extreme Gradient Boosting Tree classifier, achieved an F1-Score of 0.988 on patients without additional cardiac conditions. The same noise reduction and feature extraction methods combined with Gradient Boosting Tree classifier achieved an F1-Score of 0.97 on patients with additional cardiac conditions. Our method achieved the highest classification accuracy (average 10-fold cross-validation F1-Score of 0.992) using an external validation data, MIT-BIH arrhythmia database. The proposed optimal multi-stage arrhythmia classification approach can dramatically benefit automatic ECG data analysis by providing cardiologist level accuracy and robust compatibility with various ECG data sources

Plant diversity is closely related to the density of zokor mounds in three alpine rangelands on the Tibetan Plateau

Background Plateau zokor (Myospalax baileyi) is a subterranean rodent endemic to the Tibetan Plateau. This species has been generally viewed as a pest in China due to the competition for food with livestock and also causing soil erosion. As a result, plateau zokor has been the target of widespread poisoning or trapping campaigns designed to control or eliminate it since 1970s. But there is little research on the effect of plateau zokor on plant diversity in alpine rangelands. Therefore, objectively evaluating the positive effects of the plateau zokors disturbance on their living environment and plant communities is of great significance to understand the function of plateau zokor in alpine ecosystem. Methods Here, we selected three rangelands (alpine meadow, alpine steppe and alpine shrub meadow) in which plateau zokors are typically distributed on the Tibetan Plateau, and five zokor mound density gradients were selected in each rangeland type to study the effects of the mounds on soil moisture and temperature related to plant species diversity. Results The results showed that, with the mound density increasing, the soil temperature decreased significantly in all three rangeland types, and the soil moisture significantly increased in all three rangeland types. In the alpine meadow, both the plant diversity and cumulative species richness increased significantly with increasing mound density. The increase in broad-leaved forbs is the main reason for the increase of plant diversity in the alpine meadow disturbed by zokor mounds. In the alpine steppe, the plant diversity decreased significantly with increasing mound density, while the cumulative species richness initially decreased and then increased. In the alpine shrub meadow, the plant diversity first increased and then decreased with increasing mound density as did the cumulative species richness. In conclusion, plateau zokor mounds dominated the distribution of soil moisture and temperature and significantly affected plant diversity in these three rangelands on Tibetan Plateau; the results further deepen our understanding toward a co-evolved process

The impact of empirical Marshall vein ethanol infusion as a first-choice intraoperative strategy on the long-term outcomes in patients with persistent atrial fibrillation undergoing mitral isthmus ablation

BackgroundMarshall vein ethanol infusion (MVEI) as an additional therapy to conventional catheter ablation (CA) has been proved to be efficacious in patients with persistent atrial fibrillation (PeAF). However, whether empirical MVEI could be the first-line strategy in mitral isthmus (MI) ablation has seldom been investigated. Here, we aim to compare the efficacy, safety, and long-term outcomes between provisional and empirical MVEI in PeAF patients undergoing the index MI ablation procedure.MethodsWe enrolled 133 patients with PeAF either in the provisional group (n = 38, MVEI was performed when conventional endocardial and/or epicardial ablation procedures were inadequate to achieve bidirectional MI block) or in the empirical group (n = 95, MVEI was performed empirically before MI CA).ResultsAll of the baseline characteristics were comparable. Less spontaneous or inducible atrial tachycardias (ATs) were encountered in the empirical group of patients (P < 0.001). More epicardial ablations were applied (26.3% vs. 9.5%, P = 0.016) and a higher incidence of CA-facilitated restoration of sinus rhythm was recorded (86.8% vs. 11.7%, P < 0.001) in the provisional group of patients. Although more fluoroscopy time (6.4[4.2, 9.3] vs. 9.5[5.9, 11.6] min, P = 0.019) and radiation exposure (69.0[25.3, 160.2] vs. 122.0[62.5, 234.1] mGy, P = 0.010) were documented in the empirical group with comparable procedure time, less time (455.9 ± 192.2 vs. 366.5 ± 161.3 s, P = 0.038) was consumed to achieve bidirectional MI block during endocardial ablation in the provisional group. Incidences of procedure-related complications were similar between the two groups. During a 16.5 ± 4.4-month follow-up, the empirical group of patients showed a significantly higher rate of freedom from AT recurrence (95.8% vs. 81.6%, log-rank P = 0.003), while the rate of freedom from AF or atrial tachyarrhythmias (combining AF and AT) was similar. Both univariate (HR 0.19, 95% CI 0.05–0.64, P = 0.008) and multivariate (HR 0.25, 95% CI 0.07–0.92, P = 0.037) Cox regression analyses indicated that empirical MVEI was independently associated with lower long-term AT recurrence.ConclusionAmong patients with PeAF who underwent the index MI ablation procedure, empirical MVEI could reduce endocardial MI ablation time and provide greater long-term freedom from AT recurrence