A 12-lead Electrocardiogram Database for Arrhythmia Research Covering More Than 10,000 Patients

This newly inaugurated research database for 12-lead electrocardiogram signals was created under the auspices of Chapman University and Shaoxing People’s Hospital (Shaoxing Hospital Zhejiang University School of Medicine) and aims to enable the scientific community in conducting new studies on arrhythmia and other cardiovascular conditions. Certain types of arrhythmias, such as atrial fibrillation, have a pronounced negative impact on public health, quality of life, and medical expenditures. As a non-invasive test, long term ECG monitoring is a major and vital diagnostic tool for detecting these conditions. This practice, however, generates large amounts of data, the analysis of which requires considerable time and effort by human experts. Advancement of modern machine learning and statistical tools can be trained on high quality, large data to achieve exceptional levels of automated diagnostic accuracy. Thus, we collected and disseminated this novel database that contains 12-lead ECGs of 10,646 patients with a 500 Hz sampling rate that features 11 common rhythms and 67 additional cardiovascular conditions, all labeled by professional experts. The dataset consists of 10-second, 12-dimension ECGs and labels for rhythms and other conditions for each subject. The dataset can be used to design, compare, and fine-tune new and classical statistical and machine learning techniques in studies focused on arrhythmia and other cardiovascular conditions

Inappropriate Activation of TLR4/NF-κB is a Cause of Heart Failure

Significance: Heart failure, a disease with extremely high incidence, is closely associated with inflammation and oxidative stress. The Toll-like receptor 4 (TLR4)/nuclear factor kappa-B (NF-κB) pathway plays an important role in the occurrence and development of heart failure. Recent advances: Previous studies have shown that TLR4/NF-κB causes heart failure by inducing oxidative stress and inflammation; damaging the endothelia; promoting fibrosis; and inducing myocardial hypertrophy, apoptosis, pyroptosis, and autophagy. Critical issues: Understanding the pathogenesis of heart failure is essential for the treatment of this disease. In this review, we outline the mechanisms underlying TLR4/NF-κB pathway-mediated heart failure and discuss drugs that alleviate heart failure by regulating the TLR4/NF-κB pathway. Future directions: During TLR4/NF-κB overactivation, interventions targeting specific receptor antagonists may effectively alleviate heart failure, thus providing a basis for the development of new anti-heart failure drugs

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

A case of delayed cardiac perforation of active ventricular lead

A 65-year-old man was admitted as for one month of repetitive dizziness and one episode of syncope. Electrocardiogram showed sinus bradycardia and his Holter monitoring also showed sinus bradycardia with sinus arrest, sino-atrial block and a longest pause of 4.3 s. Then sick sinus syndrome and Adam-Stokes syndrome were diagnosed. Then a dual chamber pacemaker (Medtronic SDR303) was implanted and the parameters were normal by detection. The patient was discharged 1 week later with suture removed. Then 1.5 month late the patient was presented to hospital once again for sudden onset of chest pain with exacerbation after taking deep breath. Pacemaker programming showed both pacing and sensing abnormality with threshold of?5.0V and resistance of 1200?. Lead perforation was revealed by chest X-ray and confirmed by echocardiogram. Considering the fact that there was high risk to remove ventricular lead, spiral tip of previous ventricular lead was withdrew followed by implantation of a new ventricular active lead to the septum. Previous ventricular lead was maintained. As we know that the complications of lead perforation in the clinic was rare. Here we discuss the clinical management and the possible reasons for cardiac perforation of active ventricular lead

Improvements of Nano-TiO₂ on the Long-Term Chloride Resistance of Concrete with Polymer Coatings

The long-term chloride resistance of concrete treated with nano-TiO2-modified polymer coatings was studied. Three types of organic film-forming paints: polyurethane, epoxy resin, and chlorinated rubber were selected, and concrete specimens with nano-TiO2-modified coatings were fabricated. Then, specimens were subjected to periodical ultraviolet-accelerated aging and subsequent Coulomb electric flux experiments. Nanomodified coatings before and after ultraviolet aging were observed through scanning electron microcopy. Results indicate that the nano-TiO2 particles can effectively reduce the microdefects in coating films and alleviate damages due to aging. As a result, nano-TiO2 can significantly reduce the Coulomb fluxes of coated concrete before and after coating aging, and the average reduction amplitudes reached 66% and 44%. That is, nano-TiO2 can remarkably improve the long-term chloride resistance of coated concrete. In addition, we established the development models of the ultraviolet aging and chloride resistance of coated concrete according to an S-shaped curve