ABSTRACT
BACKGROUND: Brugada syndrome (BrS) has been associated with sudden cardiac death in otherwise healthy subjects, and drug-induced BrS accounts for 55% to 70% of all patients with BrS. This study aims to develop a deep convolutional neural network and evaluate its performance in recognizing and predicting BrS diagnosis. METHODS AND RESULTS: Consecutive patients who underwent ajmaline testing for BrS following a standardized protocol were included. ECG tracings from baseline and during ajmaline were transformed using wavelet analysis and a deep convolutional neural network was separately trained to (1) recognize and (2) predict BrS type I pattern. The resultant networks are referred to as BrS-Net. A total of 1188 patients were included, of which 361 (30.3%) patients developed BrS type I pattern during ajmaline infusion. When trained and evaluated on ECG tracings during ajmaline, BrS-Net recognized a BrS type I pattern with an AUC-ROC of 0.945 (0.921-0.969) and an AUC-PR of 0.892 (0.815-0.939). When trained and evaluated on ECG tracings at baseline, BrS-Net predicted a BrS type I pattern during ajmaline with an AUC-ROC of 0.805 (0.845-0.736) and an AUC-PR of 0.605 (0.460-0.664). CONCLUSIONS: BrS-Net, a deep convolutional neural network, can identify BrS type I pattern with high performance. BrS-Net can predict from baseline ECG the development of a BrS type I pattern after ajmaline with good performance in an unselected population.
Subject(s)
Ajmaline , Brugada Syndrome , Deep Learning , Electrocardiography , Humans , Brugada Syndrome/diagnosis , Brugada Syndrome/physiopathology , Brugada Syndrome/chemically induced , Electrocardiography/drug effects , Male , Female , Ajmaline/adverse effects , Middle Aged , Adult , Predictive Value of Tests , Retrospective StudiesABSTRACT
We studied the effects of extremely low-frequency (50 Hz) electromagnetic fields (EMFs) on peripheral human blood lymphocytes and DBY747 Saccharomyces cerevisiae. Graded exposure to 50 Hz magnetic flux density was obtained with a Helmholtz coil system set at 1, 10 or 100 microT for 18 h. The effects of EMFs on DNA damage were studied with the single-cell gel electrophoresis assay (comet assay) in lymphocytes. Gene expression profiles of EMF-exposed human and yeast cells were evaluated with DNA microarrays containing 13,971 and 6,212 oligonucleotides, respectively. After exposure to the EMF, we did not observe an increase in the amount of strand breaks or oxidated DNA bases relative to controls or a variation in gene expression profiles. The results suggest that extremely low-frequency EMFs do not induce DNA damage or affect gene expression in these two different eukaryotic cell systems.
