Arrhythmia is a kind of common cardiac electrical activity abnormalities. Heartbeats classification based on electrocardiogram (ECG) is of great significance for clinical diagnosis of arrhythmia. This paper proposes a feature extraction method based on manifold learning, neighborhood preserving embedding (NPE) algorithm, to achieve the automatic classification of arrhythmia heartbeats. With classification system, we obtained low dimensional manifold structure features of high dimensional ECG signals by NPE algorithm, then we inputted the feature vectors into support vector machine (SVM) classifier for heartbeats diagnosis. Based on MIT-BIH arrhythmia database, we clustered 14 classes of arrhythmia heartbeats in the experiment, which yielded a high overall classification accuracy of 98.51%. Experimental result showed that the proposed method was an effective classification method for arrhythmia heartbeats.
Objective To evaluate the feasibility of imaging the rat cardiac conduction system (CCS) using transaortic antegrade perfusion of Alexa Fluor 633-labeled antibodies targeting hyperpolarization-activated cyclic nucleotide-gated cation channel 4 (HCN4) and connexin (Cx). The study also sought to optimize antibody dosage, perfusion duration, and assess the photostability of the dye. Methods Ex vivo rat heart model with transaortic antegrade perfusion was established using 33 male SPF-grade Sprague-Dawley (SD) rats. Primary and secondary antibody solutions were sequentially perfused in an antegrade manner. After perfusion for predetermined durations, the atrioventricular junction was observed, and the fluorescence intensity of the corresponding area was recorded. Five dose-gradient groups (n=3 rats/group), five perfusion time-gradient groups (n=3 rats/group), and ten continuous LED light exposure time-gradient groups (using 3 rats prepared with a fixed dose and time) were established to observe and record regional fluorescence intensity. Standard immunofluorescence staining was performed on both paraffin and frozen sections for comparative histological analysis. Results A region of aggregated red fluorescent signal was observed in the atrioventricular junction. Following semi-quantitative fluorescence intensity analysis of HCN4/Cx43 and validation through comparative histology, this structure was identified as the atrioventricular node (AVN) region. The AVN-to-background fluorescence intensity ratio showed no statistically significant differences among groups with increasing antibody dosage (P>0.05). The ratio increased with longer antibody perfusion times. Furthermore, no statistically significant differences in the ratio were observed among groups with extended light exposure (P>0.05). Conclusion Transaortic antegrade perfusion of fluorescently labeled antibodies can successfully image the AVN within the CCS of ex vivo rat hearts. Increasing the antibody dosage does not significantly improve the AVN imaging effect. Longer antibody perfusion time results in better imaging quality of the AVN. The fluorescent dye maintains sufficient visualization of the AVN even after prolonged (8 h) exposure to light.
Arrhythmia is a significant cardiovascular disease that poses a threat to human health, and its primary diagnosis relies on electrocardiogram (ECG). Implementing computer technology to achieve automatic classification of arrhythmia can effectively avoid human error, improve diagnostic efficiency, and reduce costs. However, most automatic arrhythmia classification algorithms focus on one-dimensional temporal signals, which lack robustness. Therefore, this study proposed an arrhythmia image classification method based on Gramian angular summation field (GASF) and an improved Inception-ResNet-v2 network. Firstly, the data was preprocessed using variational mode decomposition, and data augmentation was performed using a deep convolutional generative adversarial network. Then, GASF was used to transform one-dimensional ECG signals into two-dimensional images, and an improved Inception-ResNet-v2 network was utilized to implement the five arrhythmia classifications recommended by the AAMI (N, V, S, F, and Q). The experimental results on the MIT-BIH Arrhythmia Database showed that the proposed method achieved an overall classification accuracy of 99.52% and 95.48% under the intra-patient and inter-patient paradigms, respectively. The arrhythmia classification performance of the improved Inception-ResNet-v2 network in this study outperforms other methods, providing a new approach for deep learning-based automatic arrhythmia classification.
Sepsis-associated organ dysfunction arises from uncontrolled inflammation and immune dysregulation, causing microcirculatory impairment and multi-organ failure. Stellate ganglion block (SGB) may confer organ protection by regulating the sympathetic nervous system and hypothalamic-pituitary-adrenal axis to suppress excessive inflammation and oxidative stress. Available evidence, mainly from experimental and small clinical studies, suggests potential benefits of SGB in sepsis-induced acute lung injury, ventricular arrhythmias, and limb ischemia, which require confirmation in multicenter randomized controlled trials. This review outlines the mechanisms and clinical advances of SGB in sepsis-related organ dysfunction, providing a theoretical basis for its application in critical care.
Electrocardiogram (ECG) signal is an important basis for the diagnosis of arrhythmia and myocardial infarction. In order to further improve the classification effect of arrhythmia and myocardial infarction, an ECG classification algorithm based on Convolutional vision Transformer (CvT) and multimodal image fusion was proposed. Through Gramian summation angular field (GASF), Gramian difference angular field (GADF) and recurrence plot (RP), the one-dimensional ECG signal was converted into three different modes of two-dimensional images, and fused into a multimodal fusion image containing more features. The CvT-13 model could take into account local and global information when processing the fused image, thus effectively improving the classification performance. On the MIT-BIH arrhythmia dataset and the PTB myocardial infarction dataset, the algorithm achieved a combined accuracy of 99.9% for the classification of five arrhythmias and 99.8% for the classification of myocardial infarction. The experiments show that the high-precision computer-assisted intelligent classification method is superior and can effectively improve the diagnostic efficiency of arrhythmia as well as myocardial infarction and other cardiac diseases.
Objective
To evaluate the efficacy and clinical significance of bipolar radiofrequency ablation in the treatment of left ventricular aneurysm with ventricular arrhythmias guided by CARTO mapping system.
Methods
From September 2009 to December 2015, 56 patients with ventricular aneurysm following myocardial infarction were enrolled. All patients suffered different levels of angina pectoris symptoms evaluated by Holter (the frequencies of ventricular arrhythmias more than 3 000 per day). They were divided into two groups according to random ballot and preoperative communication with patients' family members: a bipolar radiofrequency ablation group (n=28, 20 males, 8 females, mean age of 61.21±1.28 years) receiving off-pump coronary artery bypass grafting (OPCABG), ventricular aneurysm surgery combined with bipolar radiofrequency ablation, and a non-bipolar radiofrequency ablation group (n=28, 22 males, 6 females, mean age of 57.46±1.30 years) receiving OPCABG and single ventricular aneurysm surgery. The grade of cardiac function and ventricular arrhythmia was compared between the two groups during pre-operation, discharge and follow-up.
Results
All patients were discharged successfully. There was no in-hospital death in both two groups. One patient in the non-radiofrequency group had cerebral infarction. All patients were re-checked with Holter before discharge and the frequency of ventricular arrhythmias significantly decreased compared to that of pre-operation in both groups, and was more significant in bipolar radiofrequency ablation group (1 197.00±248.20 times/24 h vs. 1 961.00±232.90 times/24 h, P<0.05). There was significant difference in duration of mechanical ventilation and ICU stay between the two groups (P<0.05). The left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDD) and left ventricular end-systolic diameter (LVESD) significantly improved (P<0.05) after operation in both groups.
Conclusion
The clinical efficacy of bipolar radiofrequency ablation in the treatment of ventricular aneurysm with ventricular arrhythmia guided by CARTO mapping is safe and effective, but its long-term outcomes still need further follow-up.
The cardiac conduction system (CCS) is a set of specialized myocardial pathways that spontaneously generate and conduct impulses transmitting throughout the heart, and causing the coordinated contractions of all parts of the heart. A comprehensive understanding of the anatomical characteristics of the CCS in the heart is the basis of studying cardiac electrophysiology and treating conduction-related diseases. It is also the key of avoiding damage to the CCS during open heart surgery. How to identify and locate the CCS has always been a hot topic in researches. Here, we review the histological imaging methods of the CCS and the specific molecular markers, as well as the exploration for localization and visualization of the CCS. We especially put emphasis on the clinical application prospects and the future development directions of non-destructive imaging technology and real-time localization methods of the CCS that have emerged in recent years.
Lorenz plot (LP) method which gives a global view of long-time electrocardiogram signals, is an efficient simple visualization tool to analyze cardiac arrhythmias, and the morphologies and positions of the extracted attractors may reveal the underlying mechanisms of the onset and termination of arrhythmias. But automatic diagnosis is still impossible because it is lack of the method of extracting attractors by now. We presented here a methodology of attractor extraction and recognition based upon homogeneously statistical properties of the location parameters of scatter points in three dimensional LP (3DLP), which was constructed by three successive RR intervals as X, Y and Z axis in Cartesian coordinate system. Validation experiments were tested in a group of RR-interval time series and tags data with frequent unifocal premature complexes exported from a 24-hour Holter system. The results showed that this method had excellent effective not only on extraction of attractors, but also on automatic recognition of attractors by the location parameters such as the azimuth of the points peak frequency (APF) of eccentric attractors once stereographic projection of 3DLP along the space diagonal. Besides, APF was still a powerful index of differential diagnosis of atrial and ventricular extrasystole. Additional experiments proved that this method was also available on several other arrhythmias. Moreover, there were extremely relevant relationships between 3DLP and two dimensional LPs which indicate any conventional achievement of LPs could be implanted into 3DLP. It would have a broad application prospect to integrate this method into conventional long-time electrocardiogram monitoring and analysis system.
As an important medical electronic equipment for the cardioversion of malignant arrhythmia such as ventricular fibrillation and ventricular tachycardia, cardiac external defibrillators have been widely used in the clinics. However, the resuscitation success rate for these patients is still unsatisfied. In this paper, the recent advances of cardiac external defibrillation technologies is reviewed. The potential mechanism of defibrillation, the development of novel defibrillation waveform, the factors that may affect defibrillation outcome, the interaction between defibrillation waveform and ventricular fibrillation waveform, and the individualized patient-specific external defibrillation protocol are analyzed and summarized. We hope that this review can provide helpful reference for the optimization of external defibrillator design and the individualization of clinical application.
ObjectiveTo optimize the therapy protocols of high dose prednisone combined with topiramate (TPM) in children with infantile spasms (IS).
MethodsSixty cases were collected in our hospital from September 2012 to September 2013 and randomly divided into two groups(n=30) and followed-up for more than 6 months.The spasms were assesses by video-electroencephalogram (VEEG) monitoring including awake and asleep states before treatment, after two weeks of therapy and the end of the courses respectively.And the Gessel developmental quotient (DQ) scores were performed before treatment and after six months of therapy.
ResultsFor the unresponders to high dose prednisone in one week of therapy, there were 46.67%and 60.00% in test group higher than 31.25% and 37.50% in control group respectively in 2 week and in the end of treatment.And the rate of complete resolution of hypsarrhythmia in the test group was 46.67% and 60.00% higher than 25.00% and 37.50% in control group respectively in 2 week and in the end of treatment.But there were no statistical significances between two groups(P >0.05).The incidence of side effects(83.33% vs. 80.00%) and the relapse rate(39.14% vs. 40.00%), were not statistically significant between two groups(P >0.05).The responsive rates for the cases with the lead time within 2 months higher than beyond 2 months in two groups respectively in 2 weeks and in the end of treatment.
ConclusionsThe protocol of the test group was superior to that of the control group.The responsive rates of children within 2 months of lead time were higher than beyond 2 months, which indicates that early diagnosis and early treatment would improve efficacy and have an important influence on the prognosis of IS.
