Objective To improve the myocardial protection result, observe the effects of 11,12 epoxyeicosatrienoic acid (11,12 EET) on reperfusion arrhythmias in the isolated perfused immature rabbit hearts, which underwent long term preservation. Methods Sixteen isolated rabbit hearts were randomly assigned to two groups, 8 rabbits each group. Control group: treated with St.Thomas Ⅱ solution, experimental group: treated with St.Thomas Ⅱ solution plus 11,12 EET. By means of the Langendorff technique, these isolated rabbit hearts were arrested and stored for 16 hours with 4℃ hypothermia, and underwent 30 minutes of reperfusion(37℃). The mean times until the cessation of both electrical and mechanical activity were measured after infusion of cardioplegia. The heart rate (HR), coronary flow (CF), myocardial water content (MWC), value of creatine kinase (CK) and lactic dehydrogenase (LDH), myocardial calcium content and the arrhythmias score (AS) during the period and at the endpoint of the reperfusion were observed. Results The times until electrical and mechanical activity arrest in the experimental group were significantly shorter than those in control group ; HR, CF, MWC, CK, LDH, myocardial calcium content and AS were significantly better than those in control group. Conclusions These data suggest that 11,12 EET added to the cardioplegic solution of St.Thomas Ⅱ has lower incidence rate of reperfusion arrhythmias.
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.
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.
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.
Objective To analyze the risk factors affecting the occurrence of arrhythmia after esophageal cancer surgery, construct a risk prediction model, and explore its clinical value. Methods A retrospective analysis was conducted on the clinical data of patients who underwent radical esophagectomy for esophageal cancer in the Department of Thoracic Surgery at Anhui Provincial Hospital from 2020 to 2023. Univariate and multivariate analyses were used to screen potential factors influencing postoperative arrhythmia. A risk prediction model for postoperative arrhythmia was constructed, and a nomogram was drawn. The predictive performance of the model was then validated. Results A total of 601 esophageal cancer patients were randomly divided into a modeling group (421 patients) and a validation group (180 patients) at a 7 : 3 ratio. In the modeling group, patients were further categorized into an arrhythmia group (188 patients, 44.7%) and a non-arrhythmia group (233 patients, 55.3%) based on whether they developed postoperative arrhythmia. Among those with postoperative arrhythmia, 43 (10.2%) patients had atrial fibrillation (AF), 12 (2.9%) patients had atrial premature beats, 15 (3.6%) patients had sinus bradycardia, and 143 (34%) patients had sinus tachycardia. Some patients exhibited multiple arrhythmias, including 14 patients with AF combined with sinus tachycardia, 7 patients with AF combined with atrial premature beats, and 3 patients with AF combined with sinus bradycardia. Univariate analysis revealed that a history of hypertension, heart disease, pulmonary infection, acute respiratory distress syndrome, postoperative hypoxia, anastomotic leakage, and delirium were risk factors for postoperative arrhythmia in esophageal cancer patients (P<0.05). Multivariate logistic regression analysis showed that a history of heart disease, pulmonary infection, and postoperative hypoxia were independent risk factors for postoperative arrhythmia after esophageal cancer surgery (P<0.05). The area under the receiver operating characteristic curve (AUC) of the constructed risk prediction model for postoperative arrhythmia was 0.710 [95% CI (0.659, 0.760)], with a sensitivity of 0.617 and a specificity of 0.768. Conclusion A history of heart disease, pulmonary infection, and postoperative hypoxia are independent risk factors for postoperative arrhythmia after esophageal cancer surgery. The risk prediction model constructed in this study can effectively identify high-risk patients for postoperative arrhythmia, providing a basis for personalized interventions.
ObjectiveTo investigate the efficacy of bipolar radiofrequency ablation for left ventricular aneurysm-related ventricular arrhythmia associated with mural thrombus. MethodsFifteen patients with left ventricular aneurysm-related frequent premature ventricular contractions associated with mural thrombus were enrolled in Beijing Anzhen Hospital between June 2013 and June 2015. There were 11 male and 4 female patients with their age of 63.5±4.8 years. All patients had a history of myocardial infarction, but no cerebral infarction. All patients received bipolar radiofrequency ablation combined with coronary artery bypass grafting, ventricular aneurysm plasty and thrombectomy. Holter monitoring and echocardiography were measured before discharge and 3 months following the operation. ResultsThere was no death during the operation. Cardiopulmonary bypass time was 92.7±38.3 min. The aortic clamping time was 52.4±17.8 min.The number of bypass grafts was 3.9±0.4. All the patients were discharged 7-10 days postoperatively. None of the patients had low cardiac output syndrome, malignant arrhythmias, perioperative myocardial infarction, or cerebral infarction in this study. Echocardiography conducted before discharge showed that left ventricular end diastolic diameter was decreased (54.87±5.21 cm vs. 60.73±6.24 cm, P=0.013). While there was no significant improvement in ejection fraction (45.20%±3.78% vs. 44.47%±6.12%, P=1.00) compared with those before the surgery. The number of premature ventricular contractions[4 021.00 (2 462.00, 5 496.00)beats vs. 11 097.00 (9 327.00, 13 478.00)beats, P < 0.001] and the percentage of premature ventricular contractions[2.94% (2.12%, 4.87%) vs. 8.11% (7.51%, 10.30%), P < 0.001] in 24 hours revealed by Holter monitoring were all significantly decreased than those before the surgery. At the end of 3-month follow-up, all the patients were angina and dizziness free. Echocardiography documented that there was no statistical difference in left ventricular end diastolic diameter (55.00±4.41 mm vs. 54.87±5.21 mm, P=1.00). But there were significant improvements in ejection fraction (49.93%±4.42% vs. 45.20%±3.78%, P=0.04) in contrast to those before discharge. Holter monitoring revealed that the frequency of premature ventricular contractions[2 043.00 (983.00, 3 297.00)beats vs. 4 021.00 (2 462.00, 5 496.00)beats, P=0.03] were further lessened than those before discharge, and the percentage of premature ventricular contractions[2.62% (1.44%, 3.49%)vs. 8.11% (7.51%, 10.30%), P < 0.001] was significantly decreased than those before the surgery, but no significant difference in contrast to those before discharge. ConclusionThe recoveries of cardiac function benefit from integrated improvements in myocardial ischemia, ventricular geometry, pump function, and myocardial electrophysiology. Bipolar radiofrequency ablation can correct the electrophysiological abnormality, significantly decrease the frequency of premature ventricular contractions, and further improve the heart function.
Objective To evaluate the efficacy and safety of Shen Song Yang Xin Capsule for cardiac arrhythmia. Methods Randomized controlled trials (RCTs) were searched from the following electronic databases: WanFang, CNKI, CBM, VIP, PubMed, and The Cochrane Library. Quality assessment and data extraction were conducted by two reviewers independently. Disagreement was resolved through discussion. All data were analyzed by using RevMan 5.0 software. Results Thirteen studies involving 1896 participants were included. The results of meta-analyses showed that compared with the control group, a) efficacy: Shen Song Yang Xin Capsule was superior to mexiletine (OR=2.96, 95%CI 1.79 to 4.87), and propafenone (OR=2.41, 95%CI 1.60 to 3.62), but was not superior to miodarone (OR=1.25, 95%CI 0.88 to 1.71); b) safety: Shen Song Yang Xin Capsule was superior to propafenone and miodarone in reducing the incidence of cardiac arrhythmia (OR=0.06, 95%CI 0.01 to 0.35; OR=0.05, 95%CI 0.02 to 0.17), but no significant difference was found between the two groups in incidence of gastrointestinal adverse reactions. Conclusion Based on the current studies, Shen Song Yang Xin Capsule is not inferior to the commonly-used anti-arrhythmic medicine at present. It has lower incidence of cardiac arrhythmia, and has no significant difference in the incidence of gastrointestinal adverse reactions compared with western drugs. For the quality restrictions of the included studies, more double blind RCTs with high quality are required to further assess the effects.
Existing arrhythmia classification methods usually use manual selection of electrocardiogram (ECG) signal features, so that the feature selection is subjective, and the feature extraction is complex, leaving the classification accuracy usually affected. Based on this situation, a new method of arrhythmia automatic classification based on discriminative deep belief networks (DDBNs) is proposed. The morphological features of heart beat signals are automatically extracted from the constructed generative restricted Boltzmann machine (GRBM), then the discriminative restricted Boltzmann machine (DRBM) with feature learning and classification ability is introduced, and arrhythmia classification is performed according to the extracted morphological features and RR interval features. In order to further improve the classification performance of DDBNs, DDBNs are converted to deep neural network (DNN) using the Softmax regression layer for supervised classification in this paper, and the network is fine-tuned by backpropagation. Finally, the Massachusetts Institute of Technology and Beth Israel Hospital Arrhythmia Database (MIT-BIH AR) is used for experimental verification. For training sets and test sets with consistent data sources, the overall classification accuracy of the method is up to 99.84% ± 0.04%. For training sets and test sets with inconsistent data sources, a small number of training sets are extended by the active learning (AL) method, and the overall classification accuracy of the method is up to 99.31% ± 0.23%. The experimental results show the effectiveness of the method in arrhythmia automatic feature extraction and classification. It provides a new solution for the automatic extraction of ECG signal features and classification for deep learning.
ObjectiveTo explore and analyze the risk factors for arrhythmia in patients after heart valve replacement.MethodsA retrospective analysis of 213 patients undergoing cardiac valve replacement surgery under cardiopulmonary bypass in our hospital from August 2017 to August 2019 was performed, including 97 males and 116 females, with an average age of 53.4±10.5 year and cardiac function classification (NYHA) grade of Ⅱ-Ⅳ. According to the occurrence of postoperative arrhythmia, the patients were divided into a non-postoperative arrhythmia group and a postoperative arrhythmia group. The clinical data of the two groups were compared, and the influencing factors for arrhythmia after heart valve replacement were analyzed by logistic regression analysis.ResultsThere were 96 (45%) patients with new arrhythmia after heart valve replacement surgery, and the most common type of arrhythmia was atrial fibrillation (45 patients, 18.44%). Preoperative arrhythmia rate, atrial fibrillation operation rate, postoperative minimum blood potassium value, blood magnesium value in the postoperative arrhythmia group were significantly lower than those in the non-postoperative arrhythmia group (P<0.05); hypoxemia incidence, hyperglycemia incidence, acidosis incidence, fever incidence probability were significantly higher than those in the non-postoperative arrhythmia group (P<0.05). The independent risk factors for postoperative arrhythmia were the lowest postoperative serum potassium value (OR=0.305, 95%CI 0.114-0.817), serum magnesium value (OR=0.021, 95%CI 0.002-0.218), and hypoxemia (OR=2.490, 95%CI 1.045-5.930).ConclusionTaking precautions before surgery, improving hypoxemia after surgery, maintaining electrolyte balance and acid-base balance, monitoring blood sugar, detecting arrhythmia as soon as possible and dealing with it in time can shorten the ICU stay time, reduce the occurrence of complications, and improve the prognosis of patients.
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.