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.
Objective To investigate the risky factors of ventricular arrhythmias following open heart surgery in patients with giant left ventricle, and offer the basis in order to prevent it’s occurrence. Methods The clinical materials of 176 patients who had undergone the open heart surgery were analyzed retrospectively. There were 44 patients who had ventricular arrhythmia (ventricular arrhythmia group), 132 patients who had no ventricular arrhythmia as contrast (control group). The preoperative clinical data, indexes of types of cardiopathy, ultrasonic cardiogram, electrocardiogram and cardiopulmonary bypass (CPB) etc. were choosed, and tested by using χ2 test,t test and logistic regression to analyse the high endangered factors for incidence of ventricular arrhythmia after open heart surgery. Results Age≥55 years (OR=3.469), left ventricular enddiastolic diameter(LVEDD)≥80 mm (OR=3.927), left ventricular ejection fraction（LVEF）≤55% (OR=2.967), CPB time≥120min(OR=5.170) and aortic clamping time≥80min(OR=4.501) were the independent risk factors of ventricular arrhythmia. Conclusion Ventricular arrhythmia is a severe complication for the patients with giant left ventricle after open heart surgery, and influence the prognosis of the patients. Patient’s age, size of the left ventricle, cardiac function, CPB time and clamping time could influence the incidence of ventricular arrhythmias.
Objective To investigate the risk factors for arrhythmia after robotic cardiac surgery. Methods The data of the patients who underwent robotic cardiac surgery under cardiopulmonary bypass (CPB) from July 2016 to June 2022 in Daping Hospital of Army Medical University were retrospectively analyzed. According to whether arrhythmia occurred after operation, the patients were divided into an arrhythmia group and a non-arrhythmia group. Univariate analysis and multivariate logistic analysis were used to screen the risk factors for arrhythmia after robotic cardiac surgery. ResultsA total of 146 patients were enrolled, including 55 males and 91 females, with an average age of 43.03±13.11 years. There were 23 patients in the arrhythmia group and 123 patients in the non-arrhythmia group. One (0.49%) patient died in the hospital. Univariate analysis suggested that age, body weight, body mass index (BMI), diabetes, New York Heart Association (NYHA) classification, left atrial anteroposterior diameter, left ventricular anteroposterior diameter, right ventricular anteroposterior diameter, total bilirubin, direct bilirubin, uric acid, red blood cell width, operation time, CPB time, aortic cross-clamping time, and operation type were associated with postoperative arrhythmia (P<0.05). Multivariate binary logistic regression analysis suggested that direct bilirubin (OR=1.334, 95%CI 1.003-1.774, P=0.048) and aortic cross-clamping time (OR=1.018, 95%CI 1.005-1.031, P=0.008) were independent risk factors for arrhythmia after robotic cardiac surgery. In the arrhythmia group, postoperative tracheal intubation time (P<0.001), intensive care unit stay (P<0.001) and postoperative hospital stay (P<0.001) were significantly prolonged, and postoperative high-dose blood transfusion events were significantly increased (P=0.002). Conclusion Preoperative direct bilirubin level and aortic cross-clamping time are independent risk factors for arrhythmia after robotic cardiac surgery. Postoperative tracheal intubation time, intensive care unit stay, and postoperative hospital stay are significantly prolonged in patients with postoperative arrhythmia, and postoperative high-dose blood transfusion events are significantly increased.
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 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.
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.
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.
The automatic detection of arrhythmia is of great significance for the early prevention and diagnosis of cardiovascular diseases. Traditional arrhythmia diagnosis is limited by expert knowledge and complex algorithms, and lacks multi-dimensional feature representation capabilities, which is not suitable for wearable electrocardiogram (ECG) monitoring equipment. This study proposed a feature extraction method based on autoregressive moving average (ARMA) model fitting. Different types of heartbeats were used as model inputs, and the characteristic of fast and smooth signal was used to select the appropriate order for the arrhythmia signal to perform coefficient fitting, and complete the ECG feature extraction. The feature vectors were input to the support vector machine (SVM) classifier and K-nearest neighbor classifier (KNN) for automatic ECG classification. MIT-BIH arrhythmia database and MIT-BIH atrial fibrillation database were used to verify in the experiment. The experimental results showed that the feature engineering composed of the fitting coefficients of the ARMA model combined with the SVM classifier obtained a recall rate of 98.2% and a precision rate of 98.4%, and the F1 index was 98.3%. The algorithm has high performance, meets the needs of clinical diagnosis, and has low algorithm complexity. It can use low-power embedded processors for real-time calculations, and it’s suitable for real-time warning of wearable ECG monitoring equipment.
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.
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.