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 whether single cycle ischemic preconditioning （IP） improves the myocardial preservation in patients undergoing cardiac valve replacement. Methods From August 2002 to April 2006, 85 patients who had chronic heart valve disease and required cardiac valve replacement were randomly divided into two groups. IP group, 47 allocated to receive IP and arrested with 4 C St. Thomas＇ Hospital cardioplegic solution during cardiopulmonary bypass（CPB）, preconditioning was accomplished by using single cycle of 2 minutes occlusion of aorta followed by 3 minutes of reperfusion before cross-clamping. Control group, 38 allocated to receive 4 C St. Thomas＇ Hospital cardioplegic solution alone. Myocardial protective effects were assessed by determinations of creatinine kinase-MB isoenzyme （CK-MB） and cardiac troponin I（cTnI）, ST-T changes, ventricular arrhythmias and other clinical data in ICU. Results Serum CK-MB and cTnI concentrations were increased postoperatively in two groups. At 24, 48 and 72h after operation, values of CK-MB in IP group was significantly lower than that in control group （P〈0.05）, cTnI at 24 and 48h after operation also less in IP group （P〈0.05）. The duration for patients needed for antiarrhythmic drugs in IP group was lower than that in control group （P〈0.05）. Compared with control group, fewer inotropic drugs were used in IP group. As a result, ICU stay time in IP group was shorter than that in control group （P〈0.05）. Conclusion IP enhances the myocardial protective effect when it was used with hypothermic hyper kalemic cardioplegic solution in patients undergoing cardiac valve replacement, IP significantly reduces the postoperative increase of CK-MB, cTnI and plessens the severity of postoperative ventricular arrhythmias.
Atrial tachyarrhythmias is a known complication after cardiac surgery and represents a major cause of morbidity, increased length of hospital stay, and economic costs. Atrial fibrillation is the most common heart rhythm disorder. And it is often associated with other atrial tachyarrhythmias, such as atrial flutter (AFlu), premature atrial complexes, and multifocal atrial tachycardia. Postoperative atrial fibrillation is often self-limiting, but it may require anticoagulation therapy and either a rate or rhythm control strategy. We provide a complete and updated review about mechanisms, risk factors, and treatment strategies for the main atrial tachyarrhythmias (atrial fibrillation).
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.
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.
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.
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.