Objective To study the radiofrequency ablation (RA) and vagal denervafion (VD) in surgical treatment of long-standing atrial fibrillation (AF) associated with rheumatic heart disease (RHD).Methods Retrospective analysis the cardiac rhythm by 24-hour Holter monitoring during 5-year follow-up after total Maze procedure accompanied rheumatic mitral valve replacement.Between June 2006 and December 2007,a total of 173 consecutive patients with long-standing AF-associated RHD underwent mitral valve replacement and ablation maze procedure,92 cases had RA alone and 81 had RA + VD.Results Although Kaplan-Meier curve shows that the freedom from AF at 5 years follow-up time were similar(P =0.718),the percentage of antiarrhythmic drug therapy was significant higher in the RA group during early postoperative period(4th month,54.1％ vs.34.7％,P=0.017;5th month,39.2％ vs.21.3％,P=0.018;6th month,23.0％ vs.10.7％,P =0.044),and the percentage of those free by AF was significant lower(6th month,82.2％ vs.93.8％,P =0.023;1st year,76.1％ vs.89.9％,P=0.019).Conclusion Total maze procedure with bipolar radiofrequency ablation is effective to treat longstanding AF associated with rheumatic valve disease.Vagal denervation helped to maintain stable sinus rhythm and lower antiarrhythmic drug therapy at the early stage,but there was no additional benefit after the 1 st year of follow-up,it may be caused from the reactivation of vagal plexus electrical activity.

BACKGROUND:For patients with degenerative mitral annulus dilatation complicated by atrial fibrilation, atrial fibrilation is needed to be treated concomitant with artificial valve ring implantation. Although Cox maze III procedure is the gold standard for treatment of atrial fibrilation, its safety has been questioned. OBJECTIVE:To evaluate the safety of artificial valve rings implantation and Cox Maze III procedure for treatment of degenerative mitral annulus dilatation complicated by atrial fibrilation. METHODS: A total of 43 patients with degenerative mitral annulus dilatation and atrial fibrilation were enroled and were randomly divided into test group (n=21) and control group (n=22). Patients in the test group were treated with mitral valvuloplasty and Cox Maze III procedure. Patients in the control group were only treated with mitral valvuloplasty. RESULTS AND CONCLUSION: (1) Intraoperative safety indexes: the durations of cardiopulmonary bypass and aortic clamping. and the incidence of hemoglobinuria in the test group were higher than those in the control group (P < 0.001). There was no significant difference in the urine output between these two groups. (2) Postoperative safety indexes: the incidence of atrial dysrhythmia (i.e., any atrial dysrhythmia other than atrial fibrilation), proportion of patients requiring a temporary pacemaker and hospital stays in the test group were higher than those in the control group (P < 0.05). There were no significant differences in the secondary-thoracotomy bleeding rate and incidence of stroke between these two groups. (3) Postoperative outcomes: the rates of cardioversion to achieve sinus rhythm at the day of surgery and at discharge in the test group were significantly higher than those in the control group (P < 0.001). At discharge, patients in both groups were al at NYHA functional class Ior II. Echocardiography showed trace to mild mitral regurgitation and complete closure of the tricuspid valve. There were no significant differences in the left atrial diameter, left ventricular diameter, left ventricular volume, and ejection fraction between these two groups. However, the proportions of mitral and tricuspid valve peak A-waves were significantly higher than those in the control group (P < 0.001). These results show that artificial valve ring implantation and Cox Maze III procedure is a safe and effective method for treating degenerative mitral annulus dilatation complicated by atrial fibrilation during operation.

Objective To introduce the modeling method of pendulum-like modified rat abdominal heart heterotopic transplantation model and evaluate the quality of the model. Methods An operator without transplantation experience performed 15 consecutive models, recorded the time of each step, changes in body weight and modified Stanford scores, and calculated the surgical success rate, postoperative 1-week survival rate and technical success rate. Ultrasound examinations was performed in 1 week postoperatively. Results The times for donor heart acquisition, donor heart processing, recipient preparation and transplantation anastomosis were (14.3±1.4) min, (3.5±0.6) min, (13.6±2.1) min and (38.3±5.2) min respectively. The surgical success rate was 87% (13/15), and the survival rate 1 week after operative was 100% (13/13). The improved Stanford score indicated a technical success rate of 92% (12/13), and the postoperative 1-week ultrasound examination showed that grafts with Stanford scores ≥3 had detectable pulsation and blood flow signals. Conclusions The pendulum-like modified rat abdominal heart heterotopic transplantation improved model further optimizes the operational steps with a high success rate and stable quality, may be chosen as a modeling option for basic research in heart transplantation in the future.

Lung transplantation is currently the only recognized effective treatment for end-stage lung disease and has improved the quality of life for patients. However, lung transplantation still faces many challenges, including rejection, infection, post-transplant acute kidney injury, post-transplant diabetes mellitus, ischemia-reperfusion injury and donor shortage, etc. Chinese lung transplantation scholars made a series of important progress in the field of clinical research in 2024, focusing on the study and solution of the above problems, and providing new ideas for lung transplantation surgery. This article systematically reviews the clinical research and technological innovation in the field of lung transplantation in 2024, summarizes the achievements of clinical research in the field of lung transplantation in China in 2024, and aims to providing new directions and strategies for future research.

Lung transplantation is the optimal treatment for end-stage lung diseases and can significantly improve prognosis of the patients. However, postoperative complications such as infection, rejection, ischemia-reperfusion injury, and other challenges (like shortage of donor lungs) , limit the practical application of lung transplantation in clinical practice. Chinese research teams have been making continuous efforts and have achieved breakthroughs in basic research on lung transplantation by integrating emerging technologies and cutting-edge achievements from interdisciplinary fields, which has strongly propelled the development of this field. This article will comprehensively review the academic progress made by Chinese research teams in the field of lung transplantation in 2024, with a focus on the achievements of Chinese teams in basic research on lung transplantation. It aims to provide innovative ideas and strategies for key issues in the basic field of lung transplantation and to help China's lung transplantation cause reach a higher level.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.