Objective To evaluate the impact of an integrated management mode of prenatal diagnosis-postnatal treatment for congenital heart disease (CHD) on perioperative and long-term outcomes of the arterial switch operation (ASO), and to analyze the efficacy of ASO over six years in a single center. Methods This retrospective study analyzed the clinical data of 183 children who underwent ASO at Guangdong Provincial People's Hospital from January 2018 to December 2024. The cohort included 106 patients (57.9%) of transposition of the great arteries with intact ventricular septum (TGA/IVS), 61 patients (33.3%) of transposition of the great arteries with ventricular septal defect (TGA/VSD), and 16 patients (8.7%) of taussig-bing anomaly (TBA). Perioperative indicators were compared between 91 patients in the prenatal-postnatal integrated management group (an integrated group) and 92 patients in the traditional management group (a non-integrated group). Long-term survival and reoperation rates were analyzed using Kaplan-Meier curves. Results The overall perioperative mortality rate was 4.9% (9/183), showing a downward trend year by year. The primary cause of perioperative mortality was low cardiac output syndrome (LCOS), which occurred in 12 patients (6.6% incidence) with a mortality rate of 75%. The integrated group had a higher proportion of males (89% vs. 72.8%, P<0.05) and lower body weight [3.13 (2.75, 3.35) vs. 3.30 (3.00, 3.67), P<0.05] compared to the non-integrated group. The age at surgery was significantly earlier in the integrated group [7 (3, 10) vs. 14 (9, 48), P<0.05], and all children in the Integrated Group underwent ASO within the optimal surgical window (100% vs. 82.6%, P<0.05). Intraoperatively, cardiopulmonary bypass (CPB) time [173 (150, 207) vs. 186 (159, 237), P<0.05] and aortic cross-clamp (ACC) time [100 (90, 117) vs. 116 (97, 142), P<0.05] were significantly shorter in the integrated group. although the integrated group had longer postoperative mechanical ventilation time [145 (98, 214) vs. 116 (77, 147), P<0.05] and higher 48-hour maximum vasoactive inotropic score (VISmax) [15 (10, 21) vs. 12 (8, 16), P<0.05], there was no statistically significant difference in the incidence of severe complications (LCOS, NEC, ECMO) or mortality rate (3.3% vs. 6.5%, P=0.51) between the two groups, despite earlier surgical intervention and a higher proportion of critically ill cases in the integrated group. The length of hospital stay in the emergency surgery group was significantly shorter than that in the elective surgery group [20 (15, 28) vs. 25 (21, 30), P<0.05], suggesting that early surgery may be of potential benefit. A total of 163 patients were successfully followed up for a median of 4.7 years, with a 5-year survival rate of 95.1% and a freedom from reintervention survival rate of 95.1%. There were no late deaths, and the most common postoperative complication was pulmonary artery stenosis. Conclusion The integrated management model allowed critically ill children with lower body weights to safely undergo surgery, significantly optimizing the timing of surgery and shortening intraoperative times. The long-term risk of reoperation after ASO is primarily concentrated on pulmonary artery stenosis, necessitating long-term follow-up and monitoring.
ObjectiveTo explore the anesthesia management experience in the interventional treatment of pediatric congenital heart diseases (CHD) percutaneously guided by transthoracic echocardiography (TTE) on a mobile operating platform. Methods From March to July 2023, a total of 13 patients from remote areas underwent interventional treatment for CHD on the mobile operating platform of Fuwai Yunnan Cardiovascular Hospital. Patients who received non-tracheal intubation general anesthesia were retrospectively included. ResultsEight children who had difficulty cooperating with the surgery (due to young age, emotional tension, crying) received monitored anesthesia care with local anesthesia supplemented by sedative and analgesic drugs while maintaining spontaneous breathing under the monitoring and management of an anesthesiologist (i.e., non-tracheal intubation general anesthesia). Among them, there were 5 males and 3 females, with an age of (6.95±3.29) years and a body weight of (19.50±6.04) kg. Through transthoracic echocardiography, they were diagnosed with atrial septal defect (6 patients), residual shunt after patent ductus arteriosus ligation (1 patient), and severe pulmonary valve stenosis (1 patient). The surgery proceeded smoothly, with satisfactory anesthesia and surgical effects, complete analgesia, and satisfactory postoperative recovery. There was 1 patient of body movement and 1 patient of respiratory depression during the operation, and both patients completed the surgery successfully after treatment. All children had no serious surgery- and anesthesia-related complications. The anesthesia time was 40.5 (34.5, 47.5) min, the surgery time was 39.0 (33.0, 45.5) min, and the recovery time was 43.0 (28.0, 52.5) min Conclusion Interventional surgery for CHD guided by TTE at a mobile platform is a minimally invasive approach without radiation damage. Non-tracheal intubation general anesthesia with spontaneous breathing can be safely and effectively implemented in children who cannot cooperate.
Cardiac auscultation is the basic way for primary diagnosis and screening of congenital heart disease(CHD). A new classification algorithm of CHD based on convolution neural network was proposed for analysis and classification of CHD heart sounds in this work. The algorithm was based on the clinically collected diagnosed CHD heart sound signal. Firstly the heart sound signal preprocessing algorithm was used to extract and organize the Mel Cepstral Coefficient (MFSC) of the heart sound signal in the one-dimensional time domain and turn it into a two-dimensional feature sample. Secondly, 1 000 feature samples were used to train and optimize the convolutional neural network, and the training results with the accuracy of 0.896 and the loss value of 0.25 were obtained by using the Adam optimizer. Finally, 200 samples were tested with convolution neural network, and the results showed that the accuracy was up to 0.895, the sensitivity was 0.910, and the specificity was 0.880. Compared with other algorithms, the proposed algorithm has improved accuracy and specificity. It proves that the proposed method effectively improves the robustness and accuracy of heart sound classification and is expected to be applied to machine-assisted auscultation.