Objective: The study was undertaken to analyze retrospectively the results of radiofrequency catheter ablation (RFCA) on septum originated tachycardia in children with arrhythmia. The 98 children were all treated with RFCA on septum originated tachycardia in which the ablation sites were located near the bundle of His.
Methods: Fifty female and forty-eight male cases were included in this analysis. They were at the age of 8.1 +/- 2.3 years and their body weight was (28 +/- 9) kg. The arrhythmia they suffered from consisted of atrioventricular nodal reentry tachycardia (AVNRT) (n = 62), atrioventricular reentry tachycardia (AVRT) on septum (n = 25), atria Itachycardia on Koch areas (n = 3) and left ventricular tachycardia (ILVT) on the septum (n = 8). Swartz SRO long sheath was used on the right site ablation. Titration of capacity and degreed time of increase were used in the ablation.
Results: Radiofrequency ablation was successful in all cases. Eleven cases had relapse after the procedure. They accepted RFCA again and then the treatment succeeded. One case of AVRT at the posterior septum experienced complete atrioventricular block (AVB) during ablation. Two weeks later this case was implanted with permanent pacemaker.
Conclusions: The septal site is narrow and small in children. Atrioventricular node is tender. If the above facts were neglected, it was very likely to cause AVB, especially in children accepting the procedures of electrophysiologic study an RFCA on the septal site. Attention should be paid to the followings during such procedures: ablation in the sinus rhythm; ablation following the principle, titration of capacity and degreed time of increase; ablation at the right site long sheath; thermo-ablation catheter application and ablation on the two sides of septum in the posterior septum ablation procedure. The end-point of ablation in children should be the elimination of tachycardia and the delta wave, disassociation of VA or passing through bundle of His at pacing in the ventricle, disappearance of jumping conduction or no echo or one echo but without AVNRT after infusion of isoprenaline and stimulation procedure. Avoiding bundle of His injury is important during the procedure of ablation in children.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
TCBGY net for enhanced wear particle detection in ferrography using self attention and multi scale fusion.
Sci Rep
December 2024
Merchant Marine College, Shanghai Maritime University, Shanghai, 201306, China.
The intelligent identification of wear particles in ferrography is a critical bottleneck that hampers the development and widespread adoption of ferrography technology. To address challenges such as false detection, missed detection of small wear particles, difficulty in distinguishing overlapping and similar abrasions, and handling complex image backgrounds, this paper proposes an algorithm called TCBGY-Net for detecting wear particles in ferrography images. The proposed TCBGY-Net uses YOLOv5s as the backbone network, which is enhanced with several advanced modules to improve detection performance.
View Article and Find Full Text PDFNano-second pulsed laser ablation of inconel 718 and MMPCD for simultaneous optimal ablation rate and surface quality.
Sci Rep
December 2024
Department of Mechanical Engineering, School of Science and Engineering, The American University in Cairo, AUC Avenue, 11835, New Cairo, Egypt.
This study investigates the ablation performance of Inconel 718, a nickel-based superalloy, and metal matrix polycrystalline diamond (MMPCD), a super composite, using a nano-second (ns) pulsed laser across a range of ablation conditions. Single trenches varying in energy fluence and scanning speeds were created, analyzing the experimental responses in terms of ablation rate and surface roughness. Using regression techniques, models were developed to understand these relationships.
View Article and Find Full Text PDFAttention-guided convolutional network for bias-mitigated and interpretable oral lesion classification.
Sci Rep
December 2024
Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Canada.
Accurate diagnosis of oral lesions, early indicators of oral cancer, is a complex clinical challenge. Recent advances in deep learning have demonstrated potential in supporting clinical decisions. This paper introduces a deep learning model for classifying oral lesions, focusing on accuracy, interpretability, and reducing dataset bias.
View Article and Find Full Text PDFDeep learning models reveal the link between dynamic brain connectivity patterns and states of consciousness.
Sci Rep
December 2024
BAOBAB Unit, NeuroSpin center, CEA, Université Paris-Saclay, Gif-sur-Yvette, France.
Decoding states of consciousness from brain activity is a central challenge in neuroscience. Dynamic functional connectivity (dFC) allows the study of short-term temporal changes in functional connectivity (FC) between distributed brain areas. By clustering dFC matrices from resting-state fMRI, we previously described "brain patterns" that underlie different functional configurations of the brain at rest.
View Article and Find Full Text PDFSub-millimeter fiberscopic robot with integrated maneuvering, imaging, and biomedical operation abilities.
Nat Commun
December 2024
Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong SAR, China.
Small-scale continuum robots hold promise for interventional diagnosis and treatment, yet existing models struggle to achieve small size, precise steering, and visualized functional treatment simultaneously, termed an "impossible trinity". This study introduces an optical fiber-based continuum robot integrated imaging, high-precision motion, and multifunctional operation abilities at submillimeter-scale. With a slim profile of 0.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!