Simulation of predicting atrial fibrosis in patients with paroxysmal atrial fibrillation during sinus node recovery time in optical imaging

IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS SLAS Technology Pub Date : 2024-08-29 DOI:10.1016/j.slast.2024.100186
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Abstract

Paroxysmal atrial fibrillation is a common arrhythmia, and its development process and prediction of the degree of atrial fibrosis are of great significance for treatment and management. Optical imaging technology provides a new means for non-invasive observation of atrial electrical activity. The aim of this study is to investigate the predictive effect of sinus node recovery time on the degree of atrial fibrosis in patients with paroxysmal atrial fibrillation, and to provide a basis for the application of optical imaging technology in the study of atrial fibrosis. The study collected clinical and optical imaging data from a group of patients with paroxysmal atrial fibrillation, and used statistical analysis methods to investigate the relationship between sinus node recovery time and the degree of atrial fibrosis. The research results indicate that there is a significant correlation between the recovery time of the sinus node and the degree of atrial fibrosis, that is, there is a positive correlation between the prolonged recovery time of the sinus node and the aggravation of atrial fibrosis. SNRT can serve as an effective indicator for evaluating atrial matrix and can be applied to predict recurrence after catheter ablation of paroxysmal atrial fibrillation. Shortening SNRT through catheter ablation can become an important predictor of effective catheter ablation.

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在光学成像中模拟预测窦房结恢复时间内阵发性心房颤动患者的心房纤维化。
阵发性心房颤动是一种常见的心律失常,其发展过程和心房纤维化程度的预测对治疗和管理具有重要意义。光学成像技术为无创观察心房电活动提供了一种新手段。本研究旨在探讨窦房结恢复时间对阵发性心房颤动患者心房纤维化程度的预测作用,为光学成像技术在心房纤维化研究中的应用提供依据。该研究收集了一组阵发性心房颤动患者的临床和光学成像数据,并采用统计分析方法研究了窦房结恢复时间与心房纤维化程度之间的关系。研究结果表明,窦房结恢复时间与心房纤维化程度之间存在显著相关性,即窦房结恢复时间延长与心房纤维化加重之间存在正相关。SNRT 可作为评估心房基质的有效指标,并可用于预测阵发性心房颤动导管消融术后的复发情况。通过导管消融缩短 SNRT 可以成为有效导管消融的重要预测指标。
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来源期刊
SLAS Technology
SLAS Technology Computer Science-Computer Science Applications
CiteScore
6.30
自引率
7.40%
发文量
47
审稿时长
106 days
期刊介绍: SLAS Technology emphasizes scientific and technical advances that enable and improve life sciences research and development; drug-delivery; diagnostics; biomedical and molecular imaging; and personalized and precision medicine. This includes high-throughput and other laboratory automation technologies; micro/nanotechnologies; analytical, separation and quantitative techniques; synthetic chemistry and biology; informatics (data analysis, statistics, bio, genomic and chemoinformatics); and more.
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