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数字孪生引导的虚拟胺碘酮试验在房颤消融患者中的临床应用价值

Clinical usefulness of digital twin guided virtual amiodarone test in patients with atrial fibrillation ablation.

作者信息

Hwang Taehyun, Lim Byounghyun, Kwon Oh-Seok, Kim Moon-Hyun, Kim Daehoon, Park Je-Wook, Yu Hee Tae, Kim Tae-Hoon, Uhm Jae-Sun, Joung Boyoung, Lee Moon-Hyoung, Hwang Chun, Pak Hui-Nam

机构信息

Division of Cardiology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.

Division of Cardiology, Department of Internal Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Republic of Korea.

出版信息

NPJ Digit Med. 2024 Oct 23;7(1):297. doi: 10.1038/s41746-024-01298-z.

DOI:10.1038/s41746-024-01298-z
PMID:39443659
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11499921/
Abstract

It would be clinically valuable if the efficacy of antiarrhythmic drugs could be simulated in advance. We developed a digital twin to predict amiodarone efficacy in high-risk atrial fibrillation (AF) patients post-ablation. Virtual left atrium models were created from computed tomography and electroanatomical maps to simulate AF and evaluate its response to varying amiodarone concentrations. As the amiodarone concentration increased in the virtual setting, action potential duration lengthened, peak upstroke velocities decreased, and virtual AF termination became more frequent. Patients were classified into effective (those with virtually terminated AF at therapeutic doses) and ineffective groups. The one-year clinical outcomes after AF ablation showed significantly better results in the effective group compared to the ineffective group, with AF recurrence rates of 20.8% vs. 45.1% (log-rank p = 0.031, adjusted hazard ratio, 0.37 [0.14-0.98]; p = 0.046). This study highlights the potential of a digital twin-guided approach in predicting amiodarone's effectiveness and improving personalized AF management. Clinical Trial Registration Name: The Evaluation for Prognostic Factors After Catheter Ablation of Atrial Fibrillation: Cohort Study, Registration number: NCT02138695. The date of registration: 2014-05. URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02138695.

摘要

如果能够提前模拟抗心律失常药物的疗效,将具有临床价值。我们开发了一种数字孪生模型来预测胺碘酮在高危心房颤动(AF)患者消融术后的疗效。利用计算机断层扫描和电解剖标测创建虚拟左心房模型,以模拟房颤并评估其对不同胺碘酮浓度的反应。在虚拟环境中,随着胺碘酮浓度的增加,动作电位时程延长,最大上升速度峰值降低,虚拟房颤终止变得更加频繁。患者被分为有效组(那些在治疗剂量下虚拟房颤终止的患者)和无效组。房颤消融术后的一年临床结果显示,有效组明显优于无效组,房颤复发率分别为20.8%和45.1%(对数秩检验p = 0.031,调整后风险比,0.37 [0.14 - 0.98];p = 0.046)。本研究强调了数字孪生引导方法在预测胺碘酮有效性和改善个性化房颤管理方面的潜力。临床试验注册名称:心房颤动导管消融术后预后因素评估:队列研究,注册号:NCT02138695。注册日期:2014年5月。网址:https://www.clinicaltrials.gov ;唯一标识符:NCT02138695。

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本文引用的文献

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2
Association of Antiarrhythmic Drug Therapy With Syncope and Pacemaker Implantation in Patients With Atrial Fibrillation.抗心律失常药物治疗与心房颤动患者晕厥和起搏器植入的关联。
J Am Coll Cardiol. 2024 Mar 19;83(11):1027-1038. doi: 10.1016/j.jacc.2024.01.013.
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Up digital and personal: How heart digital twins can transform heart patient care.
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J Clin Med. 2025 Apr 23;14(9):2919. doi: 10.3390/jcm14092919.
数字化与个性化:心脏数字孪生如何改变心脏病人的护理方式。
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Predicting ventricular tachycardia circuits in patients with arrhythmogenic right ventricular cardiomyopathy using genotype-specific heart digital twins.使用基因型特异性心脏数字孪生体预测心律失常性右心室心肌病患者的室性心动过速回路。
Elife. 2023 Oct 18;12:RP88865. doi: 10.7554/eLife.88865.
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