Automatic Echocardiographic Assessment of Left Atrial Function for Prediction of Low-Voltage Areas in Non-Valvular Atrial Fibrillation.

IF 2.1 4区医学 Q2 MEDICINE, GENERAL & INTERNAL

International Journal of General Medicine Pub Date : 2024-10-02 eCollection Date: 2024-01-01 DOI:10.2147/IJGM.S477499

Shuai Chang, Xiaofeng Zhang, Chenliang Ge, Yanfen Zhong, Decai Zeng, Yongzhi Cai, Tongtong Huang, Ji Wu

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引用次数: 0

Abstract

Purpose: Left atrial low-voltage areas (LA-LVAs) identified by 3D-electroanatomical mapping are crucial for determining treatment strategies and prognosis in patients with atrial fibrillation (AF). However, convenient and accurate prediction of LA-LVAs remains challenging. This study aimed to assess the viability of utilizing automatically obtained echocardiographic parameters to predict the presence of LA-LVAs in patients with non-valvular atrial fibrillation (NVAF).

Patients and methods: This retrospective study included 190 NVAF patients who underwent initial catheter ablation. Before ablation, echocardiographic data were obtained, left atrial volume and strain were automatically calculated using advanced software (Dynamic-HeartModel and AutoStrain). Electroanatomic mapping (EAM) was also performed. Results were compared between patients with LA-LVAs ≥5% (LVAs group) and <5% (non-LVAs group).

Results: LA-LVAs were observed in 81 patients (42.6%), with a significantly higher incidence in those with persistent AF than paroxysmal AF (55.6% vs 19.3%, P <0.001). Compared with the non-LVAs group, the LVAs group included significantly older patients, lower left ventricular ejection fraction, higher heart rate, and higher E/e' ratio (P <0.05). The LVAs group exhibited higher left atrial volume_max index (LAVi_max) and lower left atrial reservoir strain (LASr) (P <0.001). In multivariate analysis, both LAVi_max and LASr emerged as independent indicators of LVAs (OR 0.85; 95% CI 0.80-0.90, P<0.001) and (OR 1.15, 95% CI 1.02-1.29, P =0.021). ROC analysis demonstrated good predictive capacity for LA-LVAs, with an AUC of 0.733 (95% CI 0.650-0.794, P <0.001) for LAVi_max and 0.839 (95% CI 0.779-0.898, P <0.001) for LASr.

Conclusion: Automatic assessment of LAVi_max and LASr presents a promising non-invasive modality for predicting the presence of LA-LVAs and evaluating significant atrial remodeling in NVAF patients. This approach holds potential for aiding in risk stratification and treatment decision-making, ultimately improving clinical outcomes in patients.

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自动超声心动图评估左心房功能以预测非瓣膜性心房颤动的低电压区

目的：通过三维电子解剖图确定的左心房低电压区（LA-LVAs）对于确定心房颤动（AF）患者的治疗策略和预后至关重要。然而，方便准确地预测 LA-LVAs 仍具有挑战性。本研究旨在评估利用自动获得的超声心动图参数预测非瓣膜性心房颤动（NVAF）患者是否存在 LA-LVA 的可行性：这项回顾性研究纳入了 190 名接受初次导管消融术的 NVAF 患者。在消融术前，我们获得了超声心动图数据，并使用先进的软件（Dynamic-HeartModel 和 AutoStrain）自动计算了左心房容积和应变。同时还进行了电解剖图绘制（EAM）。对 LA-LVAs≥5% 的患者（LVAs 组）和结果进行比较：81例患者（42.6%）观察到LA-LVAs，其中持续性房颤患者的发生率明显高于阵发性房颤患者（55.6% vs 19.3%，P 0.001）。与非 LVAs 组相比，LVAs 组患者的年龄明显偏大，左室射血分数较低，心率较高，E/e'比值（P max 指数（LAVimax））较高，左房储腔应变（LASr）较低（P max 和 LASr 成为 LVAs 的独立指标（OR 0.85；95% CI 0.80-0.90，PP =0.021）。ROC 分析表明 LA-LVAs 具有良好的预测能力，AUC 为 0.733（95% CI 0.650-0.794，P 最大值）和 0.839（95% CI 0.779-0.898，P 结论）：自动评估 LAVimax 和 LASr 是预测 LA-LVA 的存在和评估 NVAF 患者心房重塑的一种很有前景的无创模式。这种方法有望帮助进行风险分层和治疗决策，最终改善患者的临床预后。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of General Medicine Medicine-General Medicine

自引率

0.00%

发文量

1113

审稿时长

16 weeks

期刊介绍： The International Journal of General Medicine is an international, peer-reviewed, open access journal that focuses on general and internal medicine, pathogenesis, epidemiology, diagnosis, monitoring and treatment protocols. The journal is characterized by the rapid reporting of reviews, original research and clinical studies across all disease areas. A key focus of the journal is the elucidation of disease processes and management protocols resulting in improved outcomes for the patient. Patient perspectives such as satisfaction, quality of life, health literacy and communication and their role in developing new healthcare programs and optimizing clinical outcomes are major areas of interest for the journal. As of 1st April 2019, the International Journal of General Medicine will no longer consider meta-analyses for publication.