可插入式心脏监护仪对室性早衰的检测和日常负荷的估计

IF 2.5 Q2 CARDIAC & CARDIOVASCULAR SYSTEMS
Kris Z. Siejko MSEE , Molly Kupfer PhD , Abhijit Rajan PhD , Keith Herrmann PhD , Devi Nair MD, FHRS
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引用次数: 0

摘要

背景:室性早搏(PVC)负荷是室性早搏诱发心肌病的临床重要指标,通常通过动态心电图(ECG)监测获得。目的本分析的目的是表征一种新的PVC检测算法的性能,该算法能够识别单个PVC和PVC序列(对联和三联),用于估计可插入式心脏监护仪(ICM)中的24小时PVC负担。方法通过ICM设备重放184例患者触发的ICM记录的748次心电事件,验证ICM算法检测室性早搏的性能。为了评估较长门诊期间的表现,对89名患者的24小时动态心电图数据集进行了评估,验证了相当于实施ICM算法的软件模型。该模型还用于评估麻省理工学院和贝斯以色列医院(MIT-BIH心律失常数据库)建立的参考库的性能,作为与其他已发表算法比较的基础。结果在icm存储的发作数据集上进行心跳水平验证,总PVC敏感性为80.1%,特异性为99.7%。24小时动态心电图负荷与ICM算法PVC负荷相关性r = 0.95。识别PVC负荷≥10%患者的敏感性为84%,患者水平阳性预测值(PPV)为100%。针对MIT-BIH数据集评估的PVC算法的节拍级灵敏度为87.9%,PPV为96.4%。结论ICM算法检测室性早搏可靠,灵敏度和特异性高。24小时PVC负荷测量显示与金标准12导联霍尔特有很强的相关性,可能为识别有左心室功能恶化风险的患者提供实用工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Premature ventricular contraction detection and estimation of daily burden by an insertable cardiac monitor

Premature ventricular contraction detection and estimation of daily burden by an insertable cardiac monitor

Background

Premature ventricular contraction (PVC) burden is a clinically important metric in the context of PVC-induced cardiomyopathy and is commonly obtained via ambulatory electrocardiogram (ECG) monitoring.

Objective

The purpose of this analysis is to characterize the performance of a novel PVC detection algorithm capable of identifying single PVCs and PVC sequences (couplets and triplets) for estimation of 24-hour PVC burden in an insertable cardiac monitor (ICM).

Methods

Performance of the ICM algorithm for detecting PVCs was validated by replaying 748 patient-triggered ICM-recorded ECG episodes from 184 patients through the ICM device. To assess performance over longer ambulatory periods, a validated software model equivalent of the implemented ICM algorithm was evaluated against a 24-hour Holter dataset of 89 patients. The model also was used to evaluate performance on an established reference library from the Massachusetts Institute of Technology and Beth Israel Hospital (MIT-BIH Arrhythmia Database) as a basis of comparison with other published algorithms.

Results

Beat-level validation on the ICM-stored episode dataset yielded a gross PVC sensitivity of 80.1% with a specificity of 99.7%. The correlation between 24-hour Holter burden and ICM algorithm PVC burden was r = 0.95. The sensitivity for identifying patients with PVC burdens ≥10% was 84%, with a patient-level positive predictive value (PPV) of 100%. Beat-level sensitivity of the PVC algorithm evaluated against the MIT-BIH dataset was 87.9% with a PPV of 96.4%.

Conclusion

The ICM algorithm reliably detects PVCs with high sensitivity and specificity. Twenty-four-hour PVC burden measurements demonstrated a strong correlation with a gold standard 12-lead Holter and may provide utility for identifying patients at risk for worsening left ventricular function.
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来源期刊
Heart Rhythm O2
Heart Rhythm O2 Cardiology and Cardiovascular Medicine
CiteScore
3.30
自引率
0.00%
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审稿时长
52 days
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