数字式心电图复合体用于阵发性心房颤动的危险分层。

Sovremennye tekhnologii v meditsine Pub Date : 2024-01-01 Epub Date: 2024-06-28 DOI:10.17691/stm2024.16.3.05
A V Frolov, O P Melnikova, A P Vorobiev, T G Vaikhanskaya
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引用次数: 0

摘要

该研究的目的是开发和临床测试一种硬件和软件系统,该系统能够使用12导联的窦性心律心电图数据识别心房颤动(AF)的隐藏形式的预测因子。材料与方法:开发了“Intecard 8.1”软硬件系统,通过3-5分钟的窦性心律心电图记录,评估一组心房电不稳定指标。标记物包括导联p波振幅120ms、房间阻滞先进性、双相p波末端部分面积3个点。对120例缺血性心脏病或扩张型心肌病患者进行了“Intecard 8.1”系统的临床测试。患者平均年龄57.9±13.1岁。结果:由于p波检测信号幅值低、噪声大、房室传导阻滞或明显心动过速时t波与p波叠加的错误概率高,是一项具有挑战性的任务。为了提高检测效率,采用了相位变换方法,研究了其相位分量arctg[x(n)/Rv],其中x(n)为心电信号样本,Rv为常数。我们开发了一种识别算法,在“Intecard 8.1”软件中实现,并正在进行临床试验。在12 [6;观察22个月,120例患者中有22例发生房颤(18.3%)。AF发作患者p波振幅显著降低(p=0.029), p波持续时间增加(p3分),具有最高的预后意义。ROC曲线下面积AUC为0.988,95%可信区间为0.975 ~ 0.999 (p)结论:在分析3 ~ 5分钟的窦性心律心电图记录时,使用数字心电图复图“Intecard 8.1”可以识别高危或隐匿房颤的患者。p波参数的动态评估为该患者队列的个性化心律控制提供了机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Digital Electrocardiographic Complex for Risk Stratification of Paroxysmal Atrial Fibrillation.

Digital Electrocardiographic Complex for Risk Stratification of Paroxysmal Atrial Fibrillation.

Digital Electrocardiographic Complex for Risk Stratification of Paroxysmal Atrial Fibrillation.

The aim of the study was to develop and clinically test a hardware and software system capable of identifying the predictors of the hidden forms of atrial fibrillation (AF) using 12-lead ECG data in sinus rhythm.

Materials and methods: There was developed the hardware and software system "Intecard 8.1" to assess a set of markers for atrial electrical instability by 3-5-minute ECG recordings in sinus rhythm. The markers include P-wave amplitude in lead II <0.1 mV, P-wave duration >120 ms, advanced interatrial block, the area of the biphasic P-wave terminal part <-4 mV·ms, and MVP (morphology-voltage- P-wave duration) score >3 points.The clinical testing of "Intecard 8.1" system was carried out on 120 patients with ischemic heart disease or dilated cardiomyopathy. The patients' average age was 57.9±13.1 years.

Results: P-wave detection is a challenging task due to a low signal amplitude, noise, high error probability in atrioventricular block or T-wave and P-wave superposition in case of marked tachycardia. To improve detection, a phase transformation method was used, according to which there was studied its phase component arctg[x(n)/Rv], where x(n) - ECG signal samples, Rv - a constant. We developed an identification algorithm implemented in "Intecard 8.1" software, its clinical trials being conducted.During the 12 [6; 22] month observation period, AF episodes were recorded in 22 from 120 patients (18.3%). The patients with AF episodes exhibited a significant decrease in P-wave amplitude (p=0.029), its duration increase (p<0.001), and a significantly high MVP score (p<0.01). The MVP score with a cut-off point >3 points is of the highest prognostic significance. The area under the ROC curve AUC was 0.988 with a 95% confidence interval: 0.975-0.999 (p<0.001). The prediction model of hidden AF paroxysms has sensitivity and specificity: 92 and 89%, respectively.

Conclusion: The digital electrocardiographic complex "Intecard 8.1" when analyzing 3-5-minute ECG recordings with sinus rhythm enables to identify the patients with high risk or with hidden AF forms. The dynamic assessment of P-wave parameters offers an opportunity to personalize heart rhythm control in this patient cohort.

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