Background

Brugada syndrome is a rare inherited arrhythmic syndrome with a coved type 1 ST-segment elevation on ECG and an increased risk of sudden death. Many studies have evaluated risk stratification performance based on ECG-derived parameters. However, since historical Brugada patient cohorts included mostly paper ECGs, most studies have been based on manual ECG parameter measurements.

We hypothesized that it would be possible to run automated algorithm-based analysis of paper ECGs.

We aimed: 1) to validate the digitization process for paper ECGs in Brugada patients; and 2) to quantify the acute class I antiarrhythmic drug effect on relevant ECG parameters in Brugada syndrome.

Methods

A total of 176 patients (30% female, 43 ± 13 years old) with induced type 1 Brugada syndrome ECG were included in the study. All of the patients had paper ECGs before and during class I antiarrhythmic drug challenge. Twenty patients also had a digital ECG, in whom printouts were used to validate the digitization process.

Paper ECGs were scanned and then digitized using ECGScan software, version 3.4.0 (AMPS, LLC, New York, NY, USA) to obtain FDA HL7 XML format ECGs. Measurements were automatically performed using the Bravo (AMPS, LLC, New York, NY, USA) and Glasgow algorithms.

Results

ECG parameters obtained from digital and digitized ECGs were closely correlated (r = 0.96 ± 0.07, R² = 0.93 ± 0.12). Class I antiarrhythmic drugs significantly increased the global QRS duration (from 113 ± 20 to 138 ± 23, p < 0.0001). On lead V2, class I antiarrhythmic drugs increased ST-segment elevation (from 110 ± 84 to 338 ± 227 μV, p < 0.0001), decreased the ST slope (from 14.9 ± 23.3 to −27.4 ± 28.5, p < 0.0001) and increased the TpTe interval (from 88 ± 18 to 104 ± 33, p < 0.0001).

Conclusions

Automated algorithm-based measurements of depolarization and repolarization parameters from digitized paper ECGs are reliable and could quantify the acute effects of class 1 antiarrhythmic drug challenge in Brugada patients. Our results support using computerized automated algorithm-based analyses from digitized paper ECGs to establish risk stratification decision trees in Brugada syndrome.

中文翻译：

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基于计算机自动算法的 Brugada 综合征数字化纸质心电图分析

背景

Brugada 综合征是一种罕见的遗传性心律失常综合征，心电图表现为 1 型 ST 段抬高，猝死风险增加。许多研究已经根据 ECG 衍生参数评估了风险分层性能。然而，由于历史上的 Brugada 患者队列主要包括纸质心电图，因此大多数研究都是基于手动心电图参数测量。

我们假设可以对纸质心电图进行基于算法的自动分析。

我们的目标是：1) 验证 Brugada 患者纸质心电图的数字化过程；2) 量化急性 I 类抗心律失常药物对 Brugada 综合征相关心电图参数的影响。

方法

共有 176 名患有诱导 1 型 Brugada 综合征心电图的患者（30% 女性，43 ± 13 岁）被纳入研究。所有患者在 I 类抗心律失常药物挑战之前和期间都有纸质心电图。20 名患者还拥有数字心电图，其中打印输出用于验证数字化过程。

对纸质心电图进行扫描，然后使用 ECGScan 软件 3.4.0 版（AMPS, LLC, New York, NY, USA）进行数字化，以获得 FDA HL7 XML 格式的心电图。使用 Bravo (AMPS, LLC, New York, NY, USA) 和 Glasgow 算法自动进行测量。

结果

从数字和数字化心电图获得的心电图参数密切相关 ( r  = 0.96 ± 0.07, R ²  = 0.93 ± 0.12)。I 类抗心律失常药物显着增加了整体 QRS 持续时间（从 113 ± 20 到 138 ± 23，p  < 0.0001）。在导联 V2 上，I 类抗心律失常药物增加 ST 段抬高（从 110 ± 84 至 338 ± 227 μV，p  < 0.0001），降低 ST 斜率（从 14.9 ± 23.3 至 -27.4 ± 28.5，p  < 0.0001）并增加TpTe 间隔（从 88 ± 18 到 104 ± 33，p < 0.0001）。

结论

基于算法的数字化纸质心电图去极化和复极化参数的自动测量是可靠的，并且可以量化 Brugada 患者中 1 类抗心律失常药物挑战的急性影响。我们的结果支持使用来自数字化纸质心电图的基于计算机自动算法的分析来建立 Brugada 综合征的风险分层决策树。