Direct Comparison of Methods to Differentiate Wide Complex Tachycardias: Novel Automated Algorithms Versus Manual ECG Interpretation Approaches.

IF 9.1 1区医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS

Circulation. Arrhythmia and electrophysiology Pub Date : 2024-08-01 Epub Date: 2024-07-25 DOI:10.1161/CIRCEP.123.012663

Sarah LoCoco, Anthony H Kashou, Abhishek J Deshmukh, Samuel J Asirvatham, Christopher V DeSimone, Krasimira M Mikhova, Sandeep S Sodhi, Phillip S Cuculich, Rugheed Ghadban, Daniel H Cooper, Thomas M Maddox, Peter A Noseworthy, Adam M May

{"title":"Direct Comparison of Methods to Differentiate Wide Complex Tachycardias: Novel Automated Algorithms Versus Manual ECG Interpretation Approaches.","authors":"Sarah LoCoco, Anthony H Kashou, Abhishek J Deshmukh, Samuel J Asirvatham, Christopher V DeSimone, Krasimira M Mikhova, Sandeep S Sodhi, Phillip S Cuculich, Rugheed Ghadban, Daniel H Cooper, Thomas M Maddox, Peter A Noseworthy, Adam M May","doi":"10.1161/CIRCEP.123.012663","DOIUrl":null,"url":null,"abstract":"Background: Differentiating wide complex tachycardias (WCTs) into ventricular tachycardia (VT) and supraventricular wide tachycardia via 12-lead ECG interpretation is a crucial but difficult task. Automated algorithms show promise as alternatives to manual ECG interpretation, but direct comparison of their diagnostic performance has not been undertaken.Methods: Two electrophysiologists applied 3 manual WCT differentiation approaches (ie, Brugada, Vereckei aVR, and VT score). Simultaneously, computerized data from paired WCT and baseline ECGs were processed by 5 automated WCT differentiation algorithms (WCT Formula, WCT Formula II, VT Prediction Model, Solo Model, and Paired Model). The diagnostic performance of automated algorithms was compared with manual ECG interpretation approaches.Results: A total of 212 WCTs (111 VT and 101 supraventricular wide tachycardia) from 104 patients were analyzed. WCT Formula demonstrated superior accuracy (85.8%) and specificity (87.1%) compared with Brugada (75.2% and 57.4%, respectively) and Vereckei aVR (65.3% and 36.4%, respectively). WCT Formula II achieved higher accuracy (89.6%) and specificity (85.1%) against Brugada and Vereckei aVR. Performance metrics of the WCT Formula (accuracy 85.8%, sensitivity 84.7%, and specificity 87.1%) and WCT Formula II (accuracy 89.8%, sensitivity 89.6%, and specificity 85.1%) were similar to the VT score (accuracy 84.4%, sensitivity 93.8%, and specificity 74.2%). Paired Model was superior to Brugada in accuracy (89.6% versus 75.2%), specificity (97.0% versus 57.4%), and F1 score (0.89 versus 0.80). Paired Model surpassed Vereckei aVR in accuracy (89.6% versus 65.3%), specificity (97.0% versus 75.2%), and F1 score (0.89 versus 0.74). Paired Model demonstrated similar accuracy (89.6% versus 84.4%), inferior sensitivity (79.3% versus 93.8%), but superior specificity (97.0% versus 74.2%) to the VT score. Solo Model and VT Prediction Model accuracy (82.5% and 77.4%, respectively) was superior to the Vereckei aVR (65.3%) but similar to Brugada (75.2%) and the VT score (84.4%).Conclusions: Automated WCT differentiation algorithms demonstrated favorable diagnostic performance compared with traditional manual ECG interpretation approaches.","PeriodicalId":10319,"journal":{"name":"Circulation. Arrhythmia and electrophysiology","volume":" ","pages":"e012663"},"PeriodicalIF":9.1000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Circulation. Arrhythmia and electrophysiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1161/CIRCEP.123.012663","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/25 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}

引用次数: 0

Abstract

Background: Differentiating wide complex tachycardias (WCTs) into ventricular tachycardia (VT) and supraventricular wide tachycardia via 12-lead ECG interpretation is a crucial but difficult task. Automated algorithms show promise as alternatives to manual ECG interpretation, but direct comparison of their diagnostic performance has not been undertaken.

Methods: Two electrophysiologists applied 3 manual WCT differentiation approaches (ie, Brugada, Vereckei aVR, and VT score). Simultaneously, computerized data from paired WCT and baseline ECGs were processed by 5 automated WCT differentiation algorithms (WCT Formula, WCT Formula II, VT Prediction Model, Solo Model, and Paired Model). The diagnostic performance of automated algorithms was compared with manual ECG interpretation approaches.

Results: A total of 212 WCTs (111 VT and 101 supraventricular wide tachycardia) from 104 patients were analyzed. WCT Formula demonstrated superior accuracy (85.8%) and specificity (87.1%) compared with Brugada (75.2% and 57.4%, respectively) and Vereckei aVR (65.3% and 36.4%, respectively). WCT Formula II achieved higher accuracy (89.6%) and specificity (85.1%) against Brugada and Vereckei aVR. Performance metrics of the WCT Formula (accuracy 85.8%, sensitivity 84.7%, and specificity 87.1%) and WCT Formula II (accuracy 89.8%, sensitivity 89.6%, and specificity 85.1%) were similar to the VT score (accuracy 84.4%, sensitivity 93.8%, and specificity 74.2%). Paired Model was superior to Brugada in accuracy (89.6% versus 75.2%), specificity (97.0% versus 57.4%), and F1 score (0.89 versus 0.80). Paired Model surpassed Vereckei aVR in accuracy (89.6% versus 65.3%), specificity (97.0% versus 75.2%), and F1 score (0.89 versus 0.74). Paired Model demonstrated similar accuracy (89.6% versus 84.4%), inferior sensitivity (79.3% versus 93.8%), but superior specificity (97.0% versus 74.2%) to the VT score. Solo Model and VT Prediction Model accuracy (82.5% and 77.4%, respectively) was superior to the Vereckei aVR (65.3%) but similar to Brugada (75.2%) and the VT score (84.4%).

Conclusions: Automated WCT differentiation algorithms demonstrated favorable diagnostic performance compared with traditional manual ECG interpretation approaches.

查看原文本刊更多论文

直接比较区分宽复律心动过速的方法：新型自动算法与手动心电图解读方法。

背景：通过 12 导联心电图解读将宽复律心动过速（WCT）区分为室性心动过速（VT）和室上性宽心动过速是一项关键但困难的任务。自动算法有望替代人工心电图解读，但尚未对其诊断性能进行直接比较：方法：两位电生理学家采用了 3 种手动 WCT 鉴别方法（即 Brugada、Vereckei aVR 和 VT 评分）。同时，5 种自动 WCT 分型算法（WCT 公式、WCT 公式 II、VT 预测模型、Solo 模型和配对模型）对配对 WCT 和基线心电图的计算机数据进行了处理。将自动算法的诊断性能与人工心电图解读方法进行了比较：结果：共分析了 104 名患者的 212 个 WCT（111 个 VT 和 101 个室上性宽心动过速）。与 Brugada（分别为 75.2% 和 57.4%）和 Vereckei aVR（分别为 65.3% 和 36.4%）相比，WCT 公式的准确性（85.8%）和特异性（87.1%）更高。WCT 公式 II 对 Brugada 和 Vereckei aVR 的准确性（89.6%）和特异性（85.1%）更高。WCT 公式（准确率 85.8%、灵敏度 84.7%、特异性 87.1%）和 WCT 公式 II（准确率 89.8%、灵敏度 89.6%、特异性 85.1%）的性能指标与 VT 评分（准确率 84.4%、灵敏度 93.8%、特异性 74.2%）相似。配对模型在准确性（89.6% 对 75.2%）、特异性（97.0% 对 57.4%）和 F1 评分（0.89 对 0.80）方面均优于 Brugada。在准确性（89.6% 对 65.3%）、特异性（97.0% 对 75.2%）和 F1 评分（0.89 对 0.74）方面，配对模型超过了 Vereckei aVR。配对模型的准确性（89.6% 对 84.4%）和灵敏度（79.3% 对 93.8%）与 VT 评分相似，但特异性（97.0% 对 74.2%）却不如 VT 评分。Solo模型和VT预测模型的准确性（分别为82.5%和77.4%）优于Vereckei aVR（65.3%），但与Brugada（75.2%）和VT评分（84.4%）相似：结论：与传统的人工心电图解读方法相比，自动 WCT 鉴别算法表现出良好的诊断性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Circulation. Arrhythmia and electrophysiology 医学-心血管系统

CiteScore

13.70

自引率

4.80%

发文量

187

审稿时长

4-8 weeks

期刊介绍： Circulation: Arrhythmia and Electrophysiology is a journal dedicated to the study and application of clinical cardiac electrophysiology. It covers a wide range of topics including the diagnosis and treatment of cardiac arrhythmias, as well as research in this field. The journal accepts various types of studies, including observational research, clinical trials, epidemiological studies, and advancements in translational research.