Suppr超能文献

下壁导联Q波形态在诊断室性心动过速中的应用

Utility of Inferior Lead Q-waveforms in diagnosing Ventricular Tachycardia.

作者信息

Subramany Swathi, Kattoor Ajoe John, Kovelamudi Swathi, Devabhaktuni Subodh, Mehta Jawahar L, Vallurupalli Srikanth, Paydak Hakan, Pothineni Naga Venkata K

机构信息

Division of Internal medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA.

Division of Cardiology, Cook County Health, Chicago, IL, USA.

出版信息

Clin Med Insights Cardiol. 2020 Aug 30;14:1179546820953416. doi: 10.1177/1179546820953416. eCollection 2020.

Abstract

BACKGROUND

Electrocardiogram (ECG) differentiation of wide complex tachycardia (WCT) into ventricular tachycardia (VT) and supraventricular tachycardia with aberration (SVT-A) is often challenging.

OBJECTIVE

To determine if the presence of Q-waveforms (QS, Qr, QRs) in the inferior leads (II, III, aVF) can differentiate VT from SVT-A in a WCT compared to Brugada algorithm. We studied 2 inferior lead criteria namely QWC-A where all the inferior leads had a similar Q wave pattern and QWC-B where only lead aVF had a Q-waveform.

METHODS

A total of 181 consecutive cases of WCT were identified, digitally separated into precordial leads and inferior leads and independently reviewed by 2 electrophysiologists. An electrocardiographic diagnosis of VT or SVT-A was assigned based on Brugada and inferior lead algorithms. Results were compared to the final clinical diagnosis.

RESULTS

VT was the final clinical diagnosis in 24.9% of ECG cohort (45/181); 75.1% (136/181) were SVT-A. QWC-A and QWC-B had a high specificity (93.3% and 82.8%) and accuracy (78.2% and 71.0%), but low sensitivity (33.3% and 35.6%) in differentiating VT from SVT-A. The Brugada algorithm yielded a sensitivity of 82.2% and specificity of 68.4%. Area under the curve in ROC analysis was highest with Brugada algorithm (0.75, 95% CI 0.69-0.81) followed by QWC-A (0.63, 95% CI 0.56-0.70) and QWC-B (0.59, 95% CI 0.52-0.67).

CONCLUSION

QWC-A and QWC-B criteria had poor sensitivity but high specificity in diagnosing VT in patients presenting with WCT. Further research combining this simple criterion with other newer diagnostic algorithms can potentially improve the accuracy of the overall diagnostic algorithm.

摘要

背景

将宽QRS波心动过速(WCT)心电图(ECG)鉴别为室性心动过速(VT)和伴差异性传导的室上性心动过速(SVT-A)通常具有挑战性。

目的

确定下壁导联(II、III、aVF)中Q波形(QS、Qr、QRs)的存在与Brugada算法相比,能否在WCT中鉴别VT和SVT-A。我们研究了2种下壁导联标准,即QWC-A(所有下壁导联具有相似的Q波形态)和QWC-B(仅aVF导联有Q波形)。

方法

共识别出181例连续的WCT病例,将其数字化分离为胸前导联和下壁导联,并由2名电生理学家独立审查。根据Brugada算法和下壁导联算法对VT或SVT-A进行心电图诊断。将结果与最终临床诊断进行比较。

结果

在心电图队列中,24.9%(45/181)的最终临床诊断为VT;75.1%(136/181)为SVT-A。在鉴别VT和SVT-A时,QWC-A和QWC-B具有较高的特异性(分别为93.3%和82.8%)和准确性(分别为78.2%和71.0%),但敏感性较低(分别为33.3%和35.6%)。Brugada算法的敏感性为82.2%,特异性为68.4%。ROC分析中,曲线下面积以Brugada算法最高(0.75,95%CI 0.69-0.81),其次是QWC-A(0.63,95%CI 0.56-0.70)和QWC-B(0.59,95%CI 0.52-0.67)。

结论

QWC-A和QWC-B标准在诊断WCT患者的VT时敏感性较差,但特异性较高。将这个简单标准与其他更新的诊断算法相结合的进一步研究可能会提高整体诊断算法的准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a11b/7466884/b7a7fd9b7176/10.1177_1179546820953416-fig1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验