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流出道异位搏动的每小时变异性可预测其起源部位。

Hourly variability in outflow tract ectopy as a predictor of its site of origin.

机构信息

St George's University of London, Cranmer Terrace, London, UK.

St George's University Hospitals NHS Foundation Trust, London, UK.

出版信息

J Cardiovasc Electrophysiol. 2022 Jan;33(1):7-16. doi: 10.1111/jce.15295. Epub 2021 Nov 25.

DOI:10.1111/jce.15295
PMID:34797600
Abstract

INTRODUCTION

Before ablation, predicting the site of origin (SOO) of outflow tract ventricular arrhythmia (OTVA), can inform patient consent and facilitate appropriate procedural planning. We set out to determine if OTVA variability can accurately predict SOO.

METHODS

Consecutive patients with a clear SOO identified at OTVA ablation had their prior 24-h ambulatory ECGs retrospectively analysed (derivation cohort). Percentage ventricular ectopic (VE) burden, hourly VE values, episodes of trigeminy/bigeminy, and the variability in these parameters were evaluated for their ability to distinguish right from left-sided SOO. Effective parameters were then prospectively tested on a validation cohort of consecutive patients undergoing their first OTVA ablation.

RESULTS

High VE variability (coefficient of variation ≥0.7) and the presence of any hour with <50 VE, were found to accurately predict RVOT SOO in a derivation cohort of 40 patients. In a validation cohort of 29 patients, the correct SOO was prospectively identified in 23/29 patients (79.3%) using CoV, and 26/29 patients (89.7%) using VE < 50. Including current ECG algorithms, VE < 50 had the highest Youden Index (78), the highest positive predictive value (95.0%) and the highest negative predictive value (77.8%).

CONCLUSION

VE variability and the presence of a single hour where VE < 50 can be used to accurately predict SOO in patients with OTVA. Accuracy of these parameters compares favorably to existing ECG algorithms.

摘要

简介

在消融之前,预测流出道室性心律失常(OTVA)的起源部位(SOO)可以告知患者并有助于进行适当的程序规划。我们旨在确定 OTVA 变异性是否可以准确预测 SOO。

方法

对有明确 SOO 的 OTVA 消融患者的 24 小时动态心电图进行回顾性分析(推导队列)。评估心室异位(VE)负担的百分比、每小时 VE 值、三联律/二联律发作以及这些参数的变异性,以区分右侧和左侧 SOO。然后在接受首次 OTVA 消融的连续患者的验证队列中前瞻性测试有效参数。

结果

在 40 例患者的推导队列中发现高 VE 变异性(变异系数≥0.7)和任何小时 VE<50 的存在能够准确预测 RVOT SOO。在 29 例患者的验证队列中,使用 CoV 前瞻性地识别了 23/29 例患者(79.3%)的正确 SOO,使用 VE<50 识别了 26/29 例患者(89.7%)。包括当前的心电图算法,VE<50 具有最高的 Youden 指数(78%)、最高的阳性预测值(95.0%)和最高的阴性预测值(77.8%)。

结论

VE 变异性和 VE<50 的存在可用于准确预测 OTVA 患者的 SOO。这些参数的准确性优于现有的心电图算法。

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