Kawazoe Hiroshi, Nakano Yukiko, Ochi Hidenori, Takagi Masahiko, Hayashi Yusuke, Uchimura Yuko, Tokuyama Takehito, Watanabe Yoshikazu, Matsumura Hiroya, Tomomori Shunsuke, Sairaku Akinori, Suenari Kazuyoshi, Awazu Akinori, Miwa Yosuke, Soejima Kyoko, Chayama Kazuaki, Kihara Yasuki
Department of Cardiovascular Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Department of Cardiovascular Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Heart Rhythm. 2016 Oct;13(10):1947-54. doi: 10.1016/j.hrthm.2016.07.009. Epub 2016 Jul 14.
Risk stratification for ventricular fibrillation (VF) in patients with Brugada syndrome (BrS) remains controversial.
The purpose of this study was to construct a novel prediction model for VF risk in BrS patients using noninvasive parameters.
A total of 143 Japanese BrS patients with VF (n = 35) and without VF (n = 108) were retrospectively enrolled. We built a logistic regression model predicting VF occurrence and evaluated it by cross-validation.
Frequencies of history of syncope and spontaneous type 1 ECG, r-J interval in V1, QRS duration in V6, and LAS40, Tpeak-Tend dispersion, and max T-wave alternans were significantly associated with VF occurrence in univariate analyses. The history of syncope, r-J interval in V1, QRS duration in V6, and Tpeak-Tend dispersion were identified as independent predictors by multivariate logistic regression analysis. The predictive model was constructed using all these parameters with good discrimination of VF occurrence (area under the curve 0.869 with 97.1% sensitivity and 65.7% specificity). The area under the curve based on leave-one-out cross-validation was 0.845, with 97.1% sensitivity and 63.0% specificity suggesting good performance of the model. Retrospective survival analysis revealed that the cumulative VF event rate was significantly higher in patients at high risk than in those with low risk using the log rank test (P = 2.97 × 10(-8)). Notably, no BrS patient below the cutoff value developed a subsequent VF event.
This novel prediction method may effectively assesses VF risk in BrS patients, especially when determining implantable cardioverter-defibrillator placement for asymptomatic BrS patients.
Brugada综合征（BrS）患者心室颤动（VF）的风险分层仍存在争议。
本研究旨在使用无创参数构建一种新的BrS患者VF风险预测模型。
回顾性纳入143例日本BrS患者，其中有VF的患者35例，无VF的患者108例。我们建立了一个预测VF发生的逻辑回归模型，并通过交叉验证对其进行评估。
在单因素分析中，晕厥病史、自发1型心电图、V1导联r-J间期、V6导联QRS波时限、LAS40、T波峰末间期离散度和最大T波交替均与VF发生显著相关。通过多因素逻辑回归分析，晕厥病史、V1导联r-J间期、V6导联QRS波时限和T波峰末间期离散度被确定为独立预测因素。使用所有这些参数构建预测模型，对VF发生具有良好的区分度（曲线下面积为0.869，敏感性为97.1%，特异性为65.7%）。基于留一法交叉验证的曲线下面积为0.845，敏感性为97.1%，特异性为63.0%，表明该模型性能良好。回顾性生存分析显示，使用对数秩检验，高危患者的累积VF事件发生率显著高于低危患者（P = 2.97×10⁻⁸）。值得注意的是，低于临界值的BrS患者未发生后续VF事件。
这种新的预测方法可以有效评估BrS患者的VF风险，尤其是在为无症状BrS患者确定植入式心脏复律除颤器植入时。
