A combined anatomic and electrophysiologic substrate based approach for sudden cardiac death risk stratification.
A combined anatomic and electrophysiologic substrate based approach for sudden cardiac death risk stratification.
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DOI：
10.1016/j.ahj.2013.06.023
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发表时间：
2013-10
影响因子：
4.8
通讯作者：
Armoundas, Antonis A.
中科院分区：
文献类型：
--
作者：
Merchant, Faisal M.;Zheng, Hui;Bigger, Thomas;Steinman, Richard;Ikeda, Takanori;Pedretti, Roberto F. E.;Salerno-Uriarte, Jorge A.;Klersy, Catherine;Chan, Paul S.;Bartone, Cheryl;Hohnloser, Stefan H.;Ruskin, Jeremy N.;Armoundas, Antonis A.
尽管左心室射血分数 (LVEF) 是心源性猝死 (SCD) 风险分层的主要决定因素，但单独来看，LVEF 是次优的风险分层因素。我们评估了多标志物策略是否能够比单独的 LVEF 提供更稳健的 SCD 风险分层。我们从 6 项研究中收集了患者水平数据 (n=3355)，评估微伏 T 波交替 (MTWA) 测试的预后效用。该组的三分之二用于推导 (n=2242)，三分之一用于验证 (n=1113)。使用接受者操作特征 (ROC) 曲线下面积（c 指数）评估多变量模型的判别能力。主要终点是 24 个月时的 SCD。在衍生队列中，59 名患者在 24 个月内经历了 SCD。逐步选择表明，基于 3 个参数（LVEF、冠状动脉疾病 [CAD] 和 MTWA 状态）的模型可提供最佳的 SCD 风险预测。在推导队列中，模型的 c 指数为 0.817，显着优于用作单一变量的 LVEF（0.637，p < 0.001）。在验证队列中，36 名患者在 24 个月内经历了 SCD。用于预测主要终点的模型的 c 指数再次显着优于单独的 LVEF（0.774 vs. 0.671，p = 0.020）。基于 CAD、LVEF 和 MTWA 状态的多变量模型可提供比 LVEF 作为单一风险标记更稳健的 SCD 风险预测。这些发现表明，基于电解剖基质不同方面的多标记策略可能能够改进一级预防 ICD 治疗算法。
Although left ventricle ejection fraction (LVEF) is the primary determinant for sudden cardiac death (SCD) risk stratification, in isolation, LVEF is a sub-optimal risk stratifier. We assessed whether a multi-marker strategy would provide more robust SCD risk stratification than LVEF alone. We collected patient-level data (n=3355) from 6 studies assessing the prognostic utility of microvolt T-wave alternans (MTWA) testing. Two-thirds of the group was used for derivation (n=2242) and one-third for validation (n=1113). The discriminative capacity of the multivariable model was assessed using the area under the receiver-operating characteristic (ROC) curve (c-index). The primary endpoint was SCD at 24 months. In the derivation cohort, 59 patients experienced SCD by 24 months. Stepwise selection suggested that a model based on 3 parameters (LVEF, coronary artery disease [CAD] and MTWA status) provided optimal SCD risk prediction. In the derivation cohort, the c-index of the model was 0.817, which was significantly better than LVEF used as a single variable (0.637, p < 0.001). In the validation cohort, 36 patients experienced SCD by 24 months. The c-index of the model for predicting the primary endpoint was again significantly better than LVEF alone (0.774 vs. 0.671, p = 0.020). A multivariable model based on presence of CAD, LVEF and MTWA status provides significantly more robust SCD risk prediction than LVEF as a single risk marker. These findings suggest that multi-marker strategies based on different aspects of the electro-anatomic substrate may be capable of improving primary prevention ICD treatment algorithms.
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影响因子：
37.8
作者：
Fishman GI;Chugh SS;Dimarco JP;Albert CM;Anderson ME;Bonow RO;Buxton AE;Chen PS;Estes M;Jouven X;Kwong R;Lathrop DA;Mascette AM;Nerbonne JM;O'Rourke B;Page RL;Roden DM;Rosenbaum DS;Sotoodehnia N;Trayanova NA;Zheng ZJ
通讯作者：
Zheng ZJ
影响因子：
39.3
作者：
Gorgels, APM;Gijsbers, C;Wellens, HJJ
通讯作者：
Wellens, HJJ
影响因子：
37.8
作者：
Grimm, W;Christ, M;Maisch, B
通讯作者：
Maisch, B
影响因子：
24
作者：
Chugh, SS;Jui, J;McAnulty, J
通讯作者：
McAnulty, J
影响因子：
2.8
作者：
Ikeda, T;Saito, H;Ohnishi, Y
通讯作者：
Ohnishi, Y