Long QT syndrome. New electrocardiographic characteristics.
Long QT syndrome. New electrocardiographic characteristics.
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长 QT 综合征。
DOI：
10.1161/01.cir.82.2.521
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发表时间：
1990
期刊：
影响因子：
37.8
通讯作者：
Cui,L
中科院分区：
文献类型：
--
作者：
Benhorin,J;Merri,M;Alberti,M;Locati,E;Moss,AJ;Hall,WJ;Cui,L
长QT综合征的心电图特征是QT间期延长和其他一些更微妙的ST-T-U波异常，其中大多数尚未量化。为了确定几个新的心电图特征在识别已知长QT综合征患者中的可能有用性，将逻辑回归模型应用于七个新的相对独立的心电图复极变量的数据库。对315名正常受试者和37名长QT综合征患者（长QT综合征家族成员，QTc大于0.44秒，27%有症状）的数字化12导联心电图进行测量，这些患者年龄从17岁到60岁不等。独立区分长QT综合征患者与正常受试者的心电图变量（p < 0.001）包括复极的定量测量：早期持续时间、频率、T波对称性、晚期现象和异质性。除早期持续时间变量外，所有复极变量与QTc基本无关（r2小于0.15），均有助于长QT综合征患者的识别。5个心电图预测变量的分类模型估计灵敏度（95%置信区间）为92.6%(81.6-100%)，估计特异性（95%置信区间）为95.8%（93.6-98.1%）。该模型的表现明显优于基于早期持续时间变量作为单一预测变量的分类模型。长QT综合征患者的症状状态不能通过所研究模型中心电图变量的任何组合来预测。
The long QT syndrome is electrocardiographically characterized by a prolonged QT interval and by several other, more subtle, ST-T-U wave abnormalities, most of which have not been quantified. To determine the possible usefulness of several new electrocardiographic characteristics in identifying patients with known long QT syndrome, logistic regression models were applied to a data base of seven new, relatively independent, electrocardiographic repolarization variables. These were measured on digitized 12-lead electrocardiograms of 315 normal subjects and 37 patients with the long QT syndrome (members of well-identified long QT syndrome families, QTc greater than 0.44 second, 27% symptomatic), who ranged in age from 17 to 60 years. Electrocardiographic variables that independently differentiated (p less than 0.001) patients with long QT syndrome from normal subjects included quantitative measures of repolarization: early duration, rate, T wave symmetry, late phenomena, and heterogeneity. All selected repolarization variables except the early duration variable were essentially independent of the QTc (r2 less than 0.15), and all contributed significantly to the identification of patients with long QT syndrome. A classification model of five electrocardiographic predictor variables resulted in an estimated sensitivity (95% confidence interval) of 92.6% (81.6-100%) and an estimated specificity (95% confidence interval) of 95.8% (93.6-98.1%). This model performed significantly better than an alternative classification model that was based on the early duration variable as a single predictor variable. The symptomatic status of patients with long QT syndrome could not be predicted by any combination of the electrocardiographic variables in the investigated model.