Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA.
Am J Cardiol. 2013 Sep 15;112(6):805-10. doi: 10.1016/j.amjcard.2013.04.058. Epub 2013 Jun 11.
Electrocardiographic lead aVR is often ignored in clinical practice. The aim of this study was to investigate whether ST-T wave amplitude in lead aVR predicts cardiovascular (CV) mortality and if this variable adds value to a traditional risk prediction model. A total of 7,928 participants enrolled in the National Health and Nutrition Examination Survey (NHANES) III with electrocardiographic data available were included. Each participant had 13.5 ± 3.8 years of follow-up. The study sample was stratified according to ST-segment amplitude and T-wave amplitude in lead aVR. ST-segment elevation (>8 μV) in lead aVR was predictive of CV mortality in the multivariate analysis when not accounting for T-wave amplitude. The finding lost significance after including T-wave amplitude in the model. A positive T wave in lead aVR (>0 mV) was the strongest multivariate predictor of CV mortality (hazard ratio 3.37, p <0.01). The addition of T-wave amplitude in lead aVR to the Framingham risk score led to a net reclassification improvement of 2.7% of subjects with CV events and 2.3% of subjects with no events (p <0.01). Furthermore, in the intermediate-risk category, 20.0% of the subjects in the CV event group and 9.1% of subjects in the no-event group were appropriately reclassified. The absolute integrated discrimination improvement was 0.012 (p <0.01), and the relative integrated discrimination improvement was 11%. In conclusion, T-wave amplitude in lead aVR independently predicts CV mortality in a cross-sectional United States population. Adding T-wave abnormalities in lead aVR to the Framingham risk score improves model discrimination and calibration with better reclassification of intermediate-risk subjects.
心电图导联 aVR 在临床实践中经常被忽视。本研究旨在探讨 aVR 导联的 ST-T 波振幅是否可预测心血管（CV）死亡率，以及该变量是否可增加传统风险预测模型的价值。共有 7928 名接受过心电图检查且可获得心电图数据的美国国家健康和营养调查（NHANES）III 参与者被纳入研究。每位参与者的随访时间为 13.5±3.8 年。研究样本根据 aVR 导联的 ST 段振幅和 T 波振幅进行分层。当不考虑 T 波振幅时，aVR 导联的 ST 段抬高（>8μV）在多变量分析中可预测 CV 死亡率。纳入模型后，该发现失去了意义。aVR 导联的正向 T 波（>0mV）是 CV 死亡率的最强多变量预测因素（危险比 3.37，p<0.01）。将 aVR 导联的 T 波振幅添加到Framingham 风险评分中，可使 CV 事件组和无事件组的受试者分别有 2.7%和 2.3%的受试者得到净重新分类改善（p<0.01）。此外，在中危组中，CV 事件组中有 20.0%的受试者和无事件组中有 9.1%的受试者得到了适当的重新分类。绝对综合鉴别改善为 0.012（p<0.01），相对综合鉴别改善为 11%。总之，aVR 导联的 T 波振幅可独立预测美国横断面人群的 CV 死亡率。将 aVR 导联的 T 波异常添加到Framingham 风险评分中可提高模型的鉴别力和校准度，并改善中危人群的重新分类。
