Fitzpatrick Jesse K, Cohen Beth E, Rosenblatt Andrew, Shaw Richard E, Schiller Nelson B
Department of Medicine, University of California San Francisco, San Francisco, California.
Department of Medicine, University of California San Francisco, San Francisco, California; Department of Medicine, San Francisco Veterans Affairs Medical Center, San Francisco, California.
Am J Cardiol. 2018 Jun 15;121(12):1639-1644. doi: 10.1016/j.amjcard.2018.02.058. Epub 2018 Mar 13.
Left ventricular (LV) hypertrophy is strongly associated with increased cardiovascular morbidity and mortality. The 2-dimensional LV mass algorithms suffer from measurement variability that can lead to misclassification of patients with LV hypertrophy as normal, or vice versa. Among the 4 echocardiographic measurements required by the 2-dimensional LV mass algorithms, epicardial and endocardial area have the lowest interobserver variation and could be used to corroborate LV mass calculations. We sought cut-off values that are able to discriminate between elevated and normal LV mass based on endocardial or epicardial area alone. Using data from 664 men enrolled in the Mind Your Heart Study, we calculated the correlation of LV mass index with epicardial area and endocardial area. We then used receiver operator characteristic curves to identify epicardial and endocardial area cut-points that could discriminate subjects with normal LV mass and LV hypertrophy. LV mass index was more strongly correlated with epicardial area compared with endocardial area, r = 0.70 versus r = 0.27, respectively. Epicardial area had a significantly higher area under the receiver operator characteristic curve (p <0.001) compared with endocardial area, 0.90 (95% confidence interval 0.86 to 0.93) versus 0.63 (95% confidence interval 0.57 to 0.71). An epicardial area cut-point of ≥38.0 cm corresponded to a sensitivity of 95.0% and specificity of 54.4% for detecting LV hypertrophy. In conclusion, epicardial area showed promise as a method of rapid screening for LV hypertrophy and could be used to validate formal LV mass calculations.
左心室（LV）肥厚与心血管疾病发病率和死亡率的增加密切相关。二维左心室质量算法存在测量变异性，可能导致左心室肥厚患者被误分类为正常，反之亦然。在二维左心室质量算法所需的4项超声心动图测量中，心外膜和心内膜面积的观察者间变异最小，可用于证实左心室质量计算。我们寻求仅基于心内膜或心外膜面积就能区分左心室质量升高和正常的临界值。利用参与“关注你的心脏研究”的664名男性的数据，我们计算了左心室质量指数与心外膜面积和心内膜面积的相关性。然后，我们使用受试者工作特征曲线来确定能够区分左心室质量正常和左心室肥厚受试者的心外膜和心内膜面积切点。与心内膜面积相比，左心室质量指数与心外膜面积的相关性更强，分别为r = 0.70和r = 0.27。与心内膜面积相比，心外膜面积在受试者工作特征曲线下的面积显著更高（p <0.001），分别为0.90（95%置信区间0.86至0.93）和0.63（95%置信区间0.57至0.71）。心外膜面积切点≥38.0 cm时，检测左心室肥厚的敏感性为95.0%，特异性为54.4%。总之，心外膜面积有望成为一种快速筛查左心室肥厚的方法，并可用于验证正式的左心室质量计算。
