Department of Medicine, Vanderbilt University, Nashville, Tennessee 37232, USA.
Heart Rhythm. 2011 Feb;8(2):271-7. doi: 10.1016/j.hrthm.2010.10.034. Epub 2010 Oct 29.
Traditional electrocardiographic (ECG) reference ranges were derived from studies in communities or clinical trial populations. The distribution of ECG parameters in a large population presenting to a healthcare system has not been studied.
The purpose of this study was to define the contribution of age, race, gender, height, body mass index, and type 2 diabetes mellitus to normal ECG parameters in a population presenting to a healthcare system.
Study subjects were obtained from the Vanderbilt Synthetic Derivative, a de-identified image of the electronic medical record (EMR), containing more than 20 years of records on 1.7 million subjects. We identified 63,177 unique subjects with an ECG that was read as "normal" by the reviewing cardiologist. Using combinations of natural language processing and laboratory and billing code queries, we identified a subset of 32,949 subjects without cardiovascular disease, interfering medications, or abnormal electrolytes. The ethnic makeup was 77% Caucasian, 13% African American, 1% Hispanic, 1% Asian, and 8% unknown.
The range that included 95% of normal PR intervals was 125-196 ms, QRS 69-103 ms, QT interval corrected with Bazett formula 365-458 ms, and heart rate 54-96 bpm. Linear regression modeling of patient characteristic effects reproduced known age and gender effects and identified novel associations with race, body mass index, and type 2 diabetes mellitus. A web-based application for patient-specific normal ranges is available online at http://biostat.mc.vanderbilt.edu/ECGPredictionInterval.
Analysis of a large set of EMR-derived normal ECGs reproduced known associations, found new relationships, and established patient-specific normal ranges. Such knowledge informs clinical and genetic research and may improve understanding of normal cardiac physiology.
传统的心电图（ECG）参考范围是从社区或临床试验人群的研究中得出的。在向医疗保健系统就诊的大量人群中，心电图参数的分布尚未得到研究。
本研究的目的是确定年龄、种族、性别、身高、体重指数和 2 型糖尿病对向医疗保健系统就诊人群的正常心电图参数的贡献。
研究对象来自范德比尔特综合衍生品，这是电子病历（EMR）的一个去识别图像，包含超过 20 年的 170 万患者的记录。我们确定了 63177 名心电图由审查心脏病专家诊断为“正常”的独特患者。使用自然语言处理和实验室及计费代码查询的组合，我们确定了一个子集，其中 32949 名患者没有心血管疾病、干扰药物或电解质异常。种族构成为 77%白种人、13%非裔美国人、1%西班牙裔、1%亚洲人和 8%未知。
包括 95%正常 PR 间隔的范围为 125-196ms，QRS 为 69-103ms，Bazett 公式校正的 QT 间隔为 365-458ms，心率为 54-96bpm。患者特征影响的线性回归模型再现了已知的年龄和性别影响，并确定了与种族、体重指数和 2 型糖尿病的新关联。一个基于网络的患者特定正常范围的应用程序可在 http://biostat.mc.vanderbilt.edu/ECGPredictionInterval 在线获得。
对一组大型 EMR 衍生正常心电图的分析再现了已知的关联，发现了新的关系，并建立了患者特定的正常范围。这种知识为临床和遗传研究提供了信息，并可能有助于更好地理解正常心脏生理学。
