Background
Traditional electrocardiographic 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.
Objective
The objective of this study is to define the contribution of age, race, gender, height, body mass index (BMI), and type 2 diabetes mellitus (T2D) to normal electrocardiographic parameters in a population presenting to a healthcare system.
Methods
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 read as ‘normal’ by the reviewing cardiologist. Using combinations of natural language processing, 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.
Results
The range that included 95% of normal PR intervals was 125–196 msec; QRS 69–103 msec; QTcB 365–458 msec; and HR 54–96 bpm. Linear regression modeling of patient characteristic effects reproduced known age and gender effects and identified novel associations with race, BMI, and T2D. A web-based application for patient-specific normal ranges has been made available online at http://biostat.mc.vanderbilt.edu/ECGPredictionInterval.
Conclusion
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.