Modulators of normal electrocardiographic intervals identified in a large electronic medical record

Abstract

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.

An analysis of QTc prolongation with atypical antipsychotic medications and selective serotonin reuptake inhibitors using a large ECG record database

“…Additionally, this study analyzed Korean population data and demonstrated sex-and age-related differences in QTcB intervals as reported previously. 11,16 The ECGs from the healthy control group showed that female subjects had a 6.3-ms longer QT but a 30.8-ms shorter RR than males, resulting in a 13.1-ms longer QTcB than male subjects. The mean QTcB interval observed in females was significantly longer than that observed in males (p < 0.001).…”

“…1, 9,10 In addition, we found that previous ECG analysis results, including mean differences in QTcB intervals according to sex-and age-related QTcB increases reported in other ethnic groups, can be extended to the current study with ECG recordings from the Korean population. 11,16 We selected cilostazol for the positive control and diazepam for the negative control because of the amount of available data and length of drug use. Although cilostazol is not a psychotropic drug, its length of use was more relevant to our study and more data were available for the analysis than for any other psychotropic drug categorized as having a known risk of TdP.…”

“…11,16 Because the number of patients with electrolyte imbalance for each study drugs was too small to perform a statistical analysis, the electrolyte level was not included as a covariate in the OR analysis. Rather, linear regression analysis comparing the QTcB interval and electrolyte levels was performed.…”

Simplicity is the ultimate sophistication. PR electrocardiographic intervals for smart forecasting of decline in renal function

“…Indeed, the suggestion of a concealed shared mechanism behind the commonly recognized risk factors for cardiovascular and renal diseases is implicit in these findings. Although the Authors acknowledge the lack of sodium, potassium and calcium serological assays among the limitations of their study, in my view these factors are not in any case able to significantly affect iPR in normal subjects [7].…”

“…Indeed, thus far the relative contributions of common variants of modest effect, and rare variants of greater effects, in terms of the risk of CHD or response to drugs remain unclear [8]. It is refreshing then that, despite its apparently simplicity, the use of recorded ECG intervals [1], which are mainly modulated by heart rate [2,7] and are not subject to arbitrary interpretation, appear to indicate a fruitful area of research.…”