A mathematical model for derivation of Elevated-Electrode-Placement Electrocardiogram (EEP-ECG) leads from a standard 12-lead electrocardiogram.

Abstract

Background: Placement of right precordial leads in higher intercostal spaces (EEP-ECG) improves the detection of Brugada Syndrome (BrS). Given the potential difficulty of lead placement and the transient nature of BrS ECG patterns, we developed a model to predict EEP-ECG from a standard 12‑lead ECG.

Objective: To create and validate a model that derives EEP-ECG leads from a standard 12‑lead ECG.

Methods: We recorded 16 channel ECGs (12 standard leads plus 4 elevated leads in the 2nd and 3rd intercostal spaces) using two identical ECG recorders. A linear regression model was developed from the ECG data in the training group. This model was subsequently used to predict EEP-ECG in the validation group. Accuracy of the model was evaluated by comparing the derived leads to the actually recorded leads. Comparison was done using correlation coefficients and visual assessment by two cardiologists on a scale of 1-3.

Results: The study included 42 participants (22 in the training group, 20 in the validation group), including 8 BrS patients. The model showed strong correlation (r > 0.85) between actual and predicted leads for 76 of 80 leads. Visual assessment yielded an average score of 2.44 ± 0.68. The model has been made available as an online tool for automatic derivation of EEP-ECG from a standard 12‑lead ECG (http://eep-ecg.in/).

Conclusion: We developed a linear model to derive elevated ECG leads from standard 12‑lead ECGs. The model predicts EEP-ECG with reasonable accuracy. This model can be useful in diagnosing BrS in new or existing ECGs.