Wide complex tachycardia discrimination tool improves physicians' diagnostic accuracy

Elsevier

Available online 2 August 2022

Journal of ElectrocardiologyHighlights•

Management decisions reply on accurate wide complex tachycardia discrimination.

A shortcoming of manual ECG approaches is complete reliance on the ECG interpreter.

Automated differentiation methods remove the reliance on ECG interpreter competency.

Automated differentiation methods improve physician accuracy and confidence.

AbstractBackground

Timely and accurate discrimination of wide complex tachycardias (WCTs) into ventricular tachycardia (VT) or supraventricular WCT (SWCT) is critically important. Previously we developed and validated an automated VT Prediction Model that provides a VT probability estimate using the paired WCT and baseline 12-lead ECGs. Whether this model improves physicians' diagnostic accuracy has not been evaluated.

Objective

We sought to determine whether the VT Prediction Model improves physicians' WCT differentiation accuracy.

Methods

Over four consecutive days, nine physicians independently interpreted fifty WCT ECGs (25 VTs and 25 SWCTs confirmed by electrophysiological study) as either VT or SWCT. Day 1 used the WCT ECG only, Day 2 used the WCT and baseline ECG, Day 3 used the WCT ECG and the VT Prediction Model's estimation of VT probability, and Day 4 used the WCT ECG, baseline ECG, and the VT Prediction Model's estimation of VT probability.

Results

Inclusion of the VT Prediction Model data increased diagnostic accuracy versus the WCT ECG alone (Day 3: 84.2% vs. Day 1: 68.7%, p 0.009) and WCT and baseline ECGs together (Day 3: 84.2% vs. Day 2: 76.4%, p 0.003). There was no further improvement of accuracy with addition of the baseline ECG comparison to the VT Prediction Model (Day 3: 84.2% vs. Day 4: 84.0%, p 0.928). Overall sensitivity (Day 3: 78.2% vs. Day 1: 67.6%, p 0.005) and specificity (Day 3: 90.2% vs. Day 1: 69.8%, p 0.016) for VT were superior after the addition of the VT Prediction Model.

Conclusion

The VT Prediction Model improves physician ECG diagnostic accuracy for discriminating WCTs.

Keywords

Wide complex tachycardias

Ventricular tachycardia

Supraventricular wide complex tachycardia

Electrocardiogram

ECG interpretation

ECG competency

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© 2022 Published by Elsevier Inc.

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