Computerized electrocardiogram data transformation enables effective algorithmic differentiation of wide QRS complex tachycardias. Issue 1 (21st November 2022)

• Record Type: Journal Article
• Authors: Kashou, Anthony H.; LoCoco, Sarah; Shaikh, Preet A.; Katbamna, Bhavesh B.; Sehrawat, Ojasav; Cooper, Daniel H.; Sodhi, Sandeep S.; Cuculich, Phillip S.; Gleva, Marye J.; Deych, Elena; Zhou, Ruiwen; Liu, Lei; Deshmukh, Abhishek J.; Asirvatham, Samuel J.; Noseworthy, Peter A.; DeSimone, Christopher V.; May, Adam M.
• Is Part Of: Annals of noninvasive electrocardiology. Volume 28:Issue 1(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-11-21
• Subjects: ventricular tachycardia/fibrillation < basic -- non‐invasive techniques—electrocardiography < clinical; Electrocardiography -- Periodicals; Arrhythmia -- Periodicals; 616.1207547
• DOI: 10.1111/anec.13018
• Languages: English
• ISSNs: 1082-720X

Abstract

Abstract: Background: Accurate automated wide QRS complex tachycardia (WCT) differentiation into ventricular tachycardia (VT) and supraventricular wide complex tachycardia (SWCT) can be accomplished using calculations derived from computerized electrocardiogram (ECG) data of paired WCT and baseline ECGs. Objective: Develop and trial novel WCT differentiation approaches for patients with and without a corresponding baseline ECG. Methods: We developed and trialed WCT differentiation models comprised of novel and previously described parameters derived from WCT and baseline ECG data. In Part 1, a derivation cohort was used to evaluate five different classification models: logistic regression (LR), artificial neural network (ANN), Random Forests [RF], support vector machine (SVM), and ensemble learning (EL). In Part 2, a separate validation cohort was used to prospectively evaluate the performance of two LR models using parameters generated from the WCT ECG alone (Solo Model) and paired WCT and baseline ECGs (Paired Model). Results: Of the 421 patients of the derivation cohort (Part 1), a favorable area under the receiver operating characteristic curve (AUC) by all modeling subtypes: LR (0.96), ANN (0.96), RF (0.96), SVM (0.96), and EL (0.97). Of the 235 patients of the validation cohort (Part 2), the Solo Model and Paired Model achieved a favorable AUC for 103 patients with (Solo Model 0.87; Paired Model 0.95) and 132 patients without (Solo Model 0.84; Paired Model 0.95) a corroborating electrophysiology procedure or intracardiac device recording. Conclusion: Accurate WCT differentiation may be accomplished using computerized data of (i) the WCT ECG alone and (ii) paired WCT and baseline ECGs. Abstract : Accurate automatic wide QRS complex tachycardia (WCT) differentiation may be accomplished through the use of novel parameters derived from computerized data of the (i) WCT electrocardiogram (ECG) alone and (ii) paired WCT and baseline ECGs. Once automated WCT differentiation models are integrated into commercially available computerized ECG interpretation software, they may help clinicians distinguish ventricular tachycardia and supraventricular wide complex tachycardia accurately.