Computerized electrocardiogram data transformation enables effective algorithmic differentiation of wide QRS complex tachycardias.

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

SUBMITTER: Kashou AH 

PROVIDER: S-EPMC9833371 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature