A new study published in the Journal of Electrocardiology this month by Washington University Physician Adam May shows that an automated tool for WCT differentiation can improve the accuracy of the physician interpreting ECGs. In the study, it was shown that using an algorithm designed to differentiate between ventricular tachycardia (VT) and supraventricular wide complex tachycardia (SWCT) in ECGs called the VT Prediction Model improved both accuracy and confidence of diagnosis among physicians who used it over a four-day period.
Using this kind of technology to improve diagnostic accuracy can have a positive impact on results for WCT patients, reducing the occurrence of application of harmful medical treatments and long-term effects of misdiagnosis.
Read the full paper here.