A new electrocardiogram algorithm to differentiate the type of paraxysmal supraventricular tachycardia
Objective:Accurately identifying types of paroxysmal supraventricular tachycardia(PSVT)through electrocardiogram(ECG)remains challenging.This study aims to develop a new ECG diagnostic algorithm that integrates multiple ECG characteristics observed during episodes and to evaluate its efficacy in distinguishing PSVT types.Methods:A new four-step ECG diagnostic algorithm was established through preliminary research and literature review.A total of 505 patients with PSVT hospitalized at the Department of Cardiology,Second Xiangya Hospital of Central South University from January 2021 to December 2023 were selected.Two cardiologists analyzed the ECGs according to this new four-step diagnostic algorithm and classified the PSVT types.Results:The algorithm correctly identified PSVT types in 454 ECGs,with an accuracy rate of 89.9%.The sensitivity and specificity of identifying atrioventricular node reentrant tachycardia(AVNRT)were 89.6%and 90.5%,respectively,with a positive predictive value of 95.0%and a negative predictive value of 81.4%.The area under the receiver operating characteristic(ROC)curve was 0.90.The diagnostic consistency between the 2 cardiologists was 98.6%.Conclusion:This new ECG algorithm provides high sensitivity and specificity for differentiating AVNRT from atrioventricular reciprocating tachycardia(AVRT),making it an effective method for ECG-based differentiation of AVNRT and AVRT.