Differential Diagnosis of Wide QRS Complex Arrhythmias Using a Novel Slow Conduction Index Algorithm.

The study investigates the utility of a slow conduction index for differential diagnosis of wide QRS complex arrhythmias with left bundle branch block (LBBB) morphology across all 12 ECG leads, aiming to improve diagnostic accuracy without reliance on identifying RS complex types based on Brugada algorithm. Including 280 single premature wide QRS complexes from 28 randomly selected patients, the research employs ROC analysis to assess the diagnostic value of the slow conduction index. Results indicate the highest sensitivity and specificity values in leads aVL, V2, aVF, V5, and III, with statistically significant findings $(p < 0.001)$ across all leads. The conclusion underscores the potential of using the slow conduction index across all ECG leads for diagnosing wide QRS complex arrhythmias with LBBB morphology, proposing a more universal and accurate approach to arrhythmia classification.