Comparison of Two Diagnostic Algorithms for Regular Broad Complex Tachycardia by Decision Theory Analysis

Sensitivity and specificity are two inversely related properties of a diagnostic test and it is often practically infeasible to secure a high value for both simultaneously. Decision theory analysis shows that the utility of a diagnostic test depends not only on its sensitivity and specificity but also on the prevalence of the intended target disorder: when prevalence is low, a high specificity is more important than a high sensitivity, whereas when prevalence is high, a high sensitivity is more important than a high specificity. The significance of this principle is illustrated by two popular algorithms for the electrocardiographic diagnosis of regular broad complex tachycardia (BCT), of which the two main differential diagnoses are ventricular tachycardia (VT) and supraventricular tachycardia with aberrant conduction (SVTAG). Brugada et al. focused on criteria highly specific for VT and used them to build a four-step algorithm. In contrast, Griffith et al. first selected criteria highly sensitive for VT and then criteria highly specific for VT to build a simple two-step algorithm. It can be objectively demonstrated that the Griffith algorithm is more efficient and effective than the Brugada algorithm in terms of clinching the final diagnosis and improving overall diagnostic accuracy. The main reason for this is that VT is more common than SVTAC as the cause of regular BCT, and the Griffith algorithm adhered to the aforementioned principle governing the choice between sensitivity and specificity according to prevalence in its design. The Griffith algorithm also embodies an additional important principle, namely, it is easier and more efficient to choose alternatively between criteria highly specific and highly sensitive for the intended target disorder than concentrating on just one or the other in designing a multiple-step sequential diagnostic algorithm.