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.

Lau EW ，Ng GA 《PACE-PACING AND CLINICAL ELECTROPHYSIOLOGY》

Comparison of the performance of three diagnostic algorithms for regular broad complex tachycardia in practical application.

The authors previously proposed a Bayesian approach to the electrocardiographic diagnosis of regular broad complex tachycardia (BCT), which can be due to VT or supraventricular tachycardia with aberrant conduction (SVTAC). They also published an account comparing the theoretical merits in the design of two of the most commonly used diagnostic algorithms for the same purpose, those of Brugada et al. and Griffith et al. In this study, a direct head-to-head comparison was performed on the practical performances of the three algorithms in this study. A set of 111 ECGs showing regular BCT (77 VT, 34 SVTAC) whose diagnoses were confirmed by electrophysiological study was shown to five internists in general medicine at a district general hospital. The observers were asked to comment on whether the ECG criteria in the three algorithms tested were fulfilled or not, and a computer program then derived the corresponding diagnoses. The sensitivity and specificity for VT achieved by the Brugada algorithm were 92% and 44%, 92% and 44% by the Griffith algorithm, and 97% and 56% by the Bayesian algorithm. The Bayesian algorithm achieved a higher sensitivity and specificity than the other two algorithms, but the differences are not statistically significant (P = 0.6583 and P = 0.5334, respectively). The Brugada, Griffith, and Bayesian algorithms show comparable performances in terms of overall sensitivity and specificity when tested in practice. Of the three algorithms, the Griffith algorithm excels in simplicity and is the easiest to implement in practice. The Bayesian algorithm achieved slightly higher values for sensitivity and specificity than the Brugada and Griffith algorithms but may be more suitable for automated computer-aided diagnosis of ECG due to its complexity.

Lau EW ，Ng GA 《PACE-PACING AND CLINICAL ELECTROPHYSIOLOGY》

Comparison of five electrocardiographic methods for differentiation of wide QRS-complex tachycardias.

To compare the sensitivity (SN), specificity (SP), and diagnostic accuracy (ACC) for ventricular tachycardia (VT) diagnosis of five electrocardiographic methods for wide QRS-complex tachycardia (WCT) differentiation, specifically the Brugada, Bayesian, Griffith, and aVR algorithms, and the lead II R-wave-peak-time (RWPT) criterion. We retrospectively analysed 260 WCTs from 204 patients with proven diagnoses. The SN, SP, ACC, and likelihood ratios (LRs) were determined for the five methods. Of the 260 tracings, there were 159 VTs and 101 supraventricular tachycardias. All five methods were found to have a similar ACC although the RWPT had a lower ACC than the Brugada algorithm (68.8 vs. 77.5%, P = 0.04). The RWPT had lower (60%) SN than the Brugada (89.0%), Griffith (94.2%), and Bayesian (89%) algorithms (P < 0.001). The Griffith algorithm showed lower (39.8%) SP than the RWPT (82.7%), Brugada (59.2%), and Bayesian (52.0%) algorithms (P< 0.05). The positive LRs for a VT diagnosis for the RWPT criterion and the Brugada, Bayesian, aVR, and Griffith algorithms were 3.46, 2.18, 1.86, 1.67, and 1.56, respectively. The present study is the first independent 'head-to-head' comparison of several WCT differentiation methods. We found that all five algorithms/criteria had rather moderate ACC, and that the newer methods were not more accurate than the classic Brugada algorithm. However, the algorithms/criteria differed significantly in terms of SN, SP, and LR, suggesting that the value of a diagnosis may differ depending on the method used.

Jastrzebski M ，Kukla P ，Czarnecka D ，Kawecka-Jaszcz K ... -  《-》

The Bayesian approach improves the electrocardiographic diagnosis of broad complex tachycardia.

Despite numerous attempts at devising algorithms for diagnosing broad complex tachycardia (BCT) on the basis of the electrocardiogram (ECG), misdiagnosis is still common. The reason for this may lie with difficulty in implementing existent algorithms in practice, due to imperfect ascertainment of ECG features within them. An attempt was made to approach the problem afresh with the Bayesian inference by the construction of a diagnostic algorithm centered around the likelihood ratio (LR). Previously studied ECG features most effective in discriminating ventricular tachycardia (VT) from supraventricular tachycardia with aberrant conduction (SVTAC), according to their LR values, were selected for inclusion into a Bayesian diagnostic algorithm. A test set of 244 BCT ECGs was assembled and shown to three independent observers who were blinded to the diagnoses made at electrophysiological study. Their diagnostic accuracy by the Bayesian algorithm was compared against that by clinical judgement with the diagnoses from EPS as the criterial standard. Clinical judgement correctly diagnosed 35% of SVTAC, 85% of VT, and 47% of fascicular tachycardia. In comparison, by the Bayesian algorithm devised, 52% of SVTAC, 95% of VT, and 97% of fascicular tachycardia were correctly diagnosed. The Bayesian algorithm devised has proved to be superior to the clinical judgement of the observers who participated in this study, and theoretically will obviate the problem of imperfect ascertainment of ECG features. Hence, it holds the promise for being an effective tool for routine use in clinical practice.

Lau EW ，Pathamanathan RK ，Ng GA ，Cooper J ，Skehan JD ，Griffith MJ ... -  《PACE-PACING AND CLINICAL ELECTROPHYSIOLOGY》

[Value of aVR lead four steps algorithm on differential diagnosis of wide QRS complex tachycardia].

The aVR lead four steps is a new algorithm for differential diagnosis of wide QRS complex tachycardia (WCT). The study explores the clinical value of this new algorithm on differential diagnosis of WCT. Application of aVR lead four steps to analysis the electrocardiogram of patients with WCT proved by electrophysiological study. Every step's accuracy rate, sensitivity and specificity to differential diagnosis of ventricular tachycardia (VT) were calculated. The first step diagnosed VT according to presence of an initial R wave in the aVR lead. The second step diagnosed VT according to width of an initial r or q wave > 40 ms in the aVR lead. The third step diagnosed VT according to notching on the initial downstroke of a predominantly negative QRS complex in the aVR lead. The fourth step diagnosis VT according to ventricular activation-velocity ratio (Vi/Vt) in the aVR lead, Vi/Vt ≤ 1 suggested VT. Results derived from aVR lead four steps algorithm were compared with results derived from Brugada and Vereckei four steps algorithm. A total of 113 patients with WCT were analyzed (31 supraventricular tachycardia, SVT and 82 ventricular tachycardia, VT). The accuracy rate of differential diagnosis VT is 91.2%, sensitivity is 90.2% and specificity is 77.4%. The accuracy and sensitivity of the aVR lead four steps algorithm for differential diagnosis of WCT were superior to the Brugada Vereckei four steps algorithm (P < 0.05). The specificity of the Vereckei four steps algorithm was superior to aVR lead and Brugada four steps algorithm (P < 0.05), while the specificity of the aVR lead four steps algorithm was similar as Brugada four steps algorithm (P > 0.05). The aVR lead four steps algorithm is associated with excellent accuracy rate, sensitivity for differential diagnosis of WCT. This algorithm is simple and could be easily learned and applied by physician.

Lin T ，Ma YT ，Muhu Y ，Tang BP ，Hou YM ，Zhang YY ... -  《-》