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》

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》

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》

Failure to agree on the electrocardiographic diagnosis of ventricular tachycardia.

To determine the extent of interobserver agreement in the ECG diagnosis of ventricular tachycardia (VT) by using a four-step algorithm and three observers. Simulated emergency department setting from records of an urban university teaching hospital. All ECGs taken in the ED during a 2-year period that showed a QRS duration of more than 120 msec and a heart rate faster than 110 beats per minute were reviewed. ECGs were categorized as demonstrating sinus rhythm (SR), irregular broad-complex tachycardia (I-BCT), or regular broad-complex tachycardia (BCT). Copies of the BCT ECGs and short clinical histories were given to each of three emergency physicians, who used a published, four-step algorithm (the Brugada algorithm) to categorize the BCT ECGs as indicating VT, indicating supraventricular tachycardia with aberrancy (SVT-A), or indeterminate. Interobserver agreement was assessed with the K-statistic. The records contained 178 ECGs, 88 of which were SR, 63 I-BCT, and 27 BCT. The 27 BCT ECGs were selected for review. The emergency physicians disagreed with each other 22% of the time in differentiating VT from SVT-A (K = .58). Application of the algorithm to actual clinical practice in the ED would probably result in the misdiagnosis of a substantial minority of patients having BCT, with potentially serious adverse consequences.

Herbert ME ，Votey SR ，Morgan MT ，Cameron P ，Dziukas L ... -  《ANNALS OF EMERGENCY MEDICINE》

Differential diagnosis of wide QRS tachycardias: comparison of two electrocardiographic algorithms.

This study's aim is to compare the ability of two ECG criteria to differentiate ventricular (VT) from supraventricular tachycardia (SVT): Brugada et al. [horizontal plane (HP) leads] and Vereckei et al. [frontal plane (FP), specifically aVR lead], having electrophysiological study (EPS) as gold standard. After comparing, suggestions for better diagnosis of wide QRS-complex tachycardia (WCT) in emergency situations were made. Fifty-one consecutive patients with 12-lead ECG registered during EPS-induced regular WCT were selected. Each ECG was split into two parts: HP (V1-V6) and FP (D1-D3, aVR, aVL, and aVF), randomly distributed to three observers, blinded for EPS diagnosis and complementary ECG plane, resulting in total 306 ECG analyses. Observers followed the four steps of both algorithms, counting time-to-diagnosis. Global sensitivity, specificity, percentage of incorrect diagnoses, and step-by-step positive/negative likelihood ratios (+LR and -LR) were calculated. Kaplan-Meier curve was plotted for final time-to-diagnosis. Inter-observer agreement was assessed with kappa-statistic. Global sensitivity was similarly high in FP and HP algorithms (89.2 vs. 90.1%), and incorrect classifications were 27.4 vs. 24.7%. Forty-eight correct analyses by Vereckei criteria took 9.13 s to diagnose VT in the first step, showing that first step was fast, with high +LR, generating nearly conclusive pre- (72.6%) to post-test (98.0%) changes for VT probability. Both algorithms as a whole are similar for diagnosis of WTC; however, the first step of Vereckei (initial R in aVR) is a simple, reproducible, accurate, and fast tool to use. The negativity of this step requires a 'holistic' approach to distinguish VT from SVT.

Kaiser E ，Darrieux FC ，Barbosa SA ，Grinberg R ，Assis-Carmo A ，Sousa JC ，Hachul D ，Pisani CF ，Kosa E ，Pastore CA ，Scanavacca MI ... -  《-》