Brugada Algorithm Research Articles

Diagnostic accuracy of different ECG-based algorithms in wide QRS complex tachycardia: a systematic review and meta-analysis

ObjectiveSeveral ECG-based algorithms have been proposed to enhance the effectiveness of distinguishing Wide QRS complex tachycardia (WCT), but a comprehensive comparison of their accuracy is still lacking. This meta-analysis aimed...

Abstract 13915: Man vs. Machine: A Direct Comparison of the Diagnostic Efficacy of Novel Automated WCT Differentiation to Traditional Manual ECG Interpretation Approaches

BACKGROUND: Differentiation of wide QRS complex tachycardias (WCTs) into ventricular tachycardia (VT) and supraventricular wide QRS tachycardia (SWCT) through 12-lead electrocardiogram (ECG) interpretation is one of the most critical yet challenging tasks in clinical practice. Recent research highlights novel automated methods that successfully diagnose WCTs. We sought to directly compare the diagnostic efficacy of these novel automated WCT differentiation methods (i.e., WCT Formula, VT Prediction Model, and WCT Formula II) to traditional ECG interpretation approaches (i.e., Brugada and Vereckei aVR algorithms). METHODS: A collection of paired WCT and baselined ECGs were retrospectively analyzed. Next, an electrophysiologist blindly and prospectively applied the Brugada and Vereckei aVR algorithms. Separately, computerized measurements were used to apply the three automated WCT differentiation methods. The diagnostic performance of each method was then evaluated. RESULTS: 213 WCTs (111 VT and 102 SWCT) from 105 patients were analyzed. The WCT Formula demonstrated superior overall accuracy (84.7% vs. 64.8%), specificity (86.2% vs. 35.3%), positive predictive value (PPV) (85.7% vs. 60.7%), and positive (+) likelihood ratio (LR) (6.06 vs. 1.42) compared to Vereckei aVR algorithm. Similarly, the WCT Formula attained higher specificity (86.2% vs. 61.8%), PPV (85.7% vs. 71.9%), and (+) LR (6.06 vs. 2.36) than the Brugada algorithm. The WCT Formula II demonstrated superior overall accuracy (89.2% vs. 64.8%), specificity (84.3 % vs. 35.3%), PPV (86.7% vs. 60.7%), and positive (+) LR (5.97 vs.1.42) compared to Vereckei aVR algorithm as well as higher specificity (84.3 % vs. 61.8 %), PPV (86.7% vs. 71.9%), and (+) LR (5.97 vs. 2.36) than the Brugada algorithm. The VT prediction model yielded superior specificity (79.4% vs. 35.3%), PPV (79.8 vs. 60.7%) and (+) LR (3.63 vs.1.42) compared to the Vereckei aVR algorithm but did not demonstrate superior diagnostic performance to the Brugada algorithm. CONCLUSIONS: Novel automated WCT differentiation methods achieved similar or superior diagnostic performance metrics compared to traditional ECG interpretation approaches.

Simplified Integrated Clinical and Electrocardiographic Algorithm for Differentiation of Wide QRS Complex Tachycardia: The Basel Algorithm.

Prompt differential diagnosis of wide QRS complex tachycardia (WCT) is crucial to patient management. However, distinguishing ventricular tachycardia (VT) from supraventricular tachycardia (SVT) with wide QRS complexes remains problematic, especially for nonelectrophysiologists. This study aimed to develop a simple-to-use algorithm with integration of clinical and electrocardiographic (ECG) parameters for the differential diagnosis of WCT. The 12-lead ECGs of 206 monomorphic WCTs (153 VT, 53 SVT) with electrophysiology-confirmed diagnoses were analyzed. In the novel Basel algorithm, VT was diagnosed in the presence of at least 2 of the following criteria: 1)clinical high risk features; 2) lead II time to first peak >40ms; and 3) lead aVR time to first peak >40ms. The algorithm was externally validated in 203 consecutive WCT cases (151 VT, 52 SVT). Its' diagnostic performance and clinical applicability were compared with those of the Brugada and Vereckei algorithms. The Basel algorithm showed a sensitivity, specificity, and accuracy of 92%, 89%, and 91%, respectively, in the derivation cohort and 93%, 90%, and 93%, respectively, in the validation cohort. There were no significant differences in the performance characteristics between the 3 algorithms. The evaluation of the clinical applicability of theBasel algorithm showed similar diagnostic accuracy compared with the Brugada algorithm (80% vs 81%; P=1.00), but superiority compared with the Vereckei algorithm (72%; P=0.03). The Basel algorithm, however, enabled a faster diagnosis (median 36 seconds vs 105 seconds for the Brugada algorithm [P=0.002] and 50 seconds for the Vereckei algorithm [P=0.02]). The novel Basel algorithm based on simple clinical and ECG criteria allows for a rapid and accurate differential diagnosis of WCT.

Validation of a Simple Electrocardiographic Algorithm for Detection of Ventricular Tachycardia.

ResumoFundamentoO diagnóstico diferencial de taquicardia de QRS largo, entre taquicardia ventricular (TV) ou taquicardia supraventricular com condução aberrante (TSV-A) é algumas vezes difícil de ser feito na sala de emergência.ObjetivoAvaliar a acurácia de um algoritmo novo e simples para a detecção de TV no eletrocardiograma (ECG) em pacientes com taquicardia de QRS largo.MétodosECGs de 12 derivações para detecção de taquicardia de QRS largo foram obtidos prospectivamente de 120 pacientes durante estudo eletrofisiológico. Seis médicos com diferentes experiências analisaram os ECGs, e fizeram o diagnóstico com base no algoritmo D12V16, que envolve a análise da polaridade predominante do complexo QRS nas derivações I, II, V1 e V6. O diagnóstico foi comparado com os obtidos pelo algoritmo tradicional de Brugada e pelo estudo eletrofisiológico, o qual é considerado padrão ouro. Adotou-se um nível de significância de 5% (p<0,05) nas análises estatísticas.ResultadosDe acordo com o estudo eletrofisiológico, 82 ECGs eram de TV e 38 de TSV-A. Doenças cardíacas estruturais estavam presentes em 71 (86,6%) dos pacientes com TV e em oito (21,1%) com TSV-A. O algoritmo de Brugada teve uma maior sensibilidade global (87,2%), enquanto o algoritmo D12V16 apresentou maior especificidade global (85,1%) para TV. Tanto o algoritmo D12V16 como o de Brugada apresentou um alto valor preditivo positivo (90,9% vs. 85,8%, respectivamente) e acurácia similar (73,8% vs. 81,4%, respectivamente) para o diagnóstico de TV. Nos avaliadores experientes, a acurácia foi maior utilizando o algoritmo de Brugada que o algoritmo D12V16, mas a acurácia dos dois algoritmos foi similar segundo os avaliadores menos experientes.ConclusãoO algoritmo simplificado pode ser um método útil para reconhecer TV no ECG, principalmente para médicos menos experientes. (Arq Bras Cardiol. 2021; [online].ahead print, PP.0-0)

Right bundle branch block–type wide QRS complex tachycardia with a reversed R/S complex in lead V6: Development and validation of electrocardiographic differentiation criteria

Differentiation of supraventricular tachycardia (SVT) with a right bundle branch block (RBBB) pattern from ventricular tachycardia (VT) is difficult, particularly when the R/S ratio in lead V6 is below 1.0. We sought to investigate the electrocardiographic criteria for distinguishing between these arrhythmias. We investigated electrocardiographic parameters from 111 consecutive patients who had RBBB pattern wide QRS complex tachycardia with a reversed R/S ratio in lead V6 (72 VTs, 39 SVTs). Diagnostic criteria from the previous algorithms were compared with our new criterion, the RS/QRS ratio, which was defined as the ratio of the interval from the onset of the QRS complex to the nadir of the S wave, divided by the QRS width in lead V6. The RS/QRS ratio was further tested in a prospective population (31 fascicular VTs, 29 SVTs). The diagnostic accuracy of previous criteria (Brugada algorithm, Vereckei algorithm, and R-wave peak time criterion) was only modest. However, the RS/QRS ratio in lead V6 was significantly lower in SVT than in VT (0.36 ± 0.04 vs 0.50 ± 0.08; P < .001). A cutoff value of the RS/QRS ratio >0.41 differentiated VT from SVT with a high diagnostic accuracy (sensitivity 97.2%; specificity 89.7%). When tested in a prospective population with fascicular VT, the diagnostic accuracy of the criteria was maintained (sensitivity 90.3%; specificity 86.2%). The RS/QRS ratio >0.41 in lead V6 is a simple and reliable index for distinguishing VT from SVT in RBBB pattern wide QRS complex tachycardia with a reversed R/S complex in lead V6. This criterion was particularly useful for the differential diagnosis of fascicular VT from RBBB pattern SVT.

Utility of Inferior Lead Q-waveforms in diagnosing Ventricular Tachycardia.

Background:Electrocardiogram (ECG) differentiation of wide complex tachycardia (WCT) into ventricular tachycardia (VT) and supraventricular tachycardia with aberration (SVT-A) is often challenging.Objective:To determine if the presence of Q-waveforms (QS, Qr, QRs) in the inferior leads (II, III, aVF) can differentiate VT from SVT-A in a WCT compared to Brugada algorithm. We studied 2 inferior lead criteria namely QWC-A where all the inferior leads had a similar Q wave pattern and QWC-B where only lead aVF had a Q-waveform.Methods:A total of 181 consecutive cases of WCT were identified, digitally separated into precordial leads and inferior leads and independently reviewed by 2 electrophysiologists. An electrocardiographic diagnosis of VT or SVT-A was assigned based on Brugada and inferior lead algorithms. Results were compared to the final clinical diagnosis.Results:VT was the final clinical diagnosis in 24.9% of ECG cohort (45/181); 75.1% (136/181) were SVT-A. QWC-A and QWC-B had a high specificity (93.3% and 82.8%) and accuracy (78.2% and 71.0%), but low sensitivity (33.3% and 35.6%) in differentiating VT from SVT-A. The Brugada algorithm yielded a sensitivity of 82.2% and specificity of 68.4%. Area under the curve in ROC analysis was highest with Brugada algorithm (0.75, 95% CI 0.69-0.81) followed by QWC-A (0.63, 95% CI 0.56-0.70) and QWC-B (0.59, 95% CI 0.52-0.67).Conclusion:QWC-A and QWC-B criteria had poor sensitivity but high specificity in diagnosing VT in patients presenting with WCT. Further research combining this simple criterion with other newer diagnostic algorithms can potentially improve the accuracy of the overall diagnostic algorithm.

Value of ventricular tachycardia score in diagnosing pre-excited tachycardia

To investigate the value of ventricular tachycardia (VT) score in diagnosing pre-excited tachycardia. Methods: Twelve-lead electrocardiograph results were obtained from 30 patients at pre-excited tachycardia attacking stage who were diagnosed by electrophysiology. We scored pre-excitation tachycardia based on the VT score. To analyze the electrocardiogram of pre-excited tachycardia using 7 diagnostic indicators of the VT score and calculate the specificity of 7 diagnostic indicators and right superior axis (-90º to ±180º), the differences were compared among VT score of 2 points and brugada, Wellens, and Vereckei algorithms in diagnosing pre-excited tachycardia. According to the specificity of Vereckei, Wellens, and Brugada algorithms, and VT scores from low to high, their prediction value and differences were analyzed. Results: Single indicator such as atrioventricular (AV) dissociation or right superior axis (-90º to ±180º) showed the highest specificity (100%) for identifying pre-excited tachycardia. No patient with VT score was ≥3 points, and the specificity was 100%. The specificity of VT score of 2 point was higher than that of Brugada, Wellens, or Vereckei algorithms in the diagnosing pre-excited tachycardia (76.7% vs 50.0%, 23.3% or 20.0%, P<0.05). The specificity of Vereckei, Wellens, and Brugada algorithms and VT score were gradually increased after each of stepwise individually eliminated VT (20.0%, 40.0%, 66.7%, 83.3%, P<0.05). However, there was no significant difference in the specificity in the remaining false positive cases between the 4 methods and VT score. Conclusion: VT score ≥3 points can identify pre-excited tachycardia and VT with 100% specificity. VT score of 2 points cannot completely distinguish pre-excited tachycardia from VT, but specificity of VT score with 2 points is obviously higher than that of Brugada, Wellens, and Vereckei algorithms.

Use of aVR and Jastrzębski algorithms in the classification of wide complex tachycardia in dogs – a preliminary study

IntroductionVentricular rhythm disturbances are a common pathology in human and veterinary medicine. In humans, the algorithmic approach is used to differentiate wide QRS complex tachycardia. The most commonly used are the aVR and Brugada algorithms as well as the ventricular tachycardia (VT) score developed by Jastrzębski and coworkers. In veterinary medicine, no such algorithms are available and the only parameter used to describe VT abnormalities is the duration of the QRS complexes. The aim of this analysis was determining whether human medicine algorithms for VT are applicable in veterinary medicine to differentiate wide QRS complex tachycardia in dogs.Material and MethodsA retrospective analysis was performed on 11 dogs of both sexes and various breeds and age diagnosed with VT. The diagnosis was based on ambulatory ECG, further established based on the reaction to lidocaine or adenosine or an invasive electrophysiological study.ResultsOf the 11 tracings passed through the aVR algorithm, 10 met the VT criteria. The most common criterion was the Vi/Vt ratio (8 out of 11 tracings). Based on the VT score, seven out of eight dogs had a high probability of VT.ConclusionRetrospective analysis of ECGs by aVR and VT score indicates that the applied algorithms may be useful in differentiating wide QRS complex tachycardia as a quick, easy, and non-invasive alternative to cardiac electrophysiology.

Electrocardiogram algorithms used to differentiate wide complex tachycardias demonstrate diagnostic limitations when applied by non-cardiologists

AimsNon-cardiologists (NCs) are often responsible for the preliminary diagnosis and early management of patients presenting with ventricular tachycardia (VT) or supraventricular wide complex tachycardia (SWCT). At present, the Vereckei aVR and Brugada algorithms are the most widely recognized and frequently relied upon wide complex tachycardia (WCT) differentiation criteria by NCs. This study aimed to determine the diagnostic efficacy of the Vereckei aVR and Brugada algorithms when applied by NCs. MethodsIn a blinded fashion, three internal medicine residents prospectively interpreted WCTs using the Vereckei aVR and Brugada algorithms. The diagnostic performance of each method was evaluated according to their agreement with the correct rhythm diagnosis. ResultsTwo-hundred sixty-nine WCTs (160 VT, 109 SWCT) from 186 patients were independently interpreted by each participant (807 separate interpretations per algorithm). The aVR and Brugada algorithms accurately classified 546 out of 807 (67.7%) and 622 out of 807 (77.1%) interpreted WCTs, respectively. Overall sensitivity and specificity of the aVR algorithm for VT was 92.1% and 31.8%, respectively. Overall sensitivity and specificity of the Brugada algorithm for VT was 89.4% and 59.0%, respectively. Both algorithms yielded modestly favorable overall positive predictive values (aVR 66.5%; Brugada 76.2%) and negative predictive values (aVR 73.3%; Brugada 79.1%). ConclusionNon-cardiologist algorithm users correctly identified most “actual” VTs, but did not sufficiently revise VT probability to conclusively distinguish VT and SWCT. Newer WCT differentiation methods are needed to improve NC's ability to accurately differentiate WCTs.

The Value of Brugada Algorithm in the Differential Diagnosis of Broad QRS Complex Tachycardia: A Meta-Analysis

Background: The diagnosis precision of Brugada algorithm in discriminating between supraventricular tachycardia and ventricular tachycardia remains controversial. We aim to evaluate the diagnostic value of Brugada algorithm in broad complex tachycardia arrhythmia.Methods: Eligible studies were identified through searching PubMed, Embase, Web of Science databases, Wan Fang data resource, China National Knowledge Infrastructure prior to 5st January 2018. Studies were assessed for quality using the Quality Assessment for Studies of Diagnostic Accuracy, 2nd version (QUADAS-2). Pooled sensitivity and pooled specificity with 95% confidence interval (CI) were calculated using random-effects models. Summary receiver operator characteristic (SROC) curves and the area under curve (AUC) were performed.Results: A total of 13 studies including 1918 electrocardiogram (ECG) were enrolled in this meta-analysis. The pooled sensitivity and specificity were 0.92(95% CI: 0.88–0.95), and 0.71(95% CI: 0.57-0.82), respectively. The positive likelihood ratio was 3 (95% CI, 2.0–5.0) and the negative likelihood ratio was 0.11 (95% CI, 0.06–0.19). The summary Diagnostic Odds Ratio (DOR) was 29 (95% CI: 12–72). The AUC was 0.95. Meta-regression analysis showed that sample size, study type and region were not the major sources of heterogeneity, the publication date may account for heterogeneity.Conclusion: Brugada algorithm has excellent pooled sensitivity and moderate pooled specificity for discriminating SVT from VT. It deserves to be widely used as clinical diagnostic methods.

Specificity of wide QRS complex tachycardia criteria and algorithms in patients with ventricular preexcitation.

Despite substantial progress in the field of differentiation between ventricular tachycardia (VT) and supraventricular tachycardia (SVT) with wide QRS complexes, differentiation between VT and preexcited SVT remains largely unresolved due to significant overlap in QRS morphology. Our aim was to assess the specificities of various single ECG criteria and sets of criteria (Brugada algorithm, aVR algorithm, Steurer algorithm, and the VT score) for diagnosis of VT in a sizable cohort of patients with preexcitation. We performed a retrospective study of consecutive accessory pathway ablation procedures to identify preexcited tachycardias. Among 670 accessory pathway ablation procedures, 329 cases with good quality ECG with either bona fide preexcited SVT (n=30) or a surrogate preexcited SVT (fast paced atrial rhythm with full preexcitation, n=299) were identified. ECGs were analyzed with the use of wide QRS complex algorithms/criteria to determine specificities of these methods. The Steurer algorithm and VT score (≥3 points), with specificities of 97.6% and 96.1%, respectively, were significantly (p<.01) more specific for the diagnosis of VT than Brugada algorithm, aVR algorithm, and Pava criterion with specificities of 31%, 11.6%, and 57.1%, respectively. The first step of the Brugada algorithm and the first step of the aVR algorithm had also high specificities of 93.3% and 96.0%, respectively. There are sufficient electrocardiographical differences between VT and preexcited SVT to allow electrocardiographic differentiation. VT score, Steurer algorithm, and some single criteria do not overdiagnose VT in patients with preexcitation.

Clinical Significance of the Forsaken aVR in Evaluation of Tachyarrhythmias: A Reminder.

Mechanism of a regular, monomorphic Wide QRS Complex Tachycardia (WCT) is an important diagnostic challenge in day to day practice for the clinicians and affects further management and prognosis. Many of the WCT and Narrow Complex Tachycardia (NCT) produce certain characteristic changes in lead aVR by which we can differentiate between them. The present study was aimed to evaluate tachyarrhythmias in relation to lead aVR and to highlight the clinical significance of lead aVR, "The Neglected Lead". This is prospective study in which 55 consecutive cases of tachyarrhythmias excluding sinus tachycardia, atrial fibrillation and atrial flutter were taken for the study admitted in from ICCU of Department of Medicine at S.S. Medical College and S.G.M. Hospital Rewa (M.P.), India, during July 2014 to September 2015, fulfilling the required study protocol. The data was collected regarding detailed history, physical examination; necessary investigations (including ECG and echocardiography) were done. Among 55 patients, 30 were of WCT and 25 were of NCT. The most common cause of WCT was Ventricular Tachycardia (VT) (83.3%) and rest were Supra Ventricular Tachycardia (SVT) with aberrancy (16.7%). The most common cause of NCT was Atrioventricular Nodal Tachycardia (AVNRT) (84%) followed by Atrioventricular Reciprocating Tachycardia (AVRT) (16%). The present study observed that 38.1% of the AVNRT cases and 50% of AVRT cases showed positive 'p' wave in lead aVR. The present study observed that 75% cases of AVRT showed ST segment elevation in lead aVR while only 33.3% cases of AVNRT showed ST elevation. In the present study 80% of the patients with WCT were diagnosed to have VT using Brugada algorithm while using Vereckei's new aVR algorithm, 83.3% were diagnosed to have VT. Lead aVR, one of the most neglected leads on 12 lead ECG, is a very important diagnostic tool for identification and categorization of different type of tachyarrhythmias. The presence of ST elevation in lead aVR on ECG showing NCT is relatively sensitive for diagnosing AVRT. New aVR algorithm by Vereckei is more sensitive for differential diagnosis of WCT. One should pay careful attention to lead aVR which provides essential diagnostic information.

Ventricular arrhythmias and sudden cardiac death

### Key points There are 50–100 unexpected, sudden cardiac deaths (SCDs) per 100 000 population per year in Europe and USA, categorized by symptom onset to cardiac arrest time of <1 h.1 Despite the decline in coronary artery disease mortality and advancements in resuscitation services, survival from these events remains low. Unfortunately, they often occur outside the hospital environment and are associated with a survival rate of <10%. The majority occur in adults over 35 yr of age and at least half of these events can be attributed to ventricular arrhythmias, although the true incidence is unknown due to inevitable degeneration to asystole if unwitnessed. These arrhythmias may be the presenting complaint in the emergency department and may feature throughout the perioperative period, including at preoperative assessment, during surgery and in the recovery phase, for example in intensive care. They may also be the direct target of therapy in the case of electrophysiological catheter ablation and implantable cardioverter defibrillators (ICDs). They are more frequent and carry greater risks in patients with structural heart disease, but younger patients with ion-channel abnormalities can also be susceptible.2 This review classifies the causes and significance of ventricular arrhythmias based on the presence or absence of structural heart disease and provides a simple system to aid confident distinction from supraventricular arrhythmias. …

Comparison of the “Real-life” Diagnostic Value of Two Recently Published Electrocardiogram Methods for the Differential Diagnosis of Wide QRS Complex Tachycardias

The diagnostic values of the aVR lead or "Vereckei algorithm," and the lead II R-wave peak time (RWPT) criterion, recently devised for the differential diagnosis of wide QRS complex tachycardias (WCTs), were compared. A total of 212 WCTs (142 ventricular tachycardias [VTs], 62 supraventricular tachycardias [SVT], and eight preexcitation SVTs) from 145 patients with proven electrophysiologic diagnoses were retrospectively analyzed by seven examiners blinded to the electrophysiologic diagnoses. The overall test accuracy of the Vereckei algorithm was superior to that of the RWPT criterion (84.3% vs. 79.6%; p = 0.0003). The sensitivity of the Vereckei algorithm for VT diagnosis was greater than that of RWPT criterion (92.4% vs. 79.1%; p < 0.0001). The negative predictive value (NPV) for the Vereckei algorithm was also greater (77.8%; 95% confidence interval [CI] = 73.6% to 82.1%) than that of the RWPT criterion (61.6%; 95% CI = 57.6% to 65.6%). The specificity of the Vereckei algorithm was lower than that of the RWPT criterion (64.7% vs. 80.9%; p < 0.0001). The positive predictive value (PPV) was also lower for the Vereckei algorithm (86.4%; 95% CI = 84.4% to 88.4%) than for the RWPT criterion (90.9%; 95% CI = 89.1% to 92.8%). Incorrect diagnoses made by the Vereckei algorithm were mainly due to misdiagnosis of SVT as VT (65.7% of cases), and those made by the RWPT criterion were due to the more dangerous misdiagnosis of VT as SVT (72.5% of cases). The Vereckei algorithm was superior in overall test accuracy, sensitivity, and NPV for VT diagnosis and inferior in specificity and PPV to the RWPT criterion. All of these parameters were lower in "real life" than those reported by the original authors for each of the particular electrocardiographic methods.

Limitations in the aVR algorithm should not lead to a redefinition of ventricular tachycardia

We have prepared the following response to the letter submitted by Drs Vereckei and Miller.1 1. Our study compared the ability of five electrocardiographic methods to differentiate ventricular tachycardia (VT) from other broad QRS tachycardias. We used the methodologies described in the original five publications, and a uniform definition of VT/non-VT (SVT). We made it clear that the VT group comprised patients that had only VT.2 2. In the original papers describing the Brugada and Griffith's algorithms and the lead II criterion, pre-excited tachycardias were not grouped with VTs. In those studies, a diagnosis of VT was only deemed correct when …

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.

Specificity of the wide QRS complex tachycardia algorithms in recipients of cardiac resynchronization therapy

BackgroundWe assessed the specificity of wide QRS complex tachycardia (WCT) differentiating algorithms in patients with preexistent left bundle branch block (LBBB) and heart failure. MethodsThree hundred fourteen patients with resynchronization devices were retrospectively screened. electrocardiograms with supraventricular LBBB rhythm were used as a surrogate for supraventricular tachycardia QRS morphology. The Pava lead II criterion, ventricular activation velocity ratio (Vi/Vt) ratio in V2, Vereckei aVR, Brugada, Griffith, and Bayesian algorithms were investigated. ResultsThe WCT algorithms had a lower specificity (33%-69%) in patients with LBBB than in general WCT populations. The Pava lead II criterion and Brugada algorithm had higher specificity than other algorithms (P < .05). Several of the single criteria (absence of an RS complex in V1 through V6, initial R wave in aVR, Vi/Vt < 1 in V2) had specificities of 92% to 99%. ConclusionsIn patients with heart failure and LBBB, an electrocardiographic diagnosis of ventricular tachycardia should be based on selected, specific criteria rather than on WCT algorithms.

Are wide complex tachycardia algorithms applicable in children and patients with congenital heart disease?

Introduction Several algorithms have been developed to help determine the etiology of wide complex tachycardias (WCTs) in adults. Sensitivity and specificity for differentiating supraventricular tachycardia (SVT) with aberration from ventricular tachycardia (VT) in adults have been demonstrated to be as high as 98% and 97%. These algorithms have not been tested in the pediatric population. We hypothesize that these algorithms have lower diagnostic accuracy in children and patients with congenital heart disease. Methods A retrospective review of the pediatric electrophysiology database at Stanford from 2001 to 2008 was performed. All children with WCT, a 12-lead electrocardiogram (ECG) available for review, and an electrophysiology study confirming the etiology of the rhythm were included. Patients with a paced rhythm were excluded. The ECGs were analyzed by 2 electrophysiologists blinded to the diagnosis according to the algorithms described in Brugada et al, 2 and Vereckei et al. 5 Additional ECG findings were recorded by each electrophysiologist. Results A total of 65 WCT ECGs in 58 patients were identified. Supraventricular tachycardia was noted in 62% (40/65) and VT in 38% (25/65) of the ECGs. The mean age was 13.5 years (SD ± 5.1), the mean weight was 51.8 kg (SD ± 22.4), and 48% (31/65) were male. The mean tachycardia cycle length was 340 milliseconds (SD ± 95). Congenital heart disease (CHD) was present in 37% (24/65) of patients (7 tetralogy of Fallot, 6 Ebstein's, 4 double-outlet right ventricle, 3 complex CHD, 2 d-transposition of great arteries, 1 status-post orthotopic heart transplantation, 1 ventricular septal defect). The Brugada algorithm correctly predicted the diagnosis 69% (45/65) of the time, the Vereckei algorithm correctly predicted the diagnosis 66% (43/65) of the time, and the blinded reviewer correctly predicted the diagnosis 78% (51/65) of the time. There was no difference in the efficacy of the algorithms in patients with CHD vs those with structurally normal hearts. The findings of left superior axis deviation ( P < .01) and a notch in the QRS downstroke of V 1 or V 2 ( P < .01) were more common in VT than SVT, whereas a positive QRS deflection in V 1 ( P = .03) was more commonly present in SVT than VT. Conclusion The Brugada and Vereckei algorithms have lower diagnostic accuracy in the pediatric population and in patients with congenital heart disease than in the adult population. Left superior axis deviation and a notch in the QRS downstroke were more commonly associated with VT, whereas a positive QRS deflection in V 1 was more commonly associated with SVT in this population.

New algorithm using only lead aVR for differential diagnosis of wide QRS complex tachycardia

We recently reported an ECG algorithm for differential diagnosis of regular wide QRS complex tachycardias that was superior to the Brugada algorithm. The purpose of this study was to further simplify the algorithm by omitting the complicated morphologic criteria and restricting the analysis to lead aVR. In this study, 483 wide QRS complex tachycardias [351 ventricular tachycardias (VTs), 112 supraventricular tachycardias (SVTs), 20 preexcited tachycardias] from 313 patients with proven diagnoses were prospectively analyzed by two of the authors blinded to the diagnosis. Lead aVR was analyzed for (1) presence of an initial R wave, (2) width of an initial r or q wave >40 ms, (3) notching on the initial downstroke of a predominantly negative QRS complex, and (4) ventricular activation-velocity ratio (v(i)/v(t)), the vertical excursion (in millivolts) recorded during the initial (v(i)) and terminal (v(t)) 40 ms of the QRS complex. When any of criteria 1 to 3 was present, VT was diagnosed; when absent, the next criterion was analyzed. In step 4, v(i)/v(t) >1 suggested SVT, and v(i)/v(t) < or =1 suggested VT. The accuracy of the new aVR algorithm and our previous algorithm was superior to that of the Brugada algorithm (P = .002 and P = .007, respectively). The aVR algorithm and our previous algorithm had greater sensitivity (P <.001 and P = .001, respectively) and negative predictive value for diagnosing VT and greater specificity (P <.001 and P = .001, respectively) and positive predictive value for diagnosing SVT compared with the Brugada criteria. The simplified aVR algorithm classified wide QRS complex tachycardias with the same accuracy as standard criteria and our previous algorithm and was superior to the Brugada algorithm.

Application of a new algorithm in the differential diagnosis of wide QRS complex tachycardia

The Brugada criteria proposed to distinguish between regular, monomorphic wide QRS complex tachycardias (WCT) caused by supraventricular (SVT) and ventricular tachycardia (VT) have been reported to have a better sensitivity and specificity than the traditional criteria. By incorporating two new criteria, a new, simplified algorithm was devised and compared with the Brugada criteria. A total of 453 WCTs (331 VTs, 105 SVTs, 17 pre-excited tachycardias) from 287 consecutive patients with a proven electrophysiological (EP) diagnosis were prospectively analysed by two of the authors blinded to the EP diagnosis. The following criteria were analysed: (i) presence of AV dissociation; (ii) presence of an initial R wave in lead aVR; (iii) whether the morphology of the WCT correspond to bundle branch or fascicular block; (iv) estimation of initial (v(i)) and terminal (v(t)) ventricular activation velocity ratio (v(i)/v(t)) by measuring the voltage change on the ECG tracing during the initial 40 ms (v(i)) and the terminal 40 ms (v(t)) of the same bi- or multiphasic QRS complex. A v(i)/v(t) >1 was suggestive of SVT and a v(i)/v(t) <or=1 of VT. An initial R wave in lead aVR suggested VT. The overall test accuracy of the new algorithm was superior (P = 0.006) to that of the Brugada criteria. The new algorithm had a greater sensitivity (P < 0.001) and (-) predictive value (NPV) for VT diagnosis, and specificity (P = 0.0471) and (+) predictive value (PPV) for SVT diagnosis than those of the Brugada criteria [both NPV for VT diagnosis and PPV for SVT diagnosis were: 83.5% (95% confidence interval = CI 75.9-91.1%) for the new vs. 65.2% (95% CI 56.5-73.9%) for the Brugada algorithms]. The new algorithm is a highly accurate tool for correctly diagnosing the cause of WCT ECGs.