Wide Complex Tachycardia

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

OBJECTIVE

Several 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 to assess the diagnostic precision of various non-artificial intelligence ECG-based algorithms for WCT.

DESIGN

Systematic review with meta-analysis.

DATA SOURCES

Electronic databases (PubMed, MEDLINE, the Cochrane Library, and Web of Science) are searched up to May 2022.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

All studies reporting the diagnostic accuracy of different ECG-based algorithms for WCT are included. The risk of bias in included studies is assessed using the Cochrane Collaboration's risk of bias tools.

DATA EXTRACTION AND SYNTHESIS

Two independent reviewers extracted data and assessed risk of bias. Data were pooled using random-effects model and expressed as mean differences with 95% CIs. Heterogeneity was calculated by the I² method. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was applied to assess the internal validity of the diagnostic studies.

RESULTS

In total, 467 studies were identified, and 14 studies comprising 3966 patients were included, involving four assessable ECG-based algorithms: the Brugada algorithm, Vereckei-pre algorithm, Vereckei-aVR algorithm and R wave peak time of lead II (RWPT-II) algorithm. The overall sensitivity was 88.89% (95% CI: 85.03 to 91.86), with a specificity of 70.55% (95% CI: 62.10 to 77.79) and a diagnostic OR (DOR) of 19.17 (95% CI: 11.45 to 32.10). Heterogeneity of the DOR was 89.1%. The summary sensitivity of each algorithm was Brugada 90.25%, Vereckei-pre 94.80%, Vereckei-aVR 90.35% and RWPT-II 78.15%; the summary specificity was Brugada 64.02%, Vereckei-pre 75.40%, Vereckei-aVR 60.88% and RWPT-II 88.30% and the summary DOR was Brugada 16.48, Vereckei-pre 60.70, Vereckei-aVR 14.57 and RWPT-II 27.00.

CONCLUSIONS

ECG-based algorithms exhibit high sensitivity and moderate specificity in diagnosing WCT. A combination of Brugada or Vereckei-aVR algorithm with RWPT-II could be considered to diagnose WCT.

PROSPERO REGISTRATION NUMBER

CRD42022344996.

Cerebrovascular and cardiovascular diseases caused by drugs of abuse

Drugs such as stimulants, sedatives, sleeping pills, and narcotics are associated with drug abuse and are therefore regulated by law. Physical dependence on these drugs is sometimes difficult to control despite an awareness of the problems they cause in daily life and the harm they can cause to the body. Drug dependence is a social problem worldwide, and the physical implications are serious. Many of these drugs cause cerebrovascular and cardiovascular diseases, which often require emergency medical treatment. Differential diagnosis is essential because of the likelihood of life-threatening events, especially among young people who exhibit cerebrovascular and cardiovascular diseases without any of the typical risk factors. Drugs of abuse, especially stimulants, induce a hyperadrenergic state that evokes vasoconstriction and tachycardia, as well as subsequent ischemic and hemorrhagic stroke, acute coronary syndrome, arrhythmias, and aortic dissection. Chronic drug abuse can also cause cardiac hypertrophy and left ventricular dysfunction. As a treatment for these conditions, sedative drugs can be effective but the use of vasodilators may also be required. There are concerns that the use of both alpha- and beta-adrenergic receptor blockers may cause tachycardia and increased blood pressure. Therefore, careful differential diagnosis and selection of therapeutic agents is required.

Wide complex tachycardia discrimination using dynamic time warping of ECG beats

BACKGROUND AND OBJECTIVE

Automatic processing and accurate diagnosis of wide complex tachycardia (WCT) arrhythmia groups using electrocardiogram signals (ECG) remains a challenge. WCT arrhythmia consists of two main groups: ventricular tachycardia (VT) and supraventricular tachycardia with aberrancy (SVT-A). These two groups have similar morphologies in the realm of ECG signals. VT and SVT-A arrhythmias originate from the ventricle and atrium, respectively. Hence, inaccurate diagnosis of SVT-A instead of VT can be fatal.

METHODS

In this paper, we present a novel algorithm using dynamic time warping (DTW) to discriminate between VT and SVT-A arrhythmias. This method includes pre-processing, best template search (BTS), and classifier modules. The first module, pre-processing, is responsible for filtering, R-wave detection, and beat detection of ECG signals. The second module, BTS, automatically extracts the minimum possible number of signals as a template from the entire training dataset using an intelligent algorithm. These template signals have the greatest morphological difference, which leads to accurate WCT discrimination. Finally, a 1NN classifier categorizes the test data using DTW distance.

RESULTS

Our proposed method was evaluated on an ECG signal database consisting of 171 subjects. The results showed that the proposed algorithm can accurately discriminate between VT, SVT-A, and normal subjects, and appears to be suitable for future use in clinical application. The obtained accuracy, sensitivity, specificity, and positive predictive values were 93.22%, 88.68%, 96.98%, and 90.27%, respectively.

CONCLUSION

The presented diagnostic method for discriminating VT and SVT-A, using only one ECG lead, is suitable for future clinical use. It can reduce needless therapeutic interventions and minimize risk for patients.

Wide QRS complex tachycardias

Wide QRS complex tachycardia is a common clinical occurrence and presents a diagnostic challenge for the physician. History, physical examination, chest radiographs, and electrocardiographic analysis are important in making the correct diagnosis. Diagnosis of ventricular tachycardia is supported by history of prior myocardial infarction or congestive heart failure, physical examination showing cannon A-waves in the jugular venous pulsation or variable heart sounds, chest radiograph showing cardiomegaly or evidence of prior cardiac surgery, and characteristic ECG features: AV dissociation, fusion/capture beats, QRS concordance or typical morphologic features in leads V1 and V6. In this article, a clinical approach to wide QRS complex tachycardias is presented.

Clinical approach to wide QRS complex tachycardias

Wide QRS complex tachycardia is a frequently encountered arrhythmia in the emergency department and presents a diagnostic challenge to the emergency physician. The history, physical examination, chest radiograph, and electrocardiogram analysis are important in making the correct diagnosis. The diagnosis of ventricular tachycardia is supported by, 1) a history of prior myocardial infarction or congestive heart failure; 2) a physical examination showing cannon A-waves in the jugular venous pulsation or variable heart sounds; 3) a chest radiograph showing cardiomegaly or evidence of prior cardiac surgery; and 4) characteristic ECG features that include AV dissociation, fusion-capture beats, QRS concordance, or, typical morphologic features in leads V1 and V6. This article presents the diagnostic and therapeutic approaches to wide QRS tachycardias.