Utility of Different Electrocardiographical Leads during Diagnostic Ajmaline Test for Suspected Brugada Syndrome

In order to compare the value of different leads and lead combinations to detect the signature Brugada type ECG pattern, we analysed digital 10-second, 15-lead ECGs (12 standard leads + leads V1 to V3 from 3rd intercostal (i.c.) space, V1h to V3h) acquired during diagnostic Ajmaline testing in 128 patients (80 men, age 37±15 years) with suspected Brugada syndrome (BS) (patient group), 15-lead resting ECGs of 108 healthy subjects (53 men, age 31.9±10.5 years) (control group A) and standard 12-lead resting ECGs of 229 healthy subjects (111 men, age 33±4 years) (control group B). Bipolar leads between V2 (positive pole) and V4 or V5 (leads V2-4V2-5) were derived by subtracting leads V4 and V5 from V2 (custom-made program). The 6 peripheral, 6 right precordial leads (V1 to V3, V1h to V3h) and leads V2-4 and V2-5 of the patients group, leads V1h to V3h of control group A, and leads V2-4 and V2-5 of control group B were analysed for the presence of type 1 Brugada pattern. There were 21 (16.4%) positive and 107 (83.6%) negative Ajmaline tests. In 7 positive tests (33%), type 1 pattern appeared only in leads V1h to V3h, whereas in 14 tests 67%) it appeared in both V1 to V3 and V1h to V3h. Lead V2 displayed type 1 pattern during 10 positive tests; in all of them, plus 10 other positive tests type 1 was also noted in lead V2h (n=20, 95.2%). In all 10 cases, in which lead V2 exhibited type 1 pattern (n=10), lead V2-4 and/or V2-5 also exhibited type 1-like pattern. During 7 positive tests, in which lead V2h but not V2 exhibited type 1 pattern, lead V2-4 and/or V2-5 also demonstrated type 1 pattern. Type 1 pattern was observed in leads V3 and V3h during 1 (5%) and 5 (24%) positive tests, in 0 ECGs (0%) in control group A and in 1 ECG (0.4%) in control group B. In conclusion, the "high" V1 and V2 leads (3rd i.c. space) detect more sensitively Brugada type 1 pattern than the standard V1 and V2 leads (4th i.c. space); leads V3 and V3h are not essential for the diagnosis of BS; bipolar leads V2-4 and V2-5 are superior to lead V2 for the ECG diagnosis of BS

ECG Wavelet Analysis for the Detection of Gene Mutations in Patients with Brugada Syndrome

Abstract We applied wavelet transform (WT) Introduction The Brugada syndrome (BrS) is an inherited ion chanelopathy characterised by a typical electrocardiographic (ECG) pattern of J point and ST segment elevation in the right precordial leads and predisposition towards malignant ventricular arrhythmias Both depolarisation and repolarisation abnormalities contribute to the arrhythmia substrate and arrhythmia genesis in the BrS Wavelet analysis is a form of time-frequency transformation that has long been used in non-invasive electrocardiology for detection of characteristic ECG components, heart rate variability, analysis of ischaemic ST changes, ventricular repolarisation and others In this study, we hypothesised that continuous wavelet transform (WT) applied to the QRS and ST-T wave can help to identify carriers of SCN5A mutations among patients with the BrS. We analysed digital 15-lead ECGs previously recorded during positive diagnostic ajmaline test for BrS with simultaneous acquisition of the right precordial leads in both standard, as well as "high" electrode positions. Methods Study population and data acquisition The study population consisted of 26 patients (age 42.0±17.8 years, 13 men, 13 women, age 41.6±19.1 and 42.4±17.2, respectively, p=0.92 for men vs women) with suspected BrS who underwent diagnostic ajmaline test as part of their standard clinical management. All patients had either normal or non-diagnostic (i.e. not displaying type 1 Brugada ECG pattern) resting ECGs before the test. Details about this patient population have been partially described in previous publication

Diagnostic utility of bipolar precordial leads during ajmaline testing for suspected Brugada syndrome

BACKGROUND Leads V-1 and V-2 recorded from the standard position (fourth intercostal space) have insufficient sensitivity to detect the diagnostic type 1 Brugada ECG pattern. OBJECTIVE The purpose of this study was to compare the sensitivity of bipolar leads with a positive pole at V-2 and a negative pole at V-4 or V-5 with that of the standard unipolar lead V-2 for detection of the type 1 Brugada pattern. METHODS We analyzed digital 15-lead ECGs (12 standard leads plus leads V-1 to V-3 recorded from the third intercostal space [V-1h to V-3h]) acquired during diagnostic ajmaline testing in 128 patients (80 men, age 37 +/- 15 years) with suspected Brugada syndrome and standard 12-lead ECGs recorded in 229 healthy subjects (111 men, age 33 +/- 4 years). Bipolar leads between V-2 (positive pole) and V-4 or V-5 (leads V2-4, V2-5) were derived by subtracting leads V-4 and V-5 from V-2. All ECGs were examined for the presence of type 1 Brugada pattern. RESULTS During 21 (16.4%) positive ajmaline tests, type 1 pattern was observed in lead V-2h during 20 tests (95.2%) and in V-2 during 10 tests (47.6%). Type 1 pattern appeared in lead V2-4 or V2-5 in all tests when it was present in V-2 and in seven tests during which it was observed in lead V-2h but not V-2 (17 tests [ 81%]). Type 1-like pattern was observed in lead V2-4 or V2-5 during two nonpositive tests (1.9%) and in one healthy subject (0.4%). CONCLUSION Bipolar leads V2-4 and V2-5 are more sensitive than lead V2 for detection of the type 1 Brugada patter

Comparison of six commonly used QT correction models and their parameter estimation methods.

This paper compares six commonly used QT correction models and three available parameter estimation methods using five indices for QTc evaluation based on real and simulated electrocardiograph (ECG) datasets. The results show that the golden section approach always finds the correction factor making QTc interval uncorrelated to heart rate for all six formulas. However, the correction formulas derived from mixed model sometimes fail to make QTc interval invariant of heart rate. The performance of an individual least-square regression method lies between the golden section iteration approach and the mixed model in terms of QTc-RR relationship

A nonparametric approach to QT interval correction for heart rate.

We propose to use generalized additive models to fit the relationship between QT interval and RR (RR = 60/heart rate), and develop two new methods for correcting the QT for heart rate: the linear additive model and log-transformed linear additive model. The proposed methods are compared with six commonly used parametric models that were used in four clinical trial data sets and a simulated data set. The results show that the linear additive models provide the best fit for the vast majority of individual QT-RR profiles. Moreover, the QT correction formula derived from the linear additive model outperforms other correction methods