Enhancing electrocardiographic analysis by combining a high-resolution 12-lead ECG with novel software tools.

INTRODUCTION: Signal-averaged electrocardiography is a non-invasive, computerized technique that amplifies, filters, and averages cardiac electrical signals reducing contaminating noise to obtain a high-resolution record. The most widely used signal averaging (SA) method involves a bipolar X, Y, and Z orthogonal lead system. Information is limited regarding its application in the standard resting 12-lead ECG. A novel system combining a high-resolution 12-lead ECG (HR-ECG) registered by SA with advanced analysis tools is presented. HISTORY: Original programming of a commercially available signal-averaged HR-ECG device was modified, introducing more exhaustive electrocardiographic assessment instruments. DESCRIPTION: Using SA techniques and placing surface electrodes in the standard 12-lead ECG positions, a HR-ECG is acquired within a bandwidth of 0.25 to 262 Hz at a rate of 1000 samples per second. It is advisable to average at least 200 cycles, taking three to five minutes to record. The package includes different optional high-frequency filters, manual calipers, zoom/superimposing/amplification functions. CLINICAL ROLE: The main strength lies in obtaining a low noise HR-ECG with zooming capabilities without definition loss. Other potential advantages are the greater ease in performing high precision analysis and comparing different ECG leads simultaneously. CURRENT PROBLEMS: The primary limitation is the inability to document intermittent or dynamic electrocardiographic disorders because of averaging similar electrical cardiac cycles. FUTURE DEVELOPMENTS: Adding artificial intelligence and further refinements in the averaging process could lead to software upgrades. CONCLUSION: Integrating HR-ECG, obtained through SA techniques, with novel advanced analysis tools can enhance the ability to detect electrocardiographic disorders of permanent expression expeditiously.

Brugada phenocopy induced by severe pneumothorax.

A Brugada phenocopy has been defined as a clinical situation that presents with an abnormal electrocardiogram identical to any of the electrocardiographic patterns found in Brugada syndrome in the absence of the characteristic congenital genetic abnormalities. The first confirmed case of type 1 Brugada phenocopy associated with severe left pneumothorax is presented. A provocative test with ajmaline, which proved to be negative, was performed to confirm the diagnosis. The presence of ST-segment elevation in the context of pneumothorax is most infrequent.

Vectorcardiography-derived index allows a robust quantification of ventricular electrical synchrony.

Alteration of muscle activation sequence is a key mechanism in heart failure with reduced ejection fraction. Successful cardiac resynchronization therapy (CRT), which has become standard therapy in these patients, is limited by the lack of precise dyssynchrony quantification. We implemented a computational pipeline that allows assessment of ventricular dyssynchrony by vectorcardiogram reconstruction from the patient's electrocardiogram. We defined a ventricular dyssynchrony index as the distance between the voltage and speed time integrals of an individual observation and the linear fit of these variables obtained from a healthy population. The pipeline was tested in a 1914-patient population. The dyssynchrony index showed minimum values in heathy controls and maximum values in patients with left bundle branch block (LBBB) or with a pacemaker (PM). We established a critical dyssynchrony index value that discriminates electrical dyssynchronous patterns (LBBB and PM) from ventricular synchrony. In 10 patients with PM or CRT devices, dyssynchrony indexes above the critical value were associated with high time to peak strain standard deviation, an echocardiographic measure of mechanical dyssynchrony. Our index proves to be a promising tool to evaluate ventricular activation dyssynchrony, potentially enhancing the selection of candidates for CRT, device configuration during implantation, and post-implant optimization.