Computerized automated algorithm-based analyses of digitized paper ECGs in Brugada syndrome

Area of Science:

• Cardiology
• Medical Informatics
• Genetics

Background:

• Brugada syndrome is a rare inherited arrhythmia linked to sudden cardiac death.
• Traditional risk stratification relies on manual ECG measurements from paper records.
• Automated analysis of digitized ECGs offers a novel approach to overcome limitations of manual measurements.

Purpose of the Study:

• To validate the digitization process for historical paper ECGs in Brugada syndrome patients.
• To quantify the acute effects of class I antiarrhythmic drugs on ECG parameters using automated analysis.
• To establish the reliability of automated ECG analysis for Brugada syndrome risk stratification.

Main Methods:

• Digitization of 176 Brugada syndrome patients' paper ECGs using ECGScan software.
• Validation of digitization using 20 patients with both paper and digital ECGs.
• Automated ECG parameter measurements performed with Bravo and Glasgow algorithms.

Main Results:

• Digitized and digital ECG parameters showed high correlation (r=0.96, R²=0.93).
• Class I antiarrhythmic drugs significantly increased QRS duration and ST-segment elevation in lead V2.
• Drug challenge also decreased ST slope and increased TpTe interval in lead V2.

Conclusions:

• Automated analysis of digitized paper ECGs is a reliable method for Brugada syndrome.
• This approach accurately quantifies the acute effects of antiarrhythmic drugs.
• Computerized analysis of digitized ECGs can enhance risk stratification decision trees for Brugada syndrome.