Electrical cardioversion presents one of the treatment options for atrial fibrillation (AF). However, the early recurrence rate is high, reaching ~40% three months after the procedure. Features based on vectorcardiographic signals were explored to find association with early recurrence of AF. Eighty-four patients with non-paroxysmal AF referred to electrical cardioversion were prospectively studied; early AF recurrence was present in 40 (47.6%). Patients underwent 24-h Holter ECG monitoring three months after the procedure to assess AF recurrence. Pre-procedural 12-lead ECGs (10 s, 1 kHz) were recorded and automatically analyzed. We explored associations of VCG-based features with early AF recurrence. Two features were strongly associated with AF recurrence: (1) a mean VCG (y-axis) signal slope in a window starting 145 ms before QRS center, lasting for 190 ms (AUC 0.778, p < 0.001), and (2) a mean VCG (z-axis) signal slope in a window starting 60 ms after QRS center, lasting for 465 ms (AUC 0.744, p < 0.001). These features showed higher association to the outcome than eighteen baseline clinical features. Our approach revealed features based on a slope of vectorcardiographic signals. This work also suggests that state of ventricles strongly affects the AF recurrence after electrical cardioversion.

• MeSH
• elektrická defibrilace * MeSH
• elektrokardiografie ambulantní MeSH
• fibrilace síní * terapie   patofyziologie   MeSH
• lidé středního věku MeSH
• lidé MeSH
• prospektivní studie MeSH
• recidiva * MeSH
• senioři MeSH
• vektorkardiografie * metody   MeSH
• výsledek terapie MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

INTRODUCTION: Electrical cardioversion (ECV) remains a treatment option for atrial fibrillation (AF). The study aimed to find predictors of SR maintenance after ECV using spectral and vector cardiographic (VCG) analysis of ECGs. METHODS: Consecutive patients with AF referred for elective ECV were prospectively enrolled. A digital ECG recording was obtained before the ECV and was analyzed using spectral and VCG analysis. AF activity was analyzed using spectral analysis to determine the dominant frequency (DF), RI (regularity index), and OI (organizational index). QRS complexes were analyzed using vectorcardiography to determine the dXmean, dYmean, and dZmean (derivation of VCG signals). We used Lasso Logistic Regression (LLR) in five-fold cross-validation for feature selection and to build combined predictive models of SR maintenance. For model training and evaluation, data were split in a 60%-40% ratio for training and testing, respectively. RESULTS: A total of 80 patients were enrolled (age 70.2 ± 10.6 years, 49 (61%) were men, BMI 29.7 kg/m2). At the 3-month follow-up, AF recurrence was present in 36 patients (45%). The best single VCG parameter to predict SR maintenance was dZMean (OR 0.18, 95% CI 0.06-0.51, p < 0.001). VCG-domain parameters combined into the LLR model showed an area under the curve (AUC) of 0.78. From the spectral analysis domain, the best predictor was DF (OR 3.54, 95% CI 1.28-10.25), p = 0.006; spectral features led to an AUC of 0.76 when combined in the LLR model. Clinical features did not form a model since no features passed feature selection. Combining VCG and spectral analysis features led to an LLR model with an AUC of 0.79. CONCLUSION: The combination of spectral analysis of AF activity and VCG analysis of ventricular activity provided more accurate predictive information than either analysis alone.

• MeSH
• elektrická defibrilace * metody   MeSH
• elektrokardiografie * metody   MeSH
• fibrilace síní * terapie   patofyziologie   MeSH
• lidé středního věku MeSH
• lidé MeSH
• prediktivní hodnota testů MeSH
• prospektivní studie MeSH
• senioři MeSH
• vektorkardiografie * metody   MeSH
• výsledek terapie MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

This article presents an overview of existing approaches to perform vectorcardiographic (VCG) diagnostics of ischemic heart disease (IHD). Individual methodologies are divided into categories to create a comprehensive and clear overview of electrical cardiac activity measurement, signal pre-processing, features extraction and classification procedures. An emphasis is placed on methods describing the electrical heart space (EHS) by several features extraction techniques based on spatiotemporal characteristics or signal modelling and signal transformations. Performance of individual methodologies are compared depending on classification of extent of ischemia, acute forms - myocardial infarction (MI) and myocardial scars localization. Based on a comparison of imaging methods, the advantages of VCG over the standard 12-leads ECG such as providing a 3D orthogonal leads imaging, better performance, and appropriate computer processing are highlighted. The issues of electrical cardiac activity measurements on body surface, the lack of VKG databases supported by a more accurate imaging method, possibility of comparison with the physiology of individual cases are outlined as potential reserves for future research.

• MeSH
• elektrokardiografie metody   MeSH
• infarkt myokardu * MeSH
• lidé MeSH
• myokard MeSH
• počítačové zpracování signálu MeSH
• srdce fyziologie   MeSH
• vektorkardiografie * metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

• MeSH
• lékařství MeSH
• Publikační typ
• periodika MeSH

• Konspekt
• Lékařské vědy. Lékařství
• NLK Obory
• lékařství