Complex multifactorial prediction model for life-threatening ventricular arrhythmias in patients with myocardial infarction

Aim. To identify markers of ventricular tachycardia (VT), as well as to create a multifactorial prediction model for arrhythmic events in inpatients with myocardial infarction (MI).

Material and methods. The study included 80 patients with MI aged 55,6±8,7 years. The following examination was carried out on days 7-9 of MI: echocardiography, assessment of global longitudinal strain (GLS), contrast-­enhanced cardiac magnetic resonance imaging (MRI), determination of N-terminal pro-brain natriuretic peptide (NT-proBNP). During 72-hour electrocardiographic (ECG) monitoring, we detected VT runs, as well as analyzed microvolt T-wave alternans (TWA), heart rate turbulence, late ventricular potentials, heart rate variability, cardiac chronotropic load, and QT dispersion. The end point was the presence of ≥1 VT episode (≥3 QRS complexes) according to multi-day ECG monitoring data.

Results. Nonsustained VT runs were recorded in 10 (12,5%) patients, who made up the VT group. The remaining 70 (87,5%) people who did not have VT episodes were included in the comparison group. MRI data established that the scar tissue mass (36,8±23,7 g) and percentage (28,5±19,8%) in the VT group was higher than in the comparison group (16,9 (6,5; 27,9) g (p=0,025) and 13,3 (5,8; 22,2)% (p=0,045), respectively).

Univariate regression analysis revealed following factors associated with the VT risk: history of coronary artery disease, high NT-proBNP values, heart rate turbulence, microvolt TWA, end diastolic dimension, GLS, scar tissue mass, scar area from total myocardial mass (%), night-time heart rate variability parameters — ULfP, TINN, SDANN.

Conclusion. A multifactorial model for predicting non-sustained VT in patients with MI is proposed, including the following parameters: end-diastolic dimension, MAT, NT-proBNP, GLS, scar tissue mass, and history of coronary artery disease.

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