Key result
Multifactorial clinical model accurately predicts post-MI non-sustained VT with ~0.96 AUC.
Why the study?
The study was conducted to identify markers of ventricular tachycardia and create a multifactorial prediction model for arrhythmic events in inpatients with myocardial infarction.
Cohort (n=80)
No
A comprehensive multifactorial model utilizing clinical, laboratory, echocardiographic, and MRI parameters can accurately identify post-myocardial infarction patients at high risk for non-sustained ventricular tachycardia.
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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Averyanova et al. (2024) conducted a cohort in Myocardial infarction (n=80). Multifactorial risk markers (including scar tissue mass, GLS, NT-proBNP, TWA, end-diastolic dimension, history of CAD) vs. Patients without ventricular tachycardia was evaluated on Presence of ≥1 ventricular tachycardia episode (≥3 QRS complexes) during 72-hour ECG monitoring. A multifactorial prediction model incorporating scar tissue mass, global longitudinal strain, NT-proBNP, microvolt T-wave alternans, end-diastolic dimension, and history of coronary artery disease accurately predicted non-sustained ventricular tachycardia with an AUC of 0.960.
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