Predicting Recovery of Myocardial Function by Electrocardiography after Acute Infarction

Abstract

In ACS patients, computed ECG variables predict recovery of LV function from ischemic myocardial injury, even in the presence of comparable CK-MBm release and LV dysfunction.

Assessment of Myocardial Infarct Size with Body Surface Potential Mapping: Validation against Contrast‐Enhanced Cardiac Magnetic Resonance Imaging

“…Earlier, we found that in left anterior descending coronary artery (LAD)-and right coronary artery (RCA)-related MIs, the 1st QRSint was the best depolarization variable to predict, after acute MI, recovery of myocardial function. 5 In this study, the 1st QRSint was positive, or close to zero, at the best recording location on the right upper back in most patients with the largest infarcts. At this site, in all patients (but one) with a small or no infarct, the 1st QRSint was negative, similar to healthy individuals.…”

“…In healthy individuals, the initial deflection of the QRS is negative on the back, representing a mirror image of the R wave in precordial ECG leads; analogically, Q waves on the precordial area are reflected as R waves reciprocally on the back. 5 What is well established is that Q waves indicate permanent myocardial damage after an infarction. Irrespective of MI age and location, classical Q waves (30-40 ms in width) are associated with larger MI size.…”

“…4 We have also shown that in acute MI patients, computed ECG variables can predict recovery of myocardial function. 5 Although ECG is routine in MI diagnostics, assessment of MI size by ECG is not current clinical practice. Our aim was to learn whether single-lead ECG variables computed from BSPM recordings could serve in MI quantification.…”

Comparison of minimum-norm estimation and beamforming in electrocardiography with acute ischemia

“…In this work, we studied the localization and size estimation of acute ischemia. We have previously studied the use of BSPM after myocardial infarction in prediction of myocardial recovery (Kylmälä et al 2013), arrhythmic events (Korhonen et al 2009), and cardiac deaths (Korhonen et al 2010). Those investigations were based on detecting BSPM features in signal…”