Depolarization changes during acute myocardial ischemia by evaluation of QRS slopes: standard lead and vectorial approach.
Diagnosis and risk stratification of patients with acute coronary syndromes can be improved by adding information from the depolarization phase (QRS complex) to the conventionally used ST-T segment changes. In this study, ischemia-induced changes in the main three slopes of the QRS complex, upward ( ℑ(US)) and downward ( ℑ(DS) ) slopes of the R wave as well as the upward ( ℑ(TS)) slope of the terminal S wave, were evaluated as to represent a robust measure of pathological changes within the depolarization phase. From ECG recordings both in a resting state (control recordings) and during percutaneous coronary intervention (PCI)-induced transmural ischemia, we developed a method for quantification of ℑ(US), ℑ(DS), and ℑ(TS) that incorporates dynamic ECG normalization so as to improve the sensitivity in the detection of ischemia-induced changes. The same method was also applied on leads obtained by projection of QRS loops onto their dominant directions. We show that ℑ(US), ℑ(DS), and ℑ(TS) present high stability in the resting state, thus providing a stable reference for ischemia characterization. Maximum relative factors of change ( ℜ(ℑ)) during PCI were found in leads derived from the QRS loop, reaching 10.5 and 13.7 times their normal variations in the control for ℑ(US) and ℑ(DS), respectively. For standard leads, the relative factors of change were 6.01 and 9.31. The ℑ(TS) index presented a similar behavior to that of ℑ(DS). The timing for the occurrence of significant changes in ℑ(US) and ℑ(DS) varied with lead, ranging from 30 s to 2 min after initiation of coronary occlusion. In the present ischemia model, relative ℑ(DS) changes were smaller than ST changes in most leads, however with only modest correlation between the two indices, suggesting they present different information about the ischemic process. We conclude that QRS slopes offer a robust tool for evaluating depolarization changes during myocardial ischemia.
Romero
Daniel
D
Communications Technology Group, Aragón Institute for Engineering Research, and CIBER de Bioingeniería, Biomateriales y Nanomedicina, University of Zaragoza, 50018 Zaragoza, Spain. daromero@unizar.es
Ringborn
Michael
M
Laguna
Pablo
P
Pahlm
Olle
O
Pueyo
Esther
E
D000208:Acute Disease; D004562:Electrocardiography / Q000379:methods*; D006801:Humans; D017202:Myocardial Ischemia / Q000503:physiopathology*; D025341:Principal Component Analysis; D012815:Signal Processing, Computer-Assisted; D018709:Statistics, Nonparametric