title: Identification of Patients with Myocardial Infarction. Vectorcardiographic and Electrocardiographic Analysis.
abstract: BACKGROUND
  The largest morbidity and mortality group worldwide continues to be that suffering Myocardial Infarction (MI). The use of vectorcardiography (VCG) and electrocardiography (ECG) has improved the diagnosis and characterization of this cardiac condition.
  
  
  OBJECTIVE
  Herein, we applied a novel ECG-VCG combination technique to identifying 95 patients with MI and to differentiating them from 52 healthy reference subjects. Subsequently, and with a similar method, the location of the infarcted area permitted patient classification.
  
  
  METHODS
  We analyzed five depolarization and four repolarization indexes, say: a) volume; b) planar area; c) QRS loop perimeter; d) QRS vector difference; e - g) Area under the QRS complex, ST segment and T-wave in the (X, Y, Z) leads; h) ST-T Vector Magnitude Difference; i) T-wave Vector Magnitude Difference; and j) the spatial angle between the QRS complex and the T-wave. For classification, patients were divided into two groups according to the infarcted area, that is, anterior or inferior sectors (MI-ant and MI-inf, respectively).
  
  
  RESULTS
  Our results indicate that several ECG and VCG parameters show significant differences (p-value<0.05) between Healthy and MI subjects, and between MI-ant and MI-inf. Moreover, combining five parameters, it was possible to classify the MI and healthy subjects with a sensitivity = 95.8%, a specificity = 94.2%, and an accuracy = 95.2%, after applying a linear discriminant classifier method. Similarly, combining eight indexes, we could separate out the MI patients in MI-ant vs MI-inf with a sensitivity = 89.8%, 84.8%, respectively, and an accuracy = 89.8%.
  
  
  CONCLUSIONS
  The new multivariable MI patient identification and localization technique, based on ECG and VCG combination indexes, offered excellent performance to differentiating populations with MI from healthy subjects. Furthermore, this technique might be applicable to estimating the infarcted area localization. In addition, the proposed method would be an alternative diagnostic technique in the emergency room.
authors.affiliation: Raúl Correa, Gabinete de Tecnología Médica - Facultad de Ingeniería, Universidad Nacional de San Juan, Av. Libertador General San Martín 1109 (O), J5400ARL - San Juan, Argentina, E-mail: rcorrea@gateme.unsj.edu.ar.
authors.forename: Raúl
authors.initials: R
authors.lastname: Correa
authors.forename: Pedro D
authors.initials: PD
authors.lastname: Arini
authors.forename: Lorena S
authors.initials: LS
authors.lastname: Correa
authors.forename: Max
authors.initials: M
authors.lastname: Valentinuzzi
authors.forename: Eric
authors.initials: E
authors.lastname: Laciar
mesh_terms: D000465:Algorithms; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009203:Myocardial Infarction / Q000175:diagnosis*; D014672:Vectorcardiography
keywords: Myocardial infarction; discriminant analysis; electrocardiography; vectorcardiography