Study of QRS-loop parameters and conventional ST-T Indexes for Identification of ischemic and healthy subjects

Several studies have shown the usefulness of the vectorcardiogram (VCG) and the electrocardiogram (ECG) for the detection of cardiac ischemia. We computed a set of VCG and ECG parameters to identify ischemic patients from healthy subjects. The study groups consisted of 80 ischemic patients and 52 healthy subjects. For both populations, five VCG parameters computed on QRS-loop were analyzed, i.e.: (a) Volume, (b) Planar Area, (c) Ratio between Area and Perimeter, (d) Perimeter, and (e) Distance between Centroid and Loop. Likewise, three conventional ECG ST-T parameters were calculated, i.e: (f) ST Vector Magnitude, (g) ST segment level and, (h) T-wave amplitude. Results indicate that VCG and ECG parameters have significant differences between healthy and ischemic subjects. The QRS-loop parameter with the best global performance was Volume, which reached a Sensitivity (Se)=64.5%, a Specificity (Sp)=74.6%, and an Area Under Relative Operating Characteristic Curve (AUC)= 0.77. The best ST-T index was STVM, which obtained Se= 73.2%, Sp=73.9%, and AUC=0.79. However, when all QRS-loop and ST-T parameters were combined, we obtained Se=90.9%, Sp=93.7% and AUC=0.97. In conclusion, the inclusion of QRS-loop parameters improves the conventional ST-T analysis in the identification of ischemic patients.Fil: Correa, Raul. Universidad Nacional de San Juan; ArgentinaFil: Arini, Pedro David. Universidad de Buenos Aires. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Argentino de Matemática Alberto Calderón; ArgentinaFil: Valentibuzzi, Maximo E.. Universidad de Buenos Aires. Facultad de Ingeniería; ArgentinaFil: Laciar, Eric. Universidad Nacional de San Juan; ArgentinaXXIX International Conference on Computers in CardiologyCracoviaPoloniaAGH University of Science and Technolog

Identification of Patients with Myocardial Infarction: Vectorcardiographic and Electrocardiographic Analysis

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. Objectives: 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.Fil: Correa, R.. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electronica y Automática. Gabinete de Tecnología Medica; ArgentinaFil: Arini, Pedro David. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Argentino de Matemática Alberto Calderon; Argentina. Universidad de Buenos Aires. Facultad de Ingeniería; ArgentinaFil: Correa, L.. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electronica y Automática. Gabinete de Tecnología Medica; ArgentinaFil: Valentibuzzi, M.. Universidad de Buenos Aires. Facultad de Ingenieria. Instituto de Ingeniería Biomédica; ArgentinaFil: Laciar, E.. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electronica y Automática. Gabinete de Tecnología Medica; Argentin

Cardiac Risk Assessment: When and Who?

Cardiac fibrillation, both ventricular and atrial, should perhaps be considered as probabilistic phenomena that can be biased according to the pathophysiological condition of the subject. Attempts in this direction have so far been few and vague, and models based on chaos theory, up to now, have been disappointing, even though, at one point in time, the theory sounded appealing, and many papers were produced. In this paper, it has been described the relatively recent historical development of different techniques for cardiac risk assessment, which started with serious quantitative steps in the middle of the 20th century, not more than 50 or 60 years ago, and is part of a much more complex effort aimed at health risk assessment.Fil: Valentinuzzi, Max E.. Universidad de Buenos Aires. Facultad de Ingenieria. Instituto de Ingeniería Biomédica; ArgentinaFil: Arini, Pedro David. Universidad de Buenos Aires. Facultad de Ingenieria. Instituto de Ingeniería Biomédica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Laciar Leber, Eric. Universidad Nacional de San Juan. Facultad de Ingenieria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bonomini, Maria Paula. Universidad Nacional de San Juan. Facultad de Ingenieria. Departamento de Electronica y Automatica. Gabinete de Tecnologia Medica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Correa, Raul O.. Universidad Nacional de San Juan. Facultad de Ingenieria; Argentin