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dc.contributor.author
Correa, R.
dc.contributor.author
Arini, Pedro David
dc.contributor.author
Correa, L.
dc.contributor.author
Valentibuzzi, M.
dc.contributor.author
Laciar, E.
dc.date.available
2017-06-28T18:31:19Z
dc.date.issued
2016-02
dc.identifier.citation
Correa, R.; Arini, Pedro David; Correa, L.; Valentibuzzi, M.; Laciar, E.; Identification of Patients with Myocardial Infarction: Vectorcardiographic and Electrocardiographic Analysis ; Schattauer Gmbh-verlag Medizin Naturwissenschaften; Methods Of Information In Medicine; 55; 3; 2-2016; 242-249
dc.identifier.issn
0026-1270
dc.identifier.uri
http://hdl.handle.net/11336/19008
dc.description.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.
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.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Schattauer Gmbh-verlag Medizin Naturwissenschaften
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Myocardial Infarction
dc.subject
Electrocardiography
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Vectorcardiography
dc.subject
Discriminant Analysis
dc.subject.classification
Otras Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
dc.subject.classification
Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
dc.title
Identification of Patients with Myocardial Infarction: Vectorcardiographic and Electrocardiographic Analysis
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2017-06-26T19:51:41Z
dc.journal.volume
55
dc.journal.number
3
dc.journal.pagination
242-249
dc.journal.pais
Alemania
dc.journal.ciudad
Stuttgart
dc.description.fil
Fil: Correa, R.. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electronica y Automática. Gabinete de Tecnología Medica; Argentina
dc.description.fil
Fil: 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; Argentina
dc.description.fil
Fil: Correa, L.. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electronica y Automática. Gabinete de Tecnología Medica; Argentina
dc.description.fil
Fil: Valentibuzzi, M.. Universidad de Buenos Aires. Facultad de Ingenieria. Instituto de Ingeniería Biomédica; Argentina
dc.description.fil
Fil: Laciar, E.. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electronica y Automática. Gabinete de Tecnología Medica; Argentina
dc.journal.title
Methods Of Information In Medicine
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://methods.schattauer.de/en/contents/archivestandard/issue/2341/manuscript/25721.html
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.3414/ME15-01-0101
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