Predicting the coronary atherosclerosis severity in cardiac patients

Background. Coronary atherosclerosis is an ongoing pathological process, varying from asymptomatic forms to angina pectoris, myocardial infarction and even sudden cardiac death. Early identification of persons with an increased risk of the severe atherosclerosis will promote adequate diagnostic and...

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Autores principales:	Yuri N. Fedulaev, Irina V. Makarova, Tatiana V. Pinchuk, Sergey E. Arakelov, Irina Y. Titova
Formato:	article
Lenguaje:	EN RU
Publicado:	Concilium Medicum 2021
Materias:	electrocardiography holter monitoring atherosclerosis qt dispersion heart rate turbulence qrs-fragmentation Diseases of the circulatory (Cardiovascular) system RC666-701 Diseases of the endocrine glands. Clinical endocrinology RC648-665
Acceso en línea:	https://doaj.org/article/3d7e73f26a854ae9aa5479e3a575cc68
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spelling	oai:doaj.org-article:3d7e73f26a854ae9aa5479e3a575cc682021-12-01T22:07:01ZPredicting the coronary atherosclerosis severity in cardiac patients2221-71852658-570710.26442/22217185.2021.1.200766https://doaj.org/article/3d7e73f26a854ae9aa5479e3a575cc682021-05-01T00:00:00Zhttps://cardiosomatics.orscience.ru/2221-7185/article/viewFile/52818/pdfhttps://doaj.org/toc/2221-7185https://doaj.org/toc/2658-5707Background. Coronary atherosclerosis is an ongoing pathological process, varying from asymptomatic forms to angina pectoris, myocardial infarction and even sudden cardiac death. Early identification of persons with an increased risk of the severe atherosclerosis will promote adequate diagnostic and therapeutic measures to prevent cardiovascular complications. Aim. To make a prognostic model determining the probability of a severe coronary atherosclerosis in cardiac patients. Material and methods. The actual study included 116 patients of cardiology departments with various degree of coronary atherosclerosis measured by coronary angiography: group I 70% coronary stenosis (50% in case of left main coronary artery), group II those with less severe atherosclerotic process. All patients underwent electrocardiography (ECG) at rest and Holter monitoring. Pathological Q-waves, qualitative and quantitative characteristics of ventricular extrasystoles as well as QRS-fragmentation were assessed in all cases. In individuals having sinus rhythm, heart rate turbulence (HRT), T-wave alternans and QT, QTc dispersion on maximum and minimum heart rate were additionally calculated. Results. The prognostic model included the following ECG-markers: HRT, pathological Q-waves, QTc dispersion on maximum heart rate and QRS-fragmentation in lateral leads (I, AVL, V6). All parameters have demonstrated a direct relationship with the likelihood of severe coronary atherosclerosis. The current model took into account 71% of the factors influencing significant atherosclerosis, AUC=0.940.04, the sensitivity and the specificity were 90.0 and 94.4% respectively. Conclusion. A comprehensive assessment of the ECG data helps to identify the group with an increased risk of severe coronary atherosclerosis among cardiac patients.Yuri N. FedulaevIrina V. MakarovaTatiana V. PinchukSergey E. ArakelovIrina Y. TitovaConcilium Medicumarticleelectrocardiographyholter monitoringatherosclerosisqt dispersionheart rate turbulenceqrs-fragmentationDiseases of the circulatory (Cardiovascular) systemRC666-701Diseases of the endocrine glands. Clinical endocrinologyRC648-665ENRUКардиоСоматика, Vol 12, Iss 1, Pp 11-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN RU
topic	electrocardiography holter monitoring atherosclerosis qt dispersion heart rate turbulence qrs-fragmentation Diseases of the circulatory (Cardiovascular) system RC666-701 Diseases of the endocrine glands. Clinical endocrinology RC648-665
spellingShingle	electrocardiography holter monitoring atherosclerosis qt dispersion heart rate turbulence qrs-fragmentation Diseases of the circulatory (Cardiovascular) system RC666-701 Diseases of the endocrine glands. Clinical endocrinology RC648-665 Yuri N. Fedulaev Irina V. Makarova Tatiana V. Pinchuk Sergey E. Arakelov Irina Y. Titova Predicting the coronary atherosclerosis severity in cardiac patients
description	Background. Coronary atherosclerosis is an ongoing pathological process, varying from asymptomatic forms to angina pectoris, myocardial infarction and even sudden cardiac death. Early identification of persons with an increased risk of the severe atherosclerosis will promote adequate diagnostic and therapeutic measures to prevent cardiovascular complications. Aim. To make a prognostic model determining the probability of a severe coronary atherosclerosis in cardiac patients. Material and methods. The actual study included 116 patients of cardiology departments with various degree of coronary atherosclerosis measured by coronary angiography: group I 70% coronary stenosis (50% in case of left main coronary artery), group II those with less severe atherosclerotic process. All patients underwent electrocardiography (ECG) at rest and Holter monitoring. Pathological Q-waves, qualitative and quantitative characteristics of ventricular extrasystoles as well as QRS-fragmentation were assessed in all cases. In individuals having sinus rhythm, heart rate turbulence (HRT), T-wave alternans and QT, QTc dispersion on maximum and minimum heart rate were additionally calculated. Results. The prognostic model included the following ECG-markers: HRT, pathological Q-waves, QTc dispersion on maximum heart rate and QRS-fragmentation in lateral leads (I, AVL, V6). All parameters have demonstrated a direct relationship with the likelihood of severe coronary atherosclerosis. The current model took into account 71% of the factors influencing significant atherosclerosis, AUC=0.940.04, the sensitivity and the specificity were 90.0 and 94.4% respectively. Conclusion. A comprehensive assessment of the ECG data helps to identify the group with an increased risk of severe coronary atherosclerosis among cardiac patients.
format	article
author	Yuri N. Fedulaev Irina V. Makarova Tatiana V. Pinchuk Sergey E. Arakelov Irina Y. Titova
author_facet	Yuri N. Fedulaev Irina V. Makarova Tatiana V. Pinchuk Sergey E. Arakelov Irina Y. Titova
author_sort	Yuri N. Fedulaev
title	Predicting the coronary atherosclerosis severity in cardiac patients
title_short	Predicting the coronary atherosclerosis severity in cardiac patients
title_full	Predicting the coronary atherosclerosis severity in cardiac patients
title_fullStr	Predicting the coronary atherosclerosis severity in cardiac patients
title_full_unstemmed	Predicting the coronary atherosclerosis severity in cardiac patients
title_sort	predicting the coronary atherosclerosis severity in cardiac patients
publisher	Concilium Medicum
publishDate	2021
url	https://doaj.org/article/3d7e73f26a854ae9aa5479e3a575cc68
work_keys_str_mv	AT yurinfedulaev predictingthecoronaryatherosclerosisseverityincardiacpatients AT irinavmakarova predictingthecoronaryatherosclerosisseverityincardiacpatients AT tatianavpinchuk predictingthecoronaryatherosclerosisseverityincardiacpatients AT sergeyearakelov predictingthecoronaryatherosclerosisseverityincardiacpatients AT irinaytitova predictingthecoronaryatherosclerosisseverityincardiacpatients
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Predicting the coronary atherosclerosis severity in cardiac patients

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