Identification of risk factors for acute heart failure in early postoperative period
DOI:
https://doi.org/10.15587/1729-4061.2013.14853Keywords:
coronary heart disease, coronary artery bypass surgery, risk factors, acute heart failureAbstract
The article discusses the application of methods of intellectual analysis in identifying the structure of the risk factors of progress of acute heart failure, which patients with coronary heart disease may incur. The main objective of the study is to analyze these methods and to construct a mathematical model of forecasting the progress of acute heart failure in early postoperative period. In this article, we discuss the results of binary logistic regression, discriminant analysis and Multifactor Dimensionality Reduction. The comparative analysis revealed that the BLR provides a higher percentage of correct assignments, sensitivity and specificity, which indicates the high quality of the obtained model.
The method MDR helps to identify the hierarchy of interactions of risk factors and the systematic links themselves. It allows you to determine the direction, strength of influence and extent of contingency of factors with an indicator of entropy. The research results can be applied to develop a decision support system to optimize the structure of therapeutic measures to minimize the risk of AHF in the early postoperative period, which patients with coronary heart disease may incur after coronary artery bypass surgery.
References
- Эндоваскулярная хирургия в лечении больных ишемической болезнью сердца с рестенозами ранее имплантированных стентов [Текст] : Руководство по рентгеноэндоваскулярной хирургии сердца и сосудов / под ред. Л. А. Бокерия, Б. Г. Алекяна. – М. : НЦССХ им. А.Н. Бакулева РАМН, 2008. – Т. 3. – Глава 23. – с. 438–455.
- Амосова, Е. Н. Эффективность коррекции факторов риска и различных методов хирургического лечения больных хронической ИБС в отношении предотвращения смерти от инфаркта миокарда: мифы и реальность [Текст] / Е. Н. Амосова // Серце і судини. – 2009. – № 4. – С. 12–24.
- Логистическая регрессия. Многомерные методы статистического анализа категориальнных даннях медицинских исследований [Текст] : Уч. пособие / С. Г. Григорьев, В. И. Юнкеров, Н. Б. Клименко . – СПб, 2001. – с. 10–21.
- Клекка, У. Р. Дискриминантный анализ // Факторный, дискриминантный и кластерный анализ [Текст] / У. Р. Клекка – М. : Финансы и статистика, 1989. – с. 78–138.
- Jakulin, A. Quantifying and Visualizing Attribute Interactions [Текст] / A. Jakulin, I. Bratko // An Approach Based on Entropy. PKDD. – 2004. – V. 3. – P. 229–240.
- Дюк, В. Data Mining: учебный курс [Текст] / В. Дюк, А. Самойленко. – СПб. : «Питер», 2001.
- Ohman, E. M. Risk stratification and therapeutic decision making in acute coronary syndromes [Текст] / E. M. Ohman, C. B. Granger, R.A. Harrington, K. L. Lee // JAMA. – 2000. –V. 8. – 284 p.
- Бююль, А. SPSS: искусство обработки информации. Анализ статистических данных и восстановление скрытых закономерностей [Текст] : пер. с нем. – СПб. : ООО «ДиаСофтЮП», 2002. – 608 с.
- Ланг, Т. А. Как описывать статистику в медицине [Текст] : Руководство для авторов, редакторов и рецензентов. / Т. А. Ланг, М. Сесик. – М. : Практическая Медицина, 2011. – 480 с.
- Бирман, Э. Г. Сравнительный анализ методов прогнозирования [Текст] / Э. Г. Бирман. – НТИ. Сер.2. – 1986. – № 1. – с. 11–16.
- Boqueria, L. A., Alekyan B. G. (2008) Endovascular surgery in the treatment of coronary heart disease patients with previously implanted stent restenosis. Moscow: NTSSSH them. AN Bakuleva Medical Sciences. (3) 23. 438–455.
- Amosova, E. N. (2009) Efficiency correction of risk factors and the different methods of surgical treatment of patients with chronic ischemic heart disease in the prevention of death from myocardial infarction: Myths and Realities. Serdce i sudiny. (4) 12–24.
- Grigoriev, S., Juncker, V. I., Klimenko, N. B. (2001) Logistic regression. Multivariate statistical analysis of categorical dannyah medical research. St. Petersburg. 10–21.
- Klekka, W. R. (1989) Discriminant analysis // The factor, discriminant and cluster analysis. Moscow: Finances and Statistics. 78–138.
- Jakulin, A. (2004) Quantifying and Visualizing Attribute Interactions. An Approach Based on Entropy. PKDD. (3) 229–240.
- Duke, V. (2001) Data Mining: Training Course. St. Petersburg. "Peter".
- Ohman, E. M. (2000) Risk stratification and therapeutic decision making in acute coronary syndromes. JAMA. (8) 284.
- Bruyul, А. (2002) SPSS: art information processing. Analysis of statistical data and restore hidden patterns. St. Petersburg. LLC "DiaSoftYuP. 608.
- Lang, T. A. (2011) How То Report Statistics in Medicine: Annotated guidelines for authors, editors, and reviewers. Philadelphia, PA: American College of Physicians. 480.
- Biermann, E. G (1986) Comparative analysis of methods for forecasting. STI. (2)1. 11–16.
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Copyright (c) 2014 Алена Викторовна Яковенко, Анатолий Викторович Руденко, Евгений Арнольдович Настенко, Николай Леонидович Руденко, Владимир Анатолиевич Павлов
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