ISSN 1812-7231 Klin.inform.telemed. Volume 14, Issue 15, 2019, Pages 58-66
A. V. Lyashenko, L. H. Voronkov, P. N. Babych
National Scientific Center "Institute of Cardiology named after Acad. N. D. Strazhesko "NAMS of Ukraine", Kiev
Prediction of a combined critical event in patients with chronic heart failure and reduced left ventricular ejection fraction for long observation.
Aim. To make a mathematical model of individual combined endpoint (death or HF hospitalization) in patients with chronic heart failure and reduced left ventricular ejection fraction on the basis of the invented survival predictors in this cohorts of patients.
Materials and methods. 134 patients with ischemic CHF (NYHA II-ІV) and LVEF < 40% were examined. The assessment of the influence of clinical and demographic and other parameters on the combined endpoint of patients was performed by F Mantel-Cox test and SPSS 13.0. The structure of the regression equation was formed using the algorithm of sequential stepwise input of explanatory variables (covariates) and their interactions. As a method of step-by-step input, the method "Forward Stepwise (Conditional LR)" was used ("Gradual inference using conditional believability").
Research results. Plasma levels of bilirubin and citrullin as well as BMI and MHFLQ score are the strong predictors of critical event (death or HF hospitalization) in CHF with redLVEF. The obtained model for predicting of critical event in patients with CHF and reduced LVEF is informative (statistics -2 LogLikelihood is equal 142,699) and adequately describes the risk depending on the variables. The regression equation includes the following changes, and their respective coefficients: FMVR < 8,775%, BMI < 28,73 kg/m2, MHFLQ score > 40,5, creatinine > 90 mkmol/l, bilirubin < 42,5 mkmol/l. The model is characterized by the following indicators: sensitivity 76,9%, specificity 72,9%, accuracy 75%.
Conclusion. The obtained results open the perspectives of optimization of medical-diagnostic measures in patients with heart failure. Individual prognosis of CHF can be used for timely formation of the corresponding groups and their active ambulatory care.
Heart failure, Critical event, Predictors, Mathematical model
1. Abrahamsson P., Swedberg K., Borer J. S. Risk following hospitalization in stable chronic systolic heart failure. Europ. J. Heart failure. 2013, vol. 15, рр. 885–891.
2. Barretto A. C., Del Carlo C. H., Cardoso J. N. Hospital readmissions and death from Heart Failure — rates still alarming. Arquivos Brasileiros de Cardiologia, 2008, vol. 91(5), pp. 335–341.
3. Berry G., Murdoch D. R. Mc Murray Economics of chronic heart failure. Eur. J. Heart Failure, 2001, vol. 3., pp. 283–291.
4. Chin B. S., Davie S. M., Lip G. Y. Heart failure in practice. London: Royal Society of Medicine Prress Ltd, 2002, pp. 76.
5. Dickstein K., Cohen-Solal A., Filippatos G. ESC guidelines for the diagnosis and treatment of acute and chronic heart failure 2016: the Task Force for the diagnosis and treatment of acute and chronic heart failure 2016 of the European Society of Cardiology. Developed in collaboration with the Heart Failure Association of the ESC (HFA) and endorsed by the European Society of Intensive Care Medicine (ESICM). Eur. J. Heart Failure, 2016, №10 (10), pp. 933–989.
6. Kannel W. B. Incidence and epidemiology of heart failure. Heart Fail review, 2000, vol. 5(2), pp. 167–173.
7. Levy W. C., Mozaffarian D., Linker D. T. The Seattle Heart Failure Model: prediction of survival in heart failure. Circulation, 2006, vol. 113(11), pp. 1424–1433.
8. Belenkov Yu. N. Epidemiological studies of heart failure: state of the issue. Consilium medicum, 2002, no. 3, pp. 112–114. (In Russ.).
9. Bykov I. V., Itkin G. P. The principles of constructing a mathematical model for the study of the interaction of nasal continuous flow and cardiovascular system. Vestnik transplantologii i iskustvennykh organov [Bulletin of Transplantology and Artificial Organs], 2013, no. 3, 64 p.
10. Voronkov L. H., Parashchenyuk L. P., Yanovs'kyy H. V. Predictors of quality of life in patients with chronic NYHA functional class III heart failure. Zh Sertse i sudyny [Heart and Vessels], 2009, no. 1, pp. 81–85. (In Ukr.).
11. Voronkov L. G., Tkach N. A., Child G. D. Predictors of survival of patients with chronic heart failure and left ventricular systolic dysfunction for different prognosis terms, according to a three-year prospective follow-up. Zh Sertse i sudyny [Heart and Vessels], 2008, no. 2, pp. 27–32. (In Ukr.).
12. Voronkov L. G. Patient with CHF in Ukraine: analysis of patient population examined in the first national UNIVERS section trial. Sertseva nedostatnist' [Heart Failure], 2012, no. 2, pp. 6 - 13. (In Ukr.).
13. Kendoll M. Dzh., Styuart A. Mnogomernyy statisticheskiy analiz i vremennyye ryady [Multivariate statistical analysis and time series.]. M., Nauka Publ. 1976. 347 p. (In Russ.).
14. Kovalenko V. M., Kornats'kyy V. M. Medyko-sotsial'ni aspekty khvorob systemy krovoobihu. Analitychno-statystychnyy posibnyk [Medico-social aspects of the circulatory system diseases. Analytical and Statistical Manual], 2013. 239 p. (In Ukr.).
15. Kosheleva N.A., Rebrov A.P. Modern algorithms for assessing the individual risk of developing cardiovascular complications in patients with chronic heart disease. Fundamental'nyye issledovaniya [Basic Research], 2011, no. 11 (2), pp. 312–315. (In Russ.).
16. Kuzmin A. G., Gorbunov V. V., Sepp A. V., Kuzmina O. V. Clinical and morphological markers of the adverse course of chronic heart failure. Dal'nevostochnyy meditsinskiy zhurnal [Far Eastern Medical Journal], 2014, no. 2, pp. 6–9. (In Russ.).
17. Kulbakh S. Teoriya informatsii i statistika [Theory of Information and Statistics.]. M., Nauka Publ. 1967. 326 p. (In Russ.).
18. Rebrova O. Yu. Statistichniy analіz medichnikh danikh. Zastosuvannya paketu prikladnikh program STATISTICA [Statistical analysis of medical data. Application of the STATISTICA application package]. M., Medifa Sfera Publ., 2002, 305 p. (In Ukr.).
19. Sergiyenko V. I. Bondareva I. B. Matematicheskaya statistika v klinicheskikh issledovaniyakh [Mathematical statistics in clinical studies]. M.: Goetar Meditsina Publ., 2000. 256 p. (In Russ.).
Full-text version http://kit-journal.com.ua/en/viewer_en.html?doc/2019_15/005.pdf