Українська  English  Русский  


Inventory reference

ISSN 1812-7231 Klin.inform.telemed. Volume 12, Issue 13, 2017, Pages 42–52


L. H. Voronkov, O. L. Filatova, P. N. Babych, A. V. Lyashenko, N. A. Tkach, L. P. Parashenuk


National Scientific Center 'M. D. Strazhesko of NAMS of Ukraine', Kyiv, Ukraine

Article title

Prediction of survival in men and women with chronic heart failure and reduced left ventricular ejection fraction for three years.

Abstract (resume)

Aim: to make a mathematical model of individual forecasting mortality in men and women 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.

356 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 survival of patients (men and women separately) 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.

The obtained model for predicting survival of men with CHF and reduced LVEF is informative (statistics - 2 Log Likelihood is equal 851.94) and adequately describes the risk depending on the variables. The regression equation includes the following changes, and their respective coefficients: LVEF<30%, RV thickness>0.6 cm, SV<64 ml, level of serum potassium>4.4 mmol/l, index EDV>118 ml, level of uric acid>597 mmol/l. For men, the model is characterized by the following indicators: sensitivity 87%, specificity 73%, accuracy 86%.

The obtained model of prediction of survival of women with CHF with reduced LVEF is informative (statistics - 2 Log Likelihood is equal 361.184) and adequately describes the risk depending on the variables. The regression equation includes the following changes, and their respective coefficients: EF<30%, level of uric acid>262 mmol/l, level of serum creatinine>130 mmol/l, BMI<29 kg/m2, eGFR<46 ml/minute/1.73m2. For women, the model is characterized by the following indicators: sensitivity 96%, specificity 71%, accuracy 91%.


The obtained results open the perspectives of optimization of medical-diagnostic measures in patients with heart failure, depending on sex. Individual prognosis of CHF can be used for timely formation of the corresponding groups and their active ambulatory care.


heart failure, survival, predictors, gender, mathematical model


1. James K. Kirklin, MD, a David C. Naftel, PhD, a Robert L. Kormos. Fifth INTERMACS annual report: Risk factor analysis from more than 6, 000 mechanical circulatory support patients. The Journal of Heart and Lung Transplantation, 2013, iss.5, pp. 141–156.

2. Khalid A., Bhatti S. K., Al-Amoodi M. Clinical factors associated with left ventricular ejection fraction disparity in patients with left ventricular dysfunction undergoing multimodality imaging. Missouri Medicine, 2012, vol. 109, iss. 6, pp. 489-492.

3. Maggioni A. P., Dahlstrom U., Filippatos G., Chioncel O. EUR Observational Research Programme: regional differences and 1-year follow-up results of the Heart Failure Pilot Survey (ESC-HF Pilot). Eur. J. Heart Fail. 2013, vol. 15, pp. 56 – 112.

4. Mozaffarian E. J., Benjamin A. S. Go heart disease and stroke statistics-2016 update: A report from the American Heart Association. Circulation, 2016, vol. 133, N 4, рр. 38–360.

5. O'Connor C. M., Abraham W. T., Albert N. M. Predictors of mortality after discharge in patients hospitalized with heart failure: an analysis from the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF). Amer. Heart J., 2008, vol. 156, iss.4, pp. 662–673.

6. Tarride J. E., Lim M., Des Meules M. A review of the cost of cardiovascular disease. Canad. J. Cardiology, 2009, vol. 25, iss. 6, pp. 195–202.

7. Belenkov U. N. Left ventricular dysfunction in patients with IHD: modern diagnostic methods, drug and non-pharmacologic correction. Rosiiskii medicinskii jyrnal [Russian Medical Journal], 2000, iss. 17, pp. 685 – 693. (In Rus.).

8. Belenkov U. N., Mareev V. U. How we diagnose and treat heart failure in real clinical practice in the early 21st century. Consilium medicum, 2001, iss.2, pp. 65-72. (In Rus.).

9. Bikov I. V., Itkin G. P. Principles for constructing a mathematical model for investigating the interaction of continuous flow pumps and the cardiovascular system. Vestnik transplantologii i iskysstvennih organov [Bulletin of Transplantology and Artificial Organs], 2013, vol. 15, iss. 3, pp. 64- 69. (In Rus.).

10. Bіlovol A. N., Bobronnikova L. P., Іlchenko І. A. Pathogenetic aspects of the development of chronic heart failure, depending on gender and age. Ykr. Terapevt. Jyrn. [Ukr therapist. J.], 2014, iss. 3, pp. 9–13. (In Ukr.).

11. Voronkov L. G. A patient with CHF in Ukraine: an analysis of the data of the population of patients examined in the framework of the first national study UNIVERS. Serceva nedostatnіst. [Heart failure], 2012, iss 1, pp. 8–132. (In Ukr.).

12. Kendoll M. Dj., Stuart A. Mnogomernyj statisticheskij analiz i vremennye rjady. [Multivariate statistical analysis and time series]. M., Nauka Publ., 1976, 347 p. (In Rus.).

13. Kovalenka V. M., Lutaya M. I., Sirenka Yu. M., Sychova O. S. Sercevo-sudynni zaxvoryuvannya. Klasyfikaciya, standarty diahnostyky ta likuvannya [Cardiovascular disease. Classification, standards of diagnosis and treatment.] Kyiv, Morion Publ., 2016, 192 p. (In Ukr.)

14. Kovalenko V. N., Lutay M. Y., Voronkov L. H. Rukovodstvo po kardiologii [Guide to Cardiology]. Kyiv, Morion Publ., 2008, 1424 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 failure. Fyndamentalnie issledovaniya [Fundamental research], 2011, vol. 11, iss. 2, pp. 312-315.

16. Kyzmin A. G., Gorbynov V. V., Sepp A. V. Clinical and morphological markers of unfavorable course of chronic heart failure. Dalnevostochnii medicinskii Jyrnal [Far Eastern Medical Journal], 2014, iss. 2, pp. 6–9. (In Rus.).

17. Kylbah S. Teorija informacii i statistika. [Information Theory and Statistics]. Moscow, Nauka Publ., 1967, 326 p. (In Rus.).

18. Ostrovskii U. P. Serdechnaja nedostatochnost' [Heart failure]. Minsk: Beleryskaya navyka Publ., 2016, 503p. (In Rus.).

19. Petri A., Sebin K. Nagljadnaja statistika v medicine [Visual statistics in medicine]. Kyiv, Geotar-Med Publ, 2003, 143p. (In Rus.).

20. Rebrova O. U. Statystychnyj analiz medychnyx danyx. Zastosuvannya paketu prykladnyx prohram Statistica [Statistical analysis of medical data. Application of Statistica application package]. Moscow, Medif Sphere Publ., 2002, 305 p. (In Rus.).

21. Sergienko V. I., Bondareva I. B. Matematicheskaja statistika v klinicheskih issledovanijah [Mathematical statistics in clinical trials]. Kyiv Geotar-Med. Publ., 2000, 256p. (In Rus.).

Full-text version