DOI: https://doi.org/10.31071/kit2017.13.06

Inventory reference

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

Author(s)

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

Institution(s)

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%.

Conclusion.

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.

Keywords

heart failure, survival, predictors, gender, mathematical model

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