Approaches to predicting life expectancy in elderly coronary artery disease patients with comorbid conditions

Abstract

The aim of the study was to develop a model for predicting the probability of survival up to 80 years of age for elderly and senile patients with coronary artery disease (CAD) and concomitant conditions. Materials and methods. A retrospective data analysis of elderly and senile CAD patients who were observed in the period 1997–2019 and died from a cardiovascular event. Results. Using binary logistic regression analysis, a model of the survival probability up to 80 years in CAD patients with comorbid conditions has been developed. The overall accuracy of the model was 83.12 % (χ2 = 6.70, p < 0.05), and the predictive accuracy of the model (AUC = 0.853, 95 % CI 0.802–0.896) was sufficiently high and adequate to use in clinical practice. Odds ratio has shown a greater contribution of arterial hypertension and diabetes mellitus to reduced probabilities of surviving to the age of 80, a less significant contribution – of chronic obstructive pulmonary disease and dyslipidemia. Conclusions. The developed model for predicting the survival probability up to 80 years for older age group patients with coronary artery disease and comorbid conditions can be used to evaluate the effectiveness and correct medical and preventive measures.