Методика прогнозирования клинических исходов при помощи логистического регрессионного анализа в статистической программе IBM SPSS Statistics 20.0 (часть 1)

Abstract

We presented a description of the organization of the method of constructing a mathematical model of clinical outcome risk prediction on the identified medical and social factors. Purpose: description of binary logistic regression analysis methodology in medical research. Research methods. Logistics regression is a form of multiple regression whose general purpose is to analyze the relationship between several independent variables and a dependent variable. For binary logistic regression analysis application, the following conditions must be met: the resulting variable must assume two values (favorable clinical outcome/adverse clinical outcome), the independent variables can be both categorical and interval, and must be independent of each other. Results of a research. On the basis of the studied medical and social factors, a mathematical model of the prediction of the probability of developing primary disability among persons who have suffered brain injuries has been developed. The obtained regression equation contains four variables: the patient's age, the nature of the brain injury, the level of formation, the severity of the brain injury. The mathematical model predicts the onset of an adverse clinical outcome with a probability of 87.6 %. The obtained results allow calculating the predicted probability of the studied clinical outcome with the permissible proportion of sensitivity and specificity. Conclusion. The presented technique is of practical importance in terms of improving the knowledge of the beginner researcher in the field of building mathematical models for predicting the probability of the event being studied.