Herasymyiuk M, Repak V
REGRESSION ANALYSIS AS A METHOD FOR PREDICTING THE RISK OF CHRONIC RHINOSINUSITIS RECURRENCE
IN PATIENTS OF DIFFERENT SEXES
Herasymiuk Maksym I
Horbachevsky Ternopil National Medical University
Associate professor of the otolaryngology, ophthalmology and neurosurgery department
PhD, Associate professor
Email: herasymyuk_m@tdmu.edu.ua
Orcid ID: https://orcid.org/0000-0001-8566-7426
Scopus Author ID: 57218549973
ResearcherID: B-7826-2018
Repak Viktor V
Horbachevsky Ternopil National Medical University
Email: repak_vikvad@tdmu.edu.ua
Orcid ID: https://orcid.org/0009-0005-2442-606X
Abstract
Relevance: Chronic rhinosinusitis (ChRS) is a broad term defined as “infection of the sinuses and nasal mucosa lasting more than 3 months (or 12 weeks) per year”. Given that, according to modern theories, ChRS is considered as a disease of multifactorial origin, and the search for effective methods of predicting the risk of disease relapse is urgent. Today, one of the popular and fairly accurate methods of predicting the relapse of various diseases is the construction of a multivariate regression model.
Aim: To propose a new approach to predicting the risk of chronic rhinosinusitis relapse in male and female patients based on multivariate regression analysis.
Materials and methods: 214 patients, including 108 women and 106 men, aged 18 to 80 years with a diagnosis of chronic rhinosinusitis, were examined.
Results: To build a multifactorial regression model for predicting the chronic rhinosinusitis relapse, probable factors of the disease were selected. Using multivariate regression analysis, 11 factors with a significance level of less than 0.05 were analysed for the male and female group separately. Histograms of the residual deviations of predicting the chronic rhinosinusitis relapse were obtained, which are distributed symmetrically, and a normal-probability straight line is presented, on which there are no systematic deviations. The given results confirm the statistical hypothesis that the residual deviations correspond to the normal distribution law. Residual deviations relative to the predicted values are scattered chaotically, which indicates the absence of dependence on the predicted values of the risk of chronic rhinosinusitis relapse.
The value of the coefficient of determination was calculated, which is 0.991 in the male group and 0.9896 in the female group, which gives grounds to claim that 99.91% of the factors in the male group and 98.96% in the female group are taken into account in the model for predicting the chronic rhinosinusitis relapse and its high reliability and pleasantness in general.
Conclusions: The use of this model helps to predict possible complications and the probability of relapse of the researched disease.
Key words: regression analysis, chronic rhinosinusitis, prognosis, gender.
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