Прогнозування ризику розвитку хронічного бронхіту у підлітків-курців

Autor: S.I. Ilchenko, A.O. Fialkovskaya
Rok vydání: 2021
Předmět:
Zdroj: CHILD`S HEALTH. 12:445-449
ISSN: 2307-1168
2224-0551
DOI: 10.22141/2224-0551.12.4.2017.107624
Popis: Background. The purpose of the study was to create a prognostic model of the risk of chronic respiratory pathology in teenage smokers comfortable to use in practical medicine. Materials and methods. 73 teenage smokers aged 14–18 years (average age is 16.4 ± 0.2 years) have been exa­mined. They were divided into two groups: group 1 consisted of 36 teenage smo­kers with chronic bronchitis (average age is 16.8 ± 0.2 years) and comparison group comprised 37 apparently healthy teenage smokers (average age is 15.9 ± 0.2 years). We have studied clinical-anamnestic, functiona­­linstrumental data (spirometry, radiography of chest organs, level of nitric oxide in expired breath condensate, respiratory muscles strength) and molecular-genetic factors of the risk of developing chronic pathology of respiratory organs in teenage smokers — 103 characteristics overall. The method of consequent (sequential) analysis of Wald and Bayes strategy were used to create a prognostic model of the risk of chronic bronchitis. Results. The principle of working with a mathematical model for predicting the risk of chronic respiratory pathology development in teenage smokers is to sum up diagnostic factors that are consistent with the signs found in the patient. When the sum of diagnostic components is +13, the deve­lopment of chronic bronchitis is diagnosed in teenage smo­kers with error probability ≤ 5 % (р < 0.05); when the sum is +20 — the probability of diagnosis is 99 % (р < 0.01). Conclusions. Our algorithm for predicting the risk of develo­ping chronic bronchitis in teenage smokers will help early detection of high-risk patients in the formation of this pathology for personalized preventive measures that will allow practitioners to prevent chronic pathological processes and to improve the quality of life.
Databáze: OpenAIRE