FORECASTING OF DEVELOPMENT OF THE VISION ORGAN CHANGES AT DIFFERENT ETIOLOGY ARTHRITIS PATIENTS

Authors

  • A. K. Pavlyuchenko National Medical University named after O. O. Bogomolets of the Ministry of Public Health of Ukraine Kyiv, Ukraine

DOI:

https://doi.org/10.22141/2309-8147.5.3.2017.172346

Keywords:

different etiology arthritis, vision organ changes development, model of logistic regression

Abstract

Summary. The aim of this work was mathematical model creation for forecasting of vision organ changes at different etiology arthritis patients.
Material and methods. It were analyzing data from 448 patients suffering from chronic infl ammatory illnesses of joints among which there were 133 patients with a rheumatic arthritis, 79 – with ankylosing spondylitis, 61 children with juvenile idiopathic arthritis, 76 – with psoriasis arthritis and 99 – with reactive Chlamidia arthritis; changes of an vision organ (conjunctivitis, scleritis, keratitis, cataract, uveitis, glaucoma) were taped at 20,3 %, 29,1 %, 39,3 %, 40,8 % and 62,6 %, respectively. For assessment of a contribution of factorial signs to forecasting of probability existence of vision organ changes (PVOC) the analysis of resultant indicators of Wald-statistics and also the importance of their difference in comparison with a zero hypothesis was carried out.
Results and conclusions. The conducted research showed that the key indicators defi ning a condition of the patient – age, sex, like arthritis and the index of arthritis progression defi ne probability of vision organ changes development. 
The logistic regression model which with high degree of probability (not less than 96 %) defi ned probability of vision organ changes development at PVOC≥0,343 value is constructed. The formula for calculation of probability of development of changes of an organ of vision which had signifi cant communication between risk of vision organ changes development and the chosen indicators is offered: the area under AUC=0,993±0,002 ROC curve (CI±95 % 0,989–0,998) which statistically signifi cantly differed from 0,5 (p=2,45E–68). Model assessment by a method of maximum likelihood taped satisfactory parameters of regression: –2log=89,73 (χ2=502,0; p=0,000 at df=4).

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Published

2017-11-01

Issue

Section

Clinical Ophthalmology