ArticleReumatologia2015
Predictors of juvenile idiopathic arthritis course.
Article in Reumatologia, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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3 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
introductionJuvenile idiopathic arthritis (JIA) is a heterogeneous group of inflammatory diseases of joints in children with various and often unfavourable prognosis. It is possible to improve the outcome of the disease in patients with JIA by a correct therapeutic choice made at disease onset - one that enables fast achievement of an inactive disease state and remission. The aim of the investigation was to develop a model/application for automatic calculation of risk of treatment-refractory JIA taking into account the combined action of clinical and cytokine factors. MATERIAL AND
methodsDisease subtype was determined in 105 patients with JIA, as well as the number of poor prognostic factors and disease activity level. Blood serum cytokine levels (IL-1β, IL-4, IL-6, IL-8, IL-10, IL-17, TNF-α, IFN-γ) and their soluble receptors and agonists - interleukin 1 receptor agonist (IL-1Ra), soluble interleukin 2 receptor (sCD25), interleukin 6 (sIL6R), soluble tumour necrosis factor receptor 1 (sTNFR1) - were determined in these patients using immunoenzymatic laboratory methods.
resultsThe following prognostic factors were taken into account in the study: JIA subtype, disease activity, presence of clinically unfavourable factors and cytokine characteristics. We determined that systemic subtype of JIA, moderate and high disease activity, presence of factors of poor disease course and sCD25 and IL-6 levels are statistically significant factors of treatment-refractory disease course. A Microsoft Excel application was developed for automatic calculation of risk of treatment-refractory JIA in a specific patient based on 10 factors.
conclusionsUse of an application for automatic calculation of risk of treatment-refractory JIA enables prediction of JIA disease course in patients at disease onset and personalization of the treatment protocol.
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