ArticleActa medica Lituanic2024
Possible Threats of IgA Vasculitis in Children: One Center Experience.
Article in Acta medica Lituanic, 2024. 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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Abstract
Introduction: Immunoglobulin A vasculitis (IgAV) is the most common vasculitis in children. Although typically self-limiting, IgAV may result in serious complications. Our objective was to evaluate the incidence, clinical features, laboratory predictors and outcomes of IgA vasculitis with gastrointestinal (GI) and kidney involvement. Methods: Medical records of patients <18 years of age with newly diagnosed IgAV between 2013 and 2021 in a single center were analyzed. Demographic, clinical, laboratory data, and incidence of GI and kidney involvement data were analyzed. As laboratory predictors, neutrophil, lymphocyte, platelets count, mean platelet volume (MPV) and neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) were calculated. Results: 240 patients with IgAV were included. GI involvement was in 104 patients (43.3%), whereas kidney involvment in 21 patients (8.8%). Age was the only variable associated with increased odds of kidney involvement (OR 3.5, 95% confidence interval 1.39-8.56, p=0.009). None of the laboratory predictors or other tested variables was associated with kidney involvement in univariable logistic regression. The neutrophil and lymphocyte count, NLR and PLR levels were found to be significantly higher in children with GI involvement. There were no bad outcomes: lethal outcome or chronic kidney disease for the patients with GI and kidney involvement in recent study. During two years of surveillance after IgAV diagnosis, 11 cases (4.6%) had indications for kidney biopsy and were diagnosed with IgAV nephritis. Conclusions: Older children were more likely to have kidney disease. Easy obtained laboratory parameters such as NLP, PLR could help to predict GI involvement in early disease stage, but had no value for predicting kidney involvement.
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