Predicting Severe Renal and Gastrointestinal Involvement in Childhood Immunoglobulin A Vasculitis with Routine Laboratory Parameters.

BACKGROUND Immunoglobulin A vasculitis (IgAV) is the most common vasculitis in children. Although childhood IgAV is generally considered as a self-limited disease, progressive course and poor prognosis could occur in some cases which mostly result from severe renal involvement and gastrointestinal (GI) involvement. METHODS We performed a retrospective study of pediatric patients diagnosed as IgAV in our institution from 2016 to 2019. Patients were divided into groups based on the occurrence and severity of GI and renal involvement. Analysis of variance (ANOVA) and Kruskal-Wallis test were used to compare results of laboratory parameters among groups and prediction models were built by using logistic regression analysis. RESULTS A total of 286 patients were enrolled. GI involvement occurred in 148 (51.7%) patients, 30 (20.3%) of which were severe cases. Renal involvement developed in 120 (42.0%) patients, 22 (18.3%) of which were severe cases. Compared with patients with only cutaneous manifestations, white blood cell (WBC) count, neutrophil-to-lymphocyte ratio (NLR), and D-dimer levels were higher in those with GI involvement, and D-dimer level was found to be positively associated with severity. Increased NLR and lower complement 3 (C3) were found in patients with renal involvement, but only C3 was relevant in distinguishing moderate and severe cases. The prediction model for severe renal involvement was: Logit (P) = 6.820 + 0.270 (age) + 0.508 (NLR) - 16.130 (C3), with an AUC of 0.914. The prediction model for severe GI involvement was: Logit (P) = -5.459 + 0.005 (WBC) + 1.355 (D-dimer) - 0.020 (NLR), with an AUC of 0.849. CONCLUSION Our data suggest C3 to be an exclusive predictor for severe renal involvement and D-dimer level to be positively associated with the severity of GI involvement. Prediction models consisting of the above parameters were built for obtaining prognostic information in the early phase of IgAV.