Risk Factors Associated with Renal Injury in Patients Initially Diagnosed with IgA Vasculitis

Lu SHen^1,2,3,4Lian Xu^1,2,3,4Li Miao^1,2,3,4*

• ¹The First People’s Hospital of Lianyungang, Lianyungang, China
• ²The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, China
• ³The Affiliated Hospital of Kangda College of Nanjing Medical University,Lianyungang Clinical College of Nanjing Medical University, Lianyungang, China
• ⁴Lianyungang Clinical Medical College, Nanjing Medical University, Lianyungang, China

Objective To explore the risk factors associated with renal injury in patients diagnosed with IgA vasculitis at initial presentation.Methods A retrospective analysis was conducted on the clinical data of 384 children who were newly diagnosed with Immunoglobulin A vasculitis(IgAV) and hospitalized between July 2020 and June 2023. The participants were categorized into two groups based on whether their 24-hour urinary protein levels exceeded 150mg upon admission. Specifically, those with a 24-hour urinary protein level exceeding 150mg were classified as the IgA vasculitis nephritis(IgAVN), while the remaining participants were included in the IgAV group. A comparative assessment was performed to evaluate the general condition and laboratory examination results of both groups. The logistic regression analysis was utilized to pinpoint variables correlated with renal injury, facilitating the development of a risk prediction model. The receiver operating characteristic curve(ROC) was employed to evaluate the model's predictive performance.The univariate analysis revealed that the duration of rash, gender, patient age, levels of C-reactive protein(CRP), Immunoglobulin G (IgG), albumin, globulin, glutamic oxaloacetic transaminase(AST), total cholesterol(TC), urine routine results, and 25-(OH)-D3 were all identified as potential influencing factors for IgAVN. Multivariate analysis revealed that albumin, patient age, and TC emerged as independent influential factors in the occurrence of IgAVN. The area under the curve (AUC) for the combined predictor(age+albumin+TC) was significantly larger than that of individual factors such as age, albumin, and TC, with respective AUC values of 0.804, 0.673, 0.737, and 0.608. The prediction model of IgAVN was further developed as follows: logit(P) = 3.978 ＋ 0.199 × age (years) -0.197 × albumin (g/L) ＋ 0.550 × TC (mmol/L).IgAVN, thereby reinforcing the importance of follow-up measures for early detection, diagnosis, and treatment in order to mitigate the occurrence of unfavorable prognosis.