Henoch-Schönlein purpura (HSP) is a common systemic vasculitis in childhood, with a relatively high incidence of renal involvement. In recent years, an increasing number of studies have focused on risk prediction models for HSP-related renal injury; however, substantial heterogeneity exists in predictor selection and modeling approaches.

This study aims to systematically summarize the characteristics of existing predictive models for kidney injury risk in children with HSP, as well as their common predictors and methodological quality, thereby providing a basis for researchers to conduct related studies and for clinicians to identify high-risk children at an early stage.

A scoping review was conducted. PubMed, Embase, the Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Data, VIP Database, and China Biology Medicine disc (CBM) were systematically searched from inception to June 1, 2025. Literature screening and data extraction were performed independently by two reviewers. Model-related information was extracted using the CHARMS checklist, and the risk of bias and applicability were assessed using the Prediction Model Risk of Bias Assessment Tool (PROBAST).

A total of 13 studies were included, comprising 6 Chinese-language and 7 English-language studies, with sample sizes ranging from 165 to 1 294 participants. The incidence of renal injury in children with HSP ranged from 26.67% to 63.75%, and the area under the receiver operating characteristic curve (AUC) ranged from 0.550 to 0.956. The most frequently reported predictors were age, recurrent purpura, persistent purpura, D-dimer, and serum albumin. PROBAST assessment indicated a high risk of bias across the included studies, mainly attributable to retrospective study designs, inadequate handling of missing data, and the lack of external validation.

Existing prediction models for renal injury in children with HSP are at high risk of bias, which compromises their reliability and clinical implementation. Future studies should prioritize prospective study designs, standardized reporting, optimization of predictor selection, and multicenter external validation to develop more robust and generalizable risk prediction tools.

过敏性紫癜（HSP）是儿童时期常见的系统性血管炎，肾脏损伤比例较高。近年来，关于HSP肾脏损伤风险预测模型的研究日益增多，但预测因子选择、建模方法等方面存在较大差异。

本研究旨在系统总结现有儿童HSP肾脏损伤风险预测模型的构建特征、常见预测因子及方法学质量，为研究者开展相关研究及临床早期识别高危患儿提供依据。

采用范围综述法，系统检索PubMed、Embase、Cochrane Library、Web of Science、中国知网、万方数据知识服务平台、维普网、中国生物医学文献数据库，检索时间为数据库建立至2025-06-01。由2名研究者独立进行文献筛选和数据提取，采用CHARMS清单提取模型相关信息，使用预测模型偏倚风险评估工具（PROBAST）评估偏倚风险和适用性。

最终共纳入13项研究，包括6项中文研究和7项英文研究，样本量165~1 294例。HSP肾脏损伤的发生率为26.67%~63.75%，受试者工作特征曲线下面积（AUC）为0.550~0.956。最常见的预测因子为年龄、紫癜反复发作、持续性紫癜、D-二聚体和白蛋白。PROBAST质量评估显示，纳入的研究存在较高偏倚风险，主要与回顾性研究设计、缺失数据处理不足及缺乏外部验证有关。

现有儿童HSP肾脏损伤预测模型偏倚风险较高，影响其可靠性与临床推广。未来研究应注重前瞻性设计、规范报告、优化预测因子，并开展多中心外部验证，构建更稳健、可推广的风险预测工具。