Scoping Review of Risk Prediction Models for Skin Tears in the Elderly

目的：对皮肤撕裂伤患者风险预测模型进行归纳总结，为临床护理实践及未来皮肤撕裂伤风险预测模型的研究提供借鉴。方法：通过计算机系统分别检索中国知网、中国生物医学文献数据库、万方、维普、PubMed、Web of Science核心合集、Cochrane Library及Embase数据库，检索时间范围为各数据库建库起至2024年11月30日。由两位研究者独立完成文献筛选工作，并对最终纳入的研究进行数据提取、整合分析及偏倚风险评估。结果：共纳入8篇文献，主要为国外研究，模型构建方法以Logistic回归为主。所有研究均未提供模型展示。最常见的预测因子为皮肤撕裂伤病史和老年性紫癜。结论：纳入的模型具有较好的预测效能，但整体偏倚风险较高。未来研究应采用可视化展示方法，建立偏倚风险低、预测性能好且具有高临床实用性的模型。Objective: This study aims to summarize existing risk prediction models for patients with skin tears, with the goal of offering insights for clinical nursing practice and informing future research on model development. Methods: A comprehensive literature search was conducted using computer-based retrieval across CNKI, CBM, Wanfang, VIP, PubMed, Web of Science Core Collection, Cochrane Library, and Embase. The search period covered all records up to November 30, 2024. Two researchers independently screened the literature, extracted relevant data, conducted synthesis, and assessed the risk of bias. Results: A total of eight studies were included, mainly from international sources. The main models were constructed using logistic regression. None of the studies provided a visual representation of the models. The most frequently reported predictors were a history of skin tears and senile purpura. Conclusion: The included models showed good predictive performance overall, but many had a high risk of bias. Future research should focus on visual presentation, reducing bias, and developing models with strong predictive accuracy and clinical applicability.