Suppr超能文献

骨关节炎的疼痛评估:当前实践与未来前景,包括生物标志物和可穿戴技术的应用以及人工智能驱动的个性化医疗。

Pain Assessment in Osteoarthritis: Present Practices and Future Prospects Including the Use of Biomarkers and Wearable Technologies, and AI-Driven Personalized Medicine.

作者信息

Khan Shujaa T, Huffman Nick, Li Xiaojuan, Sharma Anukriti, Winalski Carl S, Ricchetti Eric T, Derwin Kathleen, Apte Suneel S, Rotroff Daniel, Saab Carl Y, Piuzzi Nicolas S

机构信息

Department of Orthopedic Surgery, Cleveland Clinic, Cleveland, Ohio, USA.

Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA.

出版信息

J Orthop Res. 2025 Jul;43(7):1217-1229. doi: 10.1002/jor.26082. Epub 2025 Apr 9.

Abstract

Osteoarthritis (OA) is a highly prevalent chronic joint disorder affecting ~600 million individuals worldwide and is characterized by complex pain mechanisms that significantly impair patient quality of life. Challenges exist in accurately assessing and measuring pain in OA due to variations in pain perception among individuals and the heterogeneous nature of the disease. Conventional pain assessment methods, such as patient-reported outcome measures and clinical evaluations, often fail to fully capture the heterogeneity of pain experiences among individuals with OA. This review will summarize and evaluate current methods of pain assessment in OA and highlight future directions for standardized pain assessment. We discuss the role of animal models in enhancing our understanding of OA pain pathophysiology and highlight the necessity of translational research to advance pain assessment strategies. Key challenges explored include identifying phenotypes of pain susceptibility, integrating biomarkers into clinical practice, and adopting personalized pain management approaches through the incorporation of multi-modal data and multilevel analysis. We underscore the imperative for continued innovation in pain assessment and management to improve outcomes for patients with OA.

摘要

骨关节炎(OA)是一种非常普遍的慢性关节疾病,全球约有6亿人受其影响,其特征是复杂的疼痛机制,严重损害患者的生活质量。由于个体之间疼痛感知的差异以及该疾病的异质性,在准确评估和测量骨关节炎疼痛方面存在挑战。传统的疼痛评估方法,如患者报告的结局指标和临床评估,往往无法充分捕捉骨关节炎患者疼痛体验的异质性。本综述将总结和评估目前骨关节炎疼痛评估的方法,并强调标准化疼痛评估的未来方向。我们讨论了动物模型在增强我们对骨关节炎疼痛病理生理学理解方面的作用,并强调了转化研究对推进疼痛评估策略的必要性。探讨的关键挑战包括确定疼痛易感性的表型、将生物标志物纳入临床实践,以及通过整合多模态数据和多层次分析采用个性化疼痛管理方法。我们强调在疼痛评估和管理方面持续创新的紧迫性,以改善骨关节炎患者的治疗效果。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验