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关于个性化疼痛评估及多模式干预以优化术后恢复的综合综述

Comprehensive Review on Personalized Pain Assessment and Multimodal Interventions for Postoperative Recovery Optimization.

作者信息

Xu Jingying, Liu Xiaona, Zhao Jinyan, Zhao Jingjing, Li Hao, Ye Huanhuan, Ai Shuang

机构信息

Department of Rehabilitation Medicine, Joint Logistics Support Force No. 964 Hospital of People's Liberation Army of China, Changchun, Jilin, 130000, People's Republic of China.

Department of Outpatient, Joint Logistics Support Force No. 964 Hospital of People's Liberation Army of China, Changchun, Jilin, 130000, People's Republic of China.

出版信息

J Pain Res. 2025 Jun 5;18:2791-2804. doi: 10.2147/JPR.S516249. eCollection 2025.

Abstract

Postoperative pain management is an important determinant of patient recovery, as it directly influences rehabilitation efficiency, hospitalization duration, and the risk of postoperative complications. Despite its significance, traditional pain management strategies often fail to adequately address individual variability and the multidimensional nature of pain, thereby limiting their effectiveness. To address these limitations, we designed this comprehensive narrative review to systematically summarize relevant literature published between 2000 and 2024, from databases such as PubMed and Web of Science, with a particular focus on personalized pain assessment and multimodal interventions to optimize postoperative recovery. Personalized pain assessment, guided by the biopsychosocial model, captures the biological, psychological, and social dimensions of pain, offering a more comprehensive and individualized evaluation of patient needs. In parallel, multimodal interventions, which integrate pharmacological and non-pharmacological strategies, are designed to target multiple pain mechanisms simultaneously, thereby enhancing analgesic efficacy while minimizing adverse effects. Emerging evidence indicates that combining personalized pain assessment with multimodal interventions can significantly improve clinical outcomes, as demonstrated by reductions in postoperative pain scores by approximately 20-30%, shorter hospital stays by 1-2 days, and decreased opioid consumption by 25-40%. Notable clinical applications supporting these findings include the use of dynamic pain monitoring devices, virtual reality-based therapies, and prehabilitation programs to facilitate recovery. Building upon these findings, this review further discusses the theoretical foundations underlying personalized pain management, explores its clinical applications, and examines the practical challenges associated with its implementation. Additionally, future directions are proposed, including the development of AI-driven pain assessment tools, the promotion of interdisciplinary collaboration, and the establishment of standardized clinical protocols. Collectively, these advancements support the potential of personalized, multidimensional strategies to improve postoperative outcomes and enhance overall patient satisfaction.

摘要

术后疼痛管理是患者康复的重要决定因素,因为它直接影响康复效率、住院时间和术后并发症风险。尽管其意义重大,但传统的疼痛管理策略往往无法充分应对个体差异和疼痛的多维度性质,从而限制了它们的有效性。为了解决这些局限性,我们设计了这篇综合性叙述性综述,系统地总结2000年至2024年间发表的相关文献,这些文献来自PubMed和Web of Science等数据库,特别关注个性化疼痛评估和多模式干预措施,以优化术后康复。以生物心理社会模型为指导的个性化疼痛评估涵盖了疼痛的生物学、心理学和社会维度,能对患者需求进行更全面、个性化的评估。与此同时,整合药物和非药物策略的多模式干预措施旨在同时针对多种疼痛机制,从而提高镇痛效果,同时将不良反应降至最低。新出现的证据表明,将个性化疼痛评估与多模式干预措施相结合可显著改善临床结果,术后疼痛评分降低约20%-30%、住院时间缩短1-2天以及阿片类药物消耗量减少25%-40%就证明了这一点。支持这些发现的显著临床应用包括使用动态疼痛监测设备、虚拟现实疗法和术前康复计划以促进康复。基于这些发现,本综述进一步讨论了个性化疼痛管理的理论基础,探讨了其临床应用,并审视了与实施相关的实际挑战。此外,还提出了未来的方向,包括开发人工智能驱动的疼痛评估工具、促进跨学科合作以及建立标准化临床方案。总体而言,这些进展支持了个性化、多维度策略在改善术后结果和提高患者总体满意度方面的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44e1/12147818/ec8d860a866e/JPR-18-2791-g0001.jpg

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