个性化疼痛评估和多模式干预优化术后恢复的综合综述。

IF 2.5 3区 医学 Q2 CLINICAL NEUROLOGY
Journal of Pain Research Pub Date : 2025-06-05 eCollection Date: 2025-01-01 DOI:10.2147/JPR.S516249
Jingying Xu, Xiaona Liu, Jinyan Zhao, Jingjing Zhao, Hao Li, Huanhuan Ye, Shuang Ai
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引用次数: 0

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的发生风险。尽管具有重要意义,但传统的疼痛管理策略往往不能充分解决个体可变性和疼痛的多维性,从而限制了其有效性。为了解决这些局限性,我们设计了这一全面的叙述性综述,系统地总结了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以优化术后恢复。个性化疼痛评估,在生物心理社会模型的指导下,捕捉疼痛的生物学、心理学和社会维度,为患者需求提供更全面和个性化的评估。与此同时,结合药物和非药物策略的多模式干预,旨在同时针对多种疼痛机制,从而提高镇痛效果,同时最大限度地减少不良反应。新出现的证据表明,将个性化疼痛评估与多模式干预相结合可以显著改善临床结果,如术后疼痛评分减少约20-30%,住院时间缩短1-2天,阿片类药物消耗减少25-40%。值得注意的临床应用支持这些发现,包括使用动态疼痛监测设备,基于虚拟现实的治疗,以及促进康复的康复计划。在这些发现的基础上,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,并检查了与实施相关的实际挑战。并提出了未来的发展方向,包括开发人工智能驱动的疼痛评估工具,促进跨学科合作,建立标准化的临床方案。总的来说,这些进步支持个性化、多维策略的潜力,以改善术后结果和提高整体患者满意度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comprehensive Review on Personalized Pain Assessment and Multimodal Interventions for Postoperative Recovery Optimization.

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.

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来源期刊
Journal of Pain Research
Journal of Pain Research CLINICAL NEUROLOGY-
CiteScore
4.50
自引率
3.70%
发文量
411
审稿时长
16 weeks
期刊介绍: Journal of Pain Research is an international, peer-reviewed, open access journal that welcomes laboratory and clinical findings in the fields of pain research and the prevention and management of pain. Original research, reviews, symposium reports, hypothesis formation and commentaries are all considered for publication. Additionally, the journal now welcomes the submission of pain-policy-related editorials and commentaries, particularly in regard to ethical, regulatory, forensic, and other legal issues in pain medicine, and to the education of pain practitioners and researchers.
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