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关于个性化疼痛评估及多模式干预优化术后恢复的综合评述
Authors Xu J, Liu X, Zhao J, Zhao J, Li H, Ye H, Ai S
Received 7 January 2025
Accepted for publication 21 May 2025
Published 5 June 2025 Volume 2025:18 Pages 2791—2804
DOI http://doi.org/10.2147/JPR.S516249
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Jinlei Li
Jingying Xu,1,* Xiaona Liu,1,* Jinyan Zhao,1 Jingjing Zhao,2 Hao Li,1 Huanhuan Ye,2 Shuang Ai2
1Department 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; 2Department of Outpatient, Joint Logistics Support Force No. 964 Hospital of People’s Liberation Army of China, Changchun, Jilin, 130000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Shuang Ai, Email 124793685@qq.com
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.
Keywords: personalized pain assessment, multimodal interventions, postoperative recovery, pain management, enhanced recovery