International journal of surgery (London, England) · 2025
Acute pain service for postoperative pain in adults: a network meta-analysis.
СтатьяNetwork Meta-AnalysisНазвание и аннотация: Перевод в очереди
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Chen Lu, Feng Xixia, Ye Ling, Yang Jiaqi, Zhou Ruihao, Qiu Yong, Chen Guo, Zhu Tao
Аннотация
BACKGROUND: Postoperative pain significantly impacts patients' quality of life and recovery. Although acute pain services (APS) have been implemented in many hospitals worldwide, no study has directly compared the efficacy of different APS subtypes in managing acute postoperative pain.
OBJECTIVE: This network meta-analysis aimed to evaluate the effectiveness of various APS models in alleviating postoperative pain in adults undergoing surgery.
METHODS: Four English-language databases (PubMed, Web of Science, Embase, and Cochrane Library) and three Chinese-language databases (CNKI, WANFANG, and SinoMed) were searched to identify randomized controlled trials (RCTs) that compared the efficacy of different pain management models for postoperative pain in adult patients. Statistical analyses were conducted using R version 4.4.2 and Stata version 18.
RESULTS: A total of 38 studies were included in this network meta-analysis. All APS subtypes demonstrated superior pain relief compared to the traditional ward doctor-nurse model. These included nurse-based anesthesiologist specialist-supervised APS (NBASS-APS; SMD: -1.99, 99% CI: -2.55, -1.43), nurse-based anesthesiologist-supervised APS (NBAS-APS; SMD: -1.44, 99% CI: -2.18, -0.70), pain management multidisciplinary team (PMDT; SMD: -1.31, 99% CI: -1.74, -0.87), and conventional APS (C-APS; SMD: -0.83, 99% CI: -1.43, -0.24). Surface under the cumulative ranking (SUCRA) analysis identified NBASS-APS as having the highest probability of achieving optimal pain relief (98.0%), followed by NBAS-APS (65.9%), PMDT (58.0%), C-APS (28.1%), and the traditional model (0.1%).
CONCLUSION: APS models are significantly more effective than the traditional ward doctor-nurse model in relieving postoperative pain, with NBASS-APS emerging as the most promising approach, followed by NBAS-APS, PMDT, and C-APS.
OBJECTIVE: This network meta-analysis aimed to evaluate the effectiveness of various APS models in alleviating postoperative pain in adults undergoing surgery.
METHODS: Four English-language databases (PubMed, Web of Science, Embase, and Cochrane Library) and three Chinese-language databases (CNKI, WANFANG, and SinoMed) were searched to identify randomized controlled trials (RCTs) that compared the efficacy of different pain management models for postoperative pain in adult patients. Statistical analyses were conducted using R version 4.4.2 and Stata version 18.
RESULTS: A total of 38 studies were included in this network meta-analysis. All APS subtypes demonstrated superior pain relief compared to the traditional ward doctor-nurse model. These included nurse-based anesthesiologist specialist-supervised APS (NBASS-APS; SMD: -1.99, 99% CI: -2.55, -1.43), nurse-based anesthesiologist-supervised APS (NBAS-APS; SMD: -1.44, 99% CI: -2.18, -0.70), pain management multidisciplinary team (PMDT; SMD: -1.31, 99% CI: -1.74, -0.87), and conventional APS (C-APS; SMD: -0.83, 99% CI: -1.43, -0.24). Surface under the cumulative ranking (SUCRA) analysis identified NBASS-APS as having the highest probability of achieving optimal pain relief (98.0%), followed by NBAS-APS (65.9%), PMDT (58.0%), C-APS (28.1%), and the traditional model (0.1%).
CONCLUSION: APS models are significantly more effective than the traditional ward doctor-nurse model in relieving postoperative pain, with NBASS-APS emerging as the most promising approach, followed by NBAS-APS, PMDT, and C-APS.