five

S1 Data -

收藏
NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://figshare.com/articles/dataset/S1_Data_-/27970464
下载链接
链接失效反馈
官方服务:
资源简介:
Background To improve perioperative pain management, several interventions have been suggested for the prevention of increased pain sensitivity caused by opioids (called opioid-induced hyperalgesia). It is currently unclear which intervention is the most effective or appropriate in preventing opioid-induced hyperalgesia. Remifentanil is the most investigated opioid causing opioid-induced hyperalgesia. Thus, to guide future research, we conducted a systematic review and a network meta-analysis of preclinical trials investigating pharmacological interventions for remifentanil-induced hyperalgesia. Methods To identify relevant articles, electronic database searches were conducted in Embase, PubMed, Web of Science, and Google Scholar. Study characteristics were extracted, and the risk of bias was evaluated. Studies were included in the network meta-analysis if they shared similar characteristics with at least one other study. The interventions were ranked based on P-scores. Results Overall, the 62 eligible trials tested 86 individual interventions and 6 combination interventions. Thirty-five studies eligible in the network meta-analysis formed five groups which were further divided into subgroups based on the quantitative sensory tests used. The best-ranked interventions within the subgroups were Anxa12-26, MRS2179, salicylaldehyde isonicotinoyl hydrazone (SIH), ANA-12, TDZD-8, ketamine, dexmedetomidine, JWH015, and the combination of KN93 and ketamine. Discussion The current literature is too heterogeneous to produce a clear answer on which intervention is the most effective in preventing remifentanil-induced hyperalgesia. Future research in this field should prioritise finding the most effective intervention over testing the efficacy of new options. The results of our work can be used in planning which comparisons should be included in new trials.
创建时间:
2024-12-05
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作