Dong Yunxia, Chang Xiaohan
Department of Anesthesiology, Shengjing Hospital of China Medical University, Shenyang, China.
Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Front Pharmacol. 2021 Nov 17;12:684276. doi: 10.3389/fphar.2021.684276. eCollection 2021.
Due to the absence of direct comparisons of different therapeutic drugs in preventing opioid-induced cough (OIC) during the induction of general anesthesia, clinicians often faced difficulties in choosing the optimal drug for these patients. Hence, this network meta-analysis was conducted to solve this problem. Online databases, including Pubmed, Embase, Web of Science, Cochrane, and Google Scholar, were searched comprehensively to identify eligible randomized controlled trials (RCTs), up to March 15th, 2021. Within a Bayesian framework, network meta-analysis was performed by the "gemtc" version 0.8.2 package of R-3.4.0 software, and a pooled risk ratio (RR) associated with 95% credible interval (CrI) was calculated. A total of 20 RCTs were finally enrolled, and the overall heterogeneity for this study was low to moderate. Traditional pair-wise meta-analysis results indicated that all of the five drugs, namely, lidocaine, ketamine, dezocine, butorphanol, and dexmedetomidine could prevent OIC for four clinical outcomes, compared with the placebo (all < 0.05). Moreover, dezocine had the best effect, compared with that of the other drugs (all < 0.05). Network meta-analysis results suggested that the top three rank probabilities for four clinical outcomes from best to worst were dezocine, butorphanol, and ketamine based on individual/cumulative rank plots and surface under the cumulative ranking curve (SUCRA) probabilities. The node-splitting method indicated the consistency of the direct and indirect evidence. Our results indicated that all of these five drugs could prevent OIC compared with the placebo. Moreover, the top three rank probabilities for four clinical outcomes from best to worst were dezocine, butorphanol, and ketamine. Our results were anticipated to provide references for guiding clinical research, and further high-quality RCTs were required to verify our findings. [https://www.crd.york.ac.uk/prospero/], identifier [CRD42021243358].
由于在全身麻醉诱导期间缺乏不同治疗药物预防阿片类药物诱发咳嗽（OIC）的直接比较，临床医生在为这些患者选择最佳药物时常常面临困难。因此，开展了这项网状Meta分析以解决该问题。全面检索了包括Pubmed、Embase、Web of Science、Cochrane和谷歌学术在内的在线数据库，以识别符合条件的随机对照试验（RCT），检索截至2021年3月15日。在贝叶斯框架内，使用R-3.4.0软件的“gemtc”0.8.2版本包进行网状Meta分析，并计算了与95%可信区间（CrI）相关的合并风险比（RR）。最终共纳入20项RCT，本研究的总体异质性为低到中度。传统的成对Meta分析结果表明，与安慰剂相比，利多卡因、氯胺酮、地佐辛、布托啡诺和右美托咪定这五种药物均可预防OIC的四种临床结局（均P<0.05）。此外，与其他药物相比，地佐辛效果最佳（均P<0.05）。网状Meta分析结果表明，基于个体/累积排名图和累积排名曲线下面积（SUCRA）概率，四种临床结局从最佳到最差的前三位排序概率分别是地佐辛、布托啡诺和氯胺酮。节点拆分法表明直接证据和间接证据具有一致性。我们的结果表明，与安慰剂相比，这五种药物均可预防OIC。此外，四种临床结局从最佳到最差的前三位排序概率分别是地佐辛、布托啡诺和氯胺酮。预期我们的结果可为指导临床研究提供参考，还需要进一步的高质量RCT来验证我们的发现。[https://www.crd.york.ac.uk/prospero/]，标识符[CRD42021243358]
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