Comparison of Five Prophylactically Intravenous Drugs in Preventing Opioid-Induced Cough: A Bayesian Network Meta-Analysis of Randomized Controlled Trials

Abstract

Background: 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. Methods: 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. Results: 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 p-values < 0.05). Moreover, dezocine had the best effect, compared with that of the other drugs (all p-values < 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. Conclusions: 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. Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/], identifier [CRD42021243358].

Keywords: drugs; network meta-analysis; opioid-induced cough; pharmacological interventions; randomized controlled trials.

FIGURE 1

Flow diagram of the literature selection process.

FIGURE 2

Network structure diagrams. (A) Incidence of OIC; (B) Mild severity of OIC; (C) Moderate severity of OIC; and (D) Severe severity of OIC. The numbers showed the number of direct comparisons. Line thicknesses were proportional to the number of direct comparisons. Circle diameters were proportional to the treatment numbers.

FIGURE 3

Efficacy of different comparisons of drugs by RRs and corresponding 95% CrIs; (A) Incidence of OIC; (B) Mild severity of OIC; (C) Moderate severity of OIC; and (D) Severe severity of OIC. All results were displayed as the ratio of the Y axis versus X axis. Bold fonts indicated p-value < 0.05.

FIGURE 4

Heterogeneity between different comparisons of drugs. (A) Incidence of OIC; (B) Mild severity of OIC; (C) Moderate severity of OIC; and (D) Severe severity of OIC.

FIGURE 5

Individual rank plot for four clinical outcomes. (A) Incidence of OIC; (B) Mild severity of OIC; (C) Moderate severity of OIC; and (D) Severe severity of OIC.

FIGURE 6

Cumulative rank plot for four clinical outcomes. (A) Incidence of OIC; (B) Mild severity of OIC; (C) Moderate severity of OIC; and (D) Severe severity of OIC.

FIGURE 7

Surface under the cumulative ranking curve (SUCRA) probabilities of different drugs for four clinical outcomes. (A) Incidence of OIC; (B) Mild severity of OIC; (C) Moderate severity of OIC; and (D) Severe severity of OIC.

FIGURE 8

Node-splitting method in comparisons between direct and indirect evidence. (A) Incidence of OIC; (B) Mild severity of OIC; (C) Moderate severity of OIC; and (D) Severe severity of OIC.