Does Ondansetron Modify Sympathectomy Due to Subarachnoid Anesthesia?: Meta-analysis, Meta-regression, and Trial Sequential Analysis

Abstract

Background: Disagreement among many underpowered studies has led to an equivocal understanding of the efficacy of the 5-HT3 antagonist ondansetron in preventing the consequences of sympathectomy after subarachnoid anesthesia. The authors assessed the efficacy of ondansetron with respect to the overall quality and statistical power of the meta-analyses.

Methods: The authors used a standard and a newer method of meta-analysis, trial sequential analysis (TSA), to estimate adjusted CIs based on how much information has been accrued. They also used random-effects meta-analyses techniques, small trial bias assessment, selection models, sensitivity analyses, and the Grading of Recommendations on Assessment, Development, and Evaluation system. These results from the aforementioned techniques were compared, and importance of consideration of these factors was discussed.

Results: Fourteen randomized placebo-controlled trials (1,045 subjects) were identified and analyzed. By using conventional meta-analyses, the authors determined that ondansetron was associated with reduction in the incidence of hypotension (relative risk = 0.62 [95% CI, 0.46 to 0.83], P = 0.001; TSA-adjusted CI, 0.34 to 1.12; I = 60%, P = 0.002) and bradycardia (relative risk = 0.44 [95% CI, 0.26 to 0.73], P = 0.001; TSA-adjusted CI, 0.05 to 3.85; I = 0%, P = 0.84). However, the authors found indications of bias among these trials. TSAs demonstrated that the meta-analysis lacked adequate information size and did not achieve statistical significance when adjusted for sparse data and repetitive testing. The Grading of Recommendations on Assessment, Development, and Evaluation system showed that the results had low to very low quality of evidence.

Conclusions: The analyses fail to confirm evidence that ondansetron reduces the incidence of hypotension and bradycardia after subarachnoid anesthesia due to the risk of bias and information sizes less than the required. As results from meta-analysis are given significant weight, it is important to carefully evaluate the quality of the evidence that is input.