Surgeons' experience and interaction effect in randomized controlled trials regarding new surgical procedures

2008 ◽  
Vol 199 (2) ◽  
pp. 108.e1-108.e6 ◽  
Author(s):  
Horace Roman ◽  
Loïc Marpeau ◽  
Thomas C. Hulsey
Keyword(s):  
Randomized Controlled Trials ◽  
Surgical Procedures ◽  
Interaction Effect ◽  
Controlled Trials ◽  
Randomized Controlled

scholarly journals The Effect of Intraoperative Methadone Compared to Morphine on Postsurgical Pain: A Meta-Analysis of Randomized Controlled Trials

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Mark C. Kendall ◽  
Lucas J. Alves ◽  
Kristi Pence ◽  
Taif Mukhdomi ◽  
Daniel Croxford ◽  
...  
Keyword(s):  
Postoperative Pain ◽  
Randomized Controlled Trials ◽  
Surgical Procedures ◽  
Meta Analysis ◽  
Analgesic Efficacy ◽  
Opioid Consumption ◽  
Cochrane Library ◽  
Postanesthesia Care Unit ◽  
Controlled Trials ◽  
Randomized Controlled

Background and Objectives. Methadone is commonly used in chronic pain, but it is not frequently used as an intraoperative analgesic. Several randomized studies have compared intraoperative methadone to morphine regarding postsurgical analgesia, but they have generated conflicting results. The aim of this investigation was to compare the analgesic efficacy of intraoperative methadone to morphine in patients undergoing surgical procedures. Methods. We performed a quantitative systematic review of randomized controlled trials in PubMed, Embase, Cochrane Library, and Google Scholar electronic databases. Meta-analysis was performed using the random effects model, weighted mean differences (WMD), standard deviation, 95% confidence intervals, and sample size. Methodological quality was evaluated using Cochrane Collaboration’s tool. Results. Seven randomized controlled trials evaluating 337 patients across different surgical procedures were included. The aggregated effect of intraoperative methadone on postoperative opioid consumption did not reveal a significant effect, WMD (95% CI) of −0.51 (−1.79 to 0.76), (P=0.43) IV morphine equivalents. In contrast, the effect of methadone on postoperative pain demonstrated a significant effect in the postanesthesia care unit, WMD (95% CI) of −1.11 (−1.88 to −0.33), P=0.005, and at 24 hours, WMD (95% CI) of −1.35 (−2.03 to −0.67), P<0.001. Conclusions. The use of intraoperative methadone reduces postoperative pain when compared to morphine. In addition, the beneficial effect of methadone on postoperative pain is not attributable to an increase in postsurgical opioid consumption. Our results suggest that intraoperative methadone may be a viable strategy to reduce acute pain in surgical patients.

The Effect of Partly Missing Covariates on Statistical Power in Randomized Controlled Trials With Discrete-Time Survival Endpoints

Methodology ◽  
2017 ◽  
Vol 13 (2) ◽  
pp. 41-60
Author(s):  
Shahab Jolani ◽  
Maryam Safarkhani
Keyword(s):  
Randomized Controlled Trials ◽  
Discrete Time ◽  
Treatment Effect ◽  
Survival Data ◽  
Controlled Trials ◽  
Missing Covariates ◽  
Indicator Method ◽  
Imputation Methods ◽  
Randomized Controlled ◽  
Baseline Covariates

Abstract. In randomized controlled trials (RCTs), a common strategy to increase power to detect a treatment effect is adjustment for baseline covariates. However, adjustment with partly missing covariates, where complete cases are only used, is inefficient. We consider different alternatives in trials with discrete-time survival data, where subjects are measured in discrete-time intervals while they may experience an event at any point in time. The results of a Monte Carlo simulation study, as well as a case study of randomized trials in smokers with attention deficit hyperactivity disorder (ADHD), indicated that single and multiple imputation methods outperform the other methods and increase precision in estimating the treatment effect. Missing indicator method, which uses a dummy variable in the statistical model to indicate whether the value for that variable is missing and sets the same value to all missing values, is comparable to imputation methods. Nevertheless, the power level to detect the treatment effect based on missing indicator method is marginally lower than the imputation methods, particularly when the missingness depends on the outcome. In conclusion, it appears that imputation of partly missing (baseline) covariates should be preferred in the analysis of discrete-time survival data.

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