Intravenous dexamethasone and peripheral nerve blocks: A systemic review and meta-analysis of randomized controlled trials

Systematic reviews should build on a protocol that describes the rationale, hypothesis, and planned methods of the review; few reviews report whether a protocol exists. Detailed, well-described protocols can facilitate the understanding and appraisal of the review methods, as well as the detection of modifications to methods and selective reporting in completed reviews. We describe the development of a reporting guideline, the Preferred Reporting Items for Systematic reviews and Meta-Analyses for Protocols 2015 (PRISMA-P 2015). PRISMA-P consists of a 17-item checklist intended to facilitate the preparation and reporting of a robust protocol for the systematic review. Funders and those commissioning reviews might consider mandating the use of the checklist to facilitate the submission of relevant protocol information in funding applications. Similarly, peer reviewers and editors can use the guidance to gauge the completeness and transparency of a systematic review protocol submitted for publication in a journal or other medium.

Background In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. Methods In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.’s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. Results We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. Conclusions In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different situations. Electronic supplementary material The online version of this article (doi:10.1186/1471-2288-14-135) contains supplementary material, which is available to authorized users.

During the past two decades, professional associations, accrediting bodies, and payors have made post-surgical pain treatment a high priority. In light of the disappointing findings in previous surveys, a survey was conducted to assess patient perceptions and characterize patient experiences/levels of satisfaction with post-surgical pain management. Survey included a random sample of US adults who had undergone surgery within 5 years from the survey date. Participants were asked about their concerns before surgery, severity of perioperative pain, pain treatments, perceptions about post-surgical pain and pain medications, and satisfaction with treatments they received. Of the 300 participants, ∼86% experienced pain after surgery; of these, 75% had moderate/extreme pain during the immediate post-surgical period, with 74% still experiencing these levels of pain after discharge. Post-surgical pain was the most prominent pre-surgical patient concern, and nearly half reported they had high/very high anxiety levels about pain before surgery. Approximately 88% received analgesic medications to manage pain; of these, 80% experienced adverse effects and 39% reported moderate/severe pain even after receiving their first dose. Key study limitations include the relatively small population size, potential for recall bias associated with the 14-month average time delay from surgery date to survey date, and the inability to account for influences of type of surgery and intraoperative anesthetic/analgesic use on survey results. Despite heightened awareness and clinical advancements in pain management, there has been little improvement in post-surgical analgesia as measured by this survey of post-surgical patients.