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      Comparison of different nonsteroidal anti-inflammatory drugs for cesarean section: a systematic review and network meta-analysis

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          Abstract

          Background

          Cesarean section is associated with moderate to severe pain and nonsteroidal anti-inflammatory drugs (NSAIDs) are commonly employed. The optimal NSAID, however, has not been elucidated. In this network meta-analysis and systematic review, we compared the influence of control and individual NSAIDs on the indices of analgesia, side effects, and quality of recovery.

          Methods

          CDSR, CINAHL, CRCT, Embase, LILACS, PubMed, and Web of Science were searched for randomized controlled trials comparing a specific NSAID to either control or another NSAID in elective or emergency cesarean section under general or neuraxial anesthesia. Network plots and league tables were constructed, and the quality of evidence was evaluated with Grading of Recommendations Assessment, Development and Evaluation (GRADE) analysis.

          Results

          We included 47 trials. Cumulative intravenous morphine equivalent consumption at 24 h, the primary outcome, was examined in 1,228 patients and 18 trials, and control was found to be inferior to diclofenac, indomethacin, ketorolac, and tenoxicam (very low quality evidence owing to serious limitations, imprecision, and publication bias). Indomethacin was superior to celecoxib for pain score at rest at 8–12 h and celecoxib + parecoxib, diclofenac, and ketorolac for pain score on movement at 48 h. In regard to the need for and time to rescue analgesia COX-2 inhibitors such as celecoxib were inferior to other NSAIDs.

          Conclusions

          Our review suggests the presence of minimal differences among the NSAIDs studied. Nonselective NSAIDs may be more effective than selective NSAIDs, and some NSAIDs such as indomethacin might be preferable to other NSAIDs.

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          Most cited references81

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          RoB 2: a revised tool for assessing risk of bias in randomised trials

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            Quantifying heterogeneity in a meta-analysis.

            The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.
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              Rayyan—a web and mobile app for systematic reviews

              Background Synthesis of multiple randomized controlled trials (RCTs) in a systematic review can summarize the effects of individual outcomes and provide numerical answers about the effectiveness of interventions. Filtering of searches is time consuming, and no single method fulfills the principal requirements of speed with accuracy. Automation of systematic reviews is driven by a necessity to expedite the availability of current best evidence for policy and clinical decision-making. We developed Rayyan (http://rayyan.qcri.org), a free web and mobile app, that helps expedite the initial screening of abstracts and titles using a process of semi-automation while incorporating a high level of usability. For the beta testing phase, we used two published Cochrane reviews in which included studies had been selected manually. Their searches, with 1030 records and 273 records, were uploaded to Rayyan. Different features of Rayyan were tested using these two reviews. We also conducted a survey of Rayyan’s users and collected feedback through a built-in feature. Results Pilot testing of Rayyan focused on usability, accuracy against manual methods, and the added value of the prediction feature. The “taster” review (273 records) allowed a quick overview of Rayyan for early comments on usability. The second review (1030 records) required several iterations to identify the previously identified 11 trials. The “suggestions” and “hints,” based on the “prediction model,” appeared as testing progressed beyond five included studies. Post rollout user experiences and a reflexive response by the developers enabled real-time modifications and improvements. The survey respondents reported 40% average time savings when using Rayyan compared to others tools, with 34% of the respondents reporting more than 50% time savings. In addition, around 75% of the respondents mentioned that screening and labeling studies as well as collaborating on reviews to be the two most important features of Rayyan. As of November 2016, Rayyan users exceed 2000 from over 60 countries conducting hundreds of reviews totaling more than 1.6M citations. Feedback from users, obtained mostly through the app web site and a recent survey, has highlighted the ease in exploration of searches, the time saved, and simplicity in sharing and comparing include-exclude decisions. The strongest features of the app, identified and reported in user feedback, were its ability to help in screening and collaboration as well as the time savings it affords to users. Conclusions Rayyan is responsive and intuitive in use with significant potential to lighten the load of reviewers.
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                Author and article information

                Journal
                Korean J Anesthesiol
                Korean J Anesthesiol
                KJA
                Korean Journal of Anesthesiology
                Korean Society of Anesthesiologists
                2005-6419
                2005-7563
                December 2023
                17 April 2023
                : 76
                : 6
                : 597-616
                Affiliations
                [1 ]Department of Anesthesia, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
                [2 ]Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
                [3 ]University of Arkansas for Medical Sciences Library, Little Rock, AR, USA
                [4 ]King’s College London, London, United Kingdom
                Author notes
                Corresponding author: Neel Desai, F.R.C.A Department of Anesthesia, Guy’s and St Thomas’ NHS Foundation Trust, Westminster Bridge Road, London SE1 7EH, London, United Kingdom Tel: +44-2071887188 Email: Neel.Desai@ 123456gstt.nhs.uk
                Author information
                http://orcid.org/0000-0002-3174-0517
                http://orcid.org/0000-0001-6679-0752
                http://orcid.org/0000-0002-7770-0289
                http://orcid.org/0000-0001-7070-2276
                http://orcid.org/0000-0002-8234-8611
                http://orcid.org/0000-0002-4919-4542
                http://orcid.org/0000-0001-7676-9375
                http://orcid.org/0000-0002-7298-9407
                Article
                kja-23014
                10.4097/kja.23014
                10718621
                37066603
                f422aa19-4a14-4d87-8c8d-85df208e9453
                Copyright © The Korean Society of Anesthesiologists, 2023

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 5 January 2023
                : 22 February 2023
                : 11 April 2023
                Categories
                Clinical Research Article

                Anesthesiology & Pain management
                analgesia,cesarean section,non-steroidal anti-inflammatory agents,obstetrical anesthesia,postoperative pain,systematic review

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