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      Effects of non-invasive brain stimulation in multiple sclerosis: systematic review and meta-analysis

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          Abstract

          Objective:

          The objective of this meta-analysis was to summarize evidence on the therapeutic effects of non-invasive brain stimulation (NIBS) on core symptoms of multiple sclerosis (MS). Specifically, findings from studies deploying transcranial direct current stimulation (tDCS) and repetitive transcranial magnetic stimulation (rTMS) protocols were summarized in this review.

          Methods:

          We systematically searched articles published in four databases, until 31 May 2021, which compared the effects of active tDCS or rTMS with sham intervention in MS patients. We used a random-effects model for this meta-analysis. Meta-regression and subgroup meta-analysis were used to examine the effects of stimulation dose and different stimulation protocols, respectively.

          Results:

          Twenty-five randomized controlled trials (RCTs) were included in this review, consisting of 19 tDCS and 6 rTMS studies. tDCS led to a significant and immediate reduction of fatigue with a large effect size (Hedges’s g = −0.870, 95% confidence intervals (CI) = [−1.225 to −0.458], number needed to treat (NNT) = 2). Particularly, a subgroup analysis showed that applying tDCS over the left DLPFC and bilateral S1 led to fatigue reductions compared to sham stimulation. Furthermore, tDCS had favorable effects on fatigue in MS patients with low physical disability but not those with high physical disability, and additionally improved cognitive function. Finally, whereas rTMS was observed to reduce muscle spasticity, these NIBS protocols showed no further effect on MS-associated pain and mood symptoms.

          Conclusion:

          tDCS in MS alleviates fatigue and improves cognitive function whereas rTMS reduces muscle spasticity. More high-quality studies are needed to substantiate the therapeutic effects of different NIBS protocols in MS.

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          Most cited references62

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          The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

          The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
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            Measuring inconsistency in meta-analyses.

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              Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range

              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.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: MethodologyRole: SoftwareRole: Writing original draftRole: Writing review editing
                Role: ConceptualizationRole: MethodologyRole: SoftwareRole: Writing original draft
                Role: ConceptualizationRole: MethodologyRole: SoftwareRole: Writing original draft
                Role: ResourcesRole: Writing review editing
                Role: ResourcesRole: Writing review editing
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Project administrationRole: SupervisionRole: Funding acquisitionRole: Writing review editing
                Journal
                Ther Adv Chronic Dis
                Ther Adv Chronic Dis
                TAJ
                sptaj
                Therapeutic Advances in Chronic Disease
                SAGE Publications (Sage UK: London, England )
                2040-6223
                2040-6231
                2 February 2022
                2022
                : 13
                : 20406223211069198
                Affiliations
                [1-20406223211069198]Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, SAR, China
                [2-20406223211069198]Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, SAR, China
                [3-20406223211069198]Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, SAR, China
                [4-20406223211069198]Department of Rehabilitation, Third Military Medical University Southwest Hospital, Chongqing, China
                [5-20406223211069198]Faculty of Health and Life Sciences, The Northumbria University Newcastle, Newcastle upon Tyne, UK
                [6-20406223211069198]Neurological Rehabilitation Center Rosenhügel, Vienna, Austria
                [7-20406223211069198]Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, SAR, 999077, China; Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria; The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Pokfulam, Hong Kong, SAR, China
                Author notes
                Author information
                https://orcid.org/0000-0002-3892-1804
                Article
                10.1177_20406223211069198
                10.1177/20406223211069198
                8814979
                35126965
                0a61099b-4f70-4165-aa54-bf33f39f1fe7
                © The Author(s), 2022

                This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ( https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                : 3 August 2021
                : 7 December 2021
                Funding
                Funded by: Hong Kong Research Grants Council, ;
                Award ID: 25100219
                Funded by: hong kong polytechnic university, FundRef https://doi.org/10.13039/501100004377;
                Categories
                Meta-Analysis
                Custom metadata
                January-December 2022
                ts1

                multiple sclerosis,repetitive transcranial magnetic stimulation,transcranial direct current stimulation,fatigue,meta-analysis

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