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      The Global Prevalence of Seborrheic Dermatitis : A Systematic Review and Meta-Analysis

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          Abstract

          Importance

          Seborrheic dermatitis is a prevalent chronic inflammatory skin disease, yet its global prevalence, pathogenesis, and epidemiology remain inadequately defined.

          Objective

          To provide a detailed estimation of the global prevalence of seborrheic dermatitis, analyze demographic variations, and explore differences in various settings.

          Data Sources

          Embase, PubMed, Scopus, and Cochrane Database of Systematic Reviews were searched from inception through October 2023.

          Study Selection

          Original investigations on seborrheic dermatitis prevalence were included after duplicate screening of titles, abstracts, and full articles, including only studies with clinician-diagnosed cases.

          Data Extraction and Synthesis

          Following PRISMA guidelines, data were extracted and quality was assessed independently by multiple reviewers. A random-effects model using restricted maximum likelihood was used for meta-analysis and subgroup analyses.

          Main Outcome and Measure

          The primary outcome was the pooled estimate of global seborrheic dermatitis prevalence.

          Results

          From 1574 identified articles, 121 studies were included, encompassing 1 260 163 individuals and revealing a pooled global seborrheic dermatitis prevalence of 4.38% (95% CI, 3.58%-5.17%), with significant heterogeneity ( I 2 = 99.94%). Subgroup analyses showed variations by age, with a higher prevalence in adults (5.64% [95% CI, 4.01%-7.27%]) compared to children (3.70% [95% CI, 2.69%-4.80%]) and neonates (0.23% [95% CI, 0.04%-0.43%]). Geographic analyses indicated variability, with the highest prevalence in South Africa (8.82% [95% CI, 3.00%-14.64%]) and the lowest in India (2.62% [95% CI, 1.33%-3.92%]).

          Conclusions and Relevance

          This comprehensive meta-analysis provides a detailed estimation of the global prevalence of seborrheic dermatitis, highlighting significant variability across different demographics and settings.

          Related collections

          Most cited references150

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          Is Open Access

          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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            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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              Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group.

              Because of the pressure for timely, informed decisions in public health and clinical practice and the explosion of information in the scientific literature, research results must be synthesized. Meta-analyses are increasingly used to address this problem, and they often evaluate observational studies. A workshop was held in Atlanta, Ga, in April 1997, to examine the reporting of meta-analyses of observational studies and to make recommendations to aid authors, reviewers, editors, and readers. Twenty-seven participants were selected by a steering committee, based on expertise in clinical practice, trials, statistics, epidemiology, social sciences, and biomedical editing. Deliberations of the workshop were open to other interested scientists. Funding for this activity was provided by the Centers for Disease Control and Prevention. We conducted a systematic review of the published literature on the conduct and reporting of meta-analyses in observational studies using MEDLINE, Educational Research Information Center (ERIC), PsycLIT, and the Current Index to Statistics. We also examined reference lists of the 32 studies retrieved and contacted experts in the field. Participants were assigned to small-group discussions on the subjects of bias, searching and abstracting, heterogeneity, study categorization, and statistical methods. From the material presented at the workshop, the authors developed a checklist summarizing recommendations for reporting meta-analyses of observational studies. The checklist and supporting evidence were circulated to all conference attendees and additional experts. All suggestions for revisions were addressed. The proposed checklist contains specifications for reporting of meta-analyses of observational studies in epidemiology, including background, search strategy, methods, results, discussion, and conclusion. Use of the checklist should improve the usefulness of meta-analyses for authors, reviewers, editors, readers, and decision makers. An evaluation plan is suggested and research areas are explored.
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                Author and article information

                Journal
                JAMA Dermatology
                JAMA Dermatol
                American Medical Association (AMA)
                2168-6068
                July 03 2024
                Affiliations
                [1 ]Chicago Medical School, Rosalind Franklin University of Medicine and Science, Chicago, Illinois
                [2 ]Feinberg School of Medicine, Northwestern University, Chicago, Illinois
                [3 ]College of Medicine, University of Illinois, Chicago
                [4 ]Center for Medical Dermatology and Immunology Research, Chicago, Illinois
                Article
                10.1001/jamadermatol.2024.1987
                38958996
                8405a2f7-eaf3-4ab6-8301-63f6bae9169f
                © 2024
                History

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