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      Neonatal sepsis and its predictors in Ethiopia: umbrella reviews of a systematic review and meta-analysis, 2023

      review-article
      , MSc a , , , PhD b , , MSc a
      Annals of Medicine and Surgery
      Lippincott Williams & Wilkins
      Ethiopia, meta-analysis, neonatal sepsis, newborns, systematic review

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          Abstract

          Background:

          Although neonatal sepsis is acknowledged as the primary cause of newborn death in Ethiopia, data on its impact at the national level are limited. Strong supporting data are required to demonstrate how this affects neonatal health. This umbrella study was conducted to determine the overall prevalence of newborn sepsis and its relationship with maternal and neonatal factors.

          Methods:

          This umbrella review included five articles from various databases. The AMSTAR-2 method was used to assess the quality of included systematic review and meta-analysis studies. STATA Version 18 software was used for statistical analysis. A random-effects model was used to estimate the overall effects.

          Results:

          In this umbrella review, 9032 neonates with an outcome of interest were included. The overall pooled prevalence of neonatal sepsis was 45% (95% CI: 39–51%; I 2=99.34). The overall pooled effect size showed that prematurity was significantly associated with neonatal sepsis [odds ratio=3.11 (95% CI: 2.22–3.99)]. Furthermore, maternal factors are strongly associated with neonatal sepsis.

          Conclusions:

          Nearly half of Ethiopian neonates are affected by neonatal sepsis. It is critical to reduce premature birth, low birth weight, and preterm membrane rupture to reduce the incidence of neonatal sepsis. Furthermore, it is preferable to design and strengthen policies and programs aimed at improving maternal nutritional status and treating maternal infections, which all contribute to lowering the burden of neonatal sepsis.

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          Most cited references59

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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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            AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both

            The number of published systematic reviews of studies of healthcare interventions has increased rapidly and these are used extensively for clinical and policy decisions. Systematic reviews are subject to a range of biases and increasingly include non-randomised studies of interventions. It is important that users can distinguish high quality reviews. Many instruments have been designed to evaluate different aspects of reviews, but there are few comprehensive critical appraisal instruments. AMSTAR was developed to evaluate systematic reviews of randomised trials. In this paper, we report on the updating of AMSTAR and its adaptation to enable more detailed assessment of systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. With moves to base more decisions on real world observational evidence we believe that AMSTAR 2 will assist decision makers in the identification of high quality systematic reviews, including those based on non-randomised studies of healthcare interventions.
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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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                Author and article information

                Contributors
                Journal
                Ann Med Surg (Lond)
                Ann Med Surg (Lond)
                MS9
                Annals of Medicine and Surgery
                Lippincott Williams & Wilkins (Hagerstown, MD )
                2049-0801
                February 2024
                11 December 2023
                : 86
                : 2
                : 994-1002
                Affiliations
                [a ]School of Nursing and Midwifery
                [b ]School of Public Health, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia
                Author notes
                [* ]Corresponding author. Address: Haramaya University College of Health and Medical Science, Harar, Ethiopia; Institutional link: www.haramaya.edu.et. Tel: +251 910 005 436; fax: 235. E-mail: addiseyeberu@ 123456gmail.com (A. Eyeberu).
                Article
                AMSU-D-23-02020 00052
                10.1097/MS9.0000000000001619
                10849430
                38333239
                c4436407-9fbe-4f36-8bfe-a57ea28a2b8b
                Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.

                This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0/

                History
                : 13 September 2023
                : 3 December 2023
                Categories
                Reviews
                Custom metadata
                TRUE

                ethiopia,meta-analysis,neonatal sepsis,newborns,systematic review

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