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Sepsis prediction during outbreaks at neonatal intensive care units through body surface screening for Gram-negative bacteria: systematic review and meta-analysis

OBJECTIVE: This systematic review focusses on the prognostic accuracy of neonatal body surface screening during outbreaks caused by Gram-negative bacteria for prediction of sepsis. In a previous systematic review we reported that only limited evidence of very low quality exists regarding the predict...

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Autores principales: Harder, Thomas, Haller, Sebastian, Eckmanns, Tim, Seidel, Juliane
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6303936/
https://www.ncbi.nlm.nih.gov/pubmed/30577822
http://dx.doi.org/10.1186/s13104-018-4033-y
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author Harder, Thomas
Haller, Sebastian
Eckmanns, Tim
Seidel, Juliane
author_facet Harder, Thomas
Haller, Sebastian
Eckmanns, Tim
Seidel, Juliane
author_sort Harder, Thomas
collection PubMed
description OBJECTIVE: This systematic review focusses on the prognostic accuracy of neonatal body surface screening during outbreaks caused by Gram-negative bacteria for prediction of sepsis. In a previous systematic review we reported that only limited evidence of very low quality exists regarding the predictive value of this screening under routine conditions. We aimed to investigate whether this is different in outbreak settings. RESULTS: We identified five studies performed during outbreaks in three countries, comprising a total of 316 infants. All studies were at high risk of bias. In outbreak settings, pooled sensitivity of body surface screening to predict sepsis was 98% (95 CI 60 to 100%), while pooled specificity was 26% (95% CI 0.5 to 96%). Evidence quality was low for all outcomes. Extending a previously published systematic review, we show here that in contrast to routine settings sensitivity of body surface screening for sepsis prediction is very high, while specificity is still insufficient. Surface screening appears to be a useful component of bundles of interventions used during outbreaks, but the evidence base is still limited. PROSPERO Registration Number: CRD42016036664. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13104-018-4033-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-63039362018-12-31 Sepsis prediction during outbreaks at neonatal intensive care units through body surface screening for Gram-negative bacteria: systematic review and meta-analysis Harder, Thomas Haller, Sebastian Eckmanns, Tim Seidel, Juliane BMC Res Notes Research Note OBJECTIVE: This systematic review focusses on the prognostic accuracy of neonatal body surface screening during outbreaks caused by Gram-negative bacteria for prediction of sepsis. In a previous systematic review we reported that only limited evidence of very low quality exists regarding the predictive value of this screening under routine conditions. We aimed to investigate whether this is different in outbreak settings. RESULTS: We identified five studies performed during outbreaks in three countries, comprising a total of 316 infants. All studies were at high risk of bias. In outbreak settings, pooled sensitivity of body surface screening to predict sepsis was 98% (95 CI 60 to 100%), while pooled specificity was 26% (95% CI 0.5 to 96%). Evidence quality was low for all outcomes. Extending a previously published systematic review, we show here that in contrast to routine settings sensitivity of body surface screening for sepsis prediction is very high, while specificity is still insufficient. Surface screening appears to be a useful component of bundles of interventions used during outbreaks, but the evidence base is still limited. PROSPERO Registration Number: CRD42016036664. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13104-018-4033-y) contains supplementary material, which is available to authorized users. BioMed Central 2018-12-22 /pmc/articles/PMC6303936/ /pubmed/30577822 http://dx.doi.org/10.1186/s13104-018-4033-y Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Note
Harder, Thomas
Haller, Sebastian
Eckmanns, Tim
Seidel, Juliane
Sepsis prediction during outbreaks at neonatal intensive care units through body surface screening for Gram-negative bacteria: systematic review and meta-analysis
title Sepsis prediction during outbreaks at neonatal intensive care units through body surface screening for Gram-negative bacteria: systematic review and meta-analysis
title_full Sepsis prediction during outbreaks at neonatal intensive care units through body surface screening for Gram-negative bacteria: systematic review and meta-analysis
title_fullStr Sepsis prediction during outbreaks at neonatal intensive care units through body surface screening for Gram-negative bacteria: systematic review and meta-analysis
title_full_unstemmed Sepsis prediction during outbreaks at neonatal intensive care units through body surface screening for Gram-negative bacteria: systematic review and meta-analysis
title_short Sepsis prediction during outbreaks at neonatal intensive care units through body surface screening for Gram-negative bacteria: systematic review and meta-analysis
title_sort sepsis prediction during outbreaks at neonatal intensive care units through body surface screening for gram-negative bacteria: systematic review and meta-analysis
topic Research Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6303936/
https://www.ncbi.nlm.nih.gov/pubmed/30577822
http://dx.doi.org/10.1186/s13104-018-4033-y
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