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Variables associated with unplanned general adult ICU admission in hospitalised patients: protocol for a systematic review

BACKGROUND: Failure to promptly identify deterioration in hospitalised patients is associated with delayed admission to intensive care units (ICUs) and poor outcomes. Existing vital sign-based Early Warning Score (EWS) algorithms do not have a sufficiently high positive predictive value to be used f...

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Detalles Bibliográficos
Autores principales: Malycha, James, Bonnici, Tim, Sebekova, Katarina, Petrinic, Tatjana, Young, Duncan, Watkinson, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5370455/
https://www.ncbi.nlm.nih.gov/pubmed/28351424
http://dx.doi.org/10.1186/s13643-017-0456-0
Descripción
Sumario:BACKGROUND: Failure to promptly identify deterioration in hospitalised patients is associated with delayed admission to intensive care units (ICUs) and poor outcomes. Existing vital sign-based Early Warning Score (EWS) algorithms do not have a sufficiently high positive predictive value to be used for automated activation of an ICU outreach team. Incorporating additional patient data might improve the predictive power of EWS algorithms; however, it is currently not known which patient data (or variables) are most predictive of ICU admission. We describe the protocol for a systematic review of variables associated with ICU admission. METHODS/DESIGN: MEDLINE, EMBASE, CINAHL and the Cochrane Library, including Cochrane Database of Systematic Reviews and the Cochrane Central Register of Controlled Trials (CENTRAL) will be searched for studies that assess the association of routinely recorded variables associated with subsequent unplanned ICU admission. Only studies involving adult patients admitted to general ICUs will be included. We will extract data relating to the statistical association between ICU admission and predictor variables, the quality of the studies and the generalisability of the findings. DISCUSSION: The results of this review will aid the development of future models which predict the risk of unplanned ICU admission. SYSTEMATIC REVIEW REGISTRATION: PROSPERO: CRD42015029617 ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13643-017-0456-0) contains supplementary material, which is available to authorized users.