Neal, S;
Musorowegomo, D;
Gannon, H;
Cortina Borja, M;
Heys, M;
Chimhini, G;
Fitzgerald, F;
(2020)
Clinical prediction models to diagnose neonatal sepsis: a scoping review protocol.
BMJ Open
, 10
, Article e039712. 10.1136/bmjopen-2020-039712.
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Abstract
Introduction: Neonatal sepsis is responsible for significant morbidity and mortality worldwide. Diagnosis is often difficult due to non-specific clinical features and unavailability of laboratory tests in many low and middle-income countries. Clinical prediction models have the potential to improve diagnostic accuracy and rationalise antibiotic usage in neonatal units, which may result in reduced antimicrobial resistance and improved neonatal outcomes. In this paper, we outline our scoping review protocol to map the literature concerning clinical prediction models to diagnose neonatal sepsis. We aim to provide an overview of existing models and evidence underlying their use and compare prediction models between high-income and low and middle-income countries. Methods and analysis: The protocol was developed with reference to recommendations by the Joanna Briggs Institute. Searches will include six electronic databases (Ovid MEDLINE, Ovid Embase, Scopus, Web of Science, Global Index Medicus, and the Cochrane Library) supplemented by hand searching of reference lists and citation analysis on included studies. No time period restrictions will be applied but only studies published in English or Spanish will be included. Screening and data extraction will be performed independently by two reviewers, with a third reviewer used to resolve conflicts. The results will be reported by narrative synthesis in line with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Ethics and dissemination: The nature of the scoping review methodology means that this study does not require ethical approval. Results will be disseminated through a peer-reviewed publication and conference presentations, as well as through engagement with peers and relevant stakeholders.
| Type: | Article |
|---|---|
| Title: | Clinical prediction models to diagnose neonatal sepsis: a scoping review protocol |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1136/bmjopen-2020-039712 |
| Publisher version: | https://doi.org/10.1136/bmjopen-2020-039712 |
| Language: | English |
| Additional information: | Copyright: © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Infection, Immunity and Inflammation Dept UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Population, Policy and Practice Dept |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10104008 |
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