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Predictors of disease severity in children presenting from the community with febrile illnesses: a systematic review of prognostic studies
INTRODUCTION: Early identification of children at risk of severe febrile illness can optimise referral, admission and treatment decisions, particularly in resource-limited settings. We aimed to identify prognostic clinical and laboratory factors that predict progression to severe disease in febrile...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7818824/ https://www.ncbi.nlm.nih.gov/pubmed/33472837 http://dx.doi.org/10.1136/bmjgh-2020-003451 |
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author | Chandna, Arjun Tan, Rainer Carter, Michael Van Den Bruel, Ann Verbakel, Jan Koshiaris, Constantinos Salim, Nahya Lubell, Yoel Turner, Paul Keitel, Kristina |
author_facet | Chandna, Arjun Tan, Rainer Carter, Michael Van Den Bruel, Ann Verbakel, Jan Koshiaris, Constantinos Salim, Nahya Lubell, Yoel Turner, Paul Keitel, Kristina |
author_sort | Chandna, Arjun |
collection | PubMed |
description | INTRODUCTION: Early identification of children at risk of severe febrile illness can optimise referral, admission and treatment decisions, particularly in resource-limited settings. We aimed to identify prognostic clinical and laboratory factors that predict progression to severe disease in febrile children presenting from the community. METHODS: We systematically reviewed publications retrieved from MEDLINE, Web of Science and Embase between 31 May 1999 and 30 April 2020, supplemented by hand search of reference lists and consultation with an expert Technical Advisory Panel. Studies evaluating prognostic factors or clinical prediction models in children presenting from the community with febrile illnesses were eligible. The primary outcome was any objective measure of disease severity ascertained within 30 days of enrolment. We calculated unadjusted likelihood ratios (LRs) for comparison of prognostic factors, and compared clinical prediction models using the area under the receiver operating characteristic curves (AUROCs). Risk of bias and applicability of studies were assessed using the Prediction Model Risk of Bias Assessment Tool and the Quality In Prognosis Studies tool. RESULTS: Of 5949 articles identified, 18 studies evaluating 200 prognostic factors and 25 clinical prediction models in 24 530 children were included. Heterogeneity between studies precluded formal meta-analysis. Malnutrition (positive LR range 1.56–11.13), hypoxia (2.10–8.11), altered consciousness (1.24–14.02), and markers of acidosis (1.36–7.71) and poor peripheral perfusion (1.78–17.38) were the most common predictors of severe disease. Clinical prediction model performance varied widely (AUROC range 0.49–0.97). Concerns regarding applicability were identified and most studies were at high risk of bias. CONCLUSIONS: Few studies address this important public health question. We identified prognostic factors from a wide range of geographic contexts that can help clinicians assess febrile children at risk of progressing to severe disease. Multicentre studies that include outpatients are required to explore generalisability and develop data-driven tools to support patient prioritisation and triage at the community level. PROSPERO REGISTRATION NUMBER: CRD42019140542. |
format | Online Article Text |
id | pubmed-7818824 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-78188242021-01-25 Predictors of disease severity in children presenting from the community with febrile illnesses: a systematic review of prognostic studies Chandna, Arjun Tan, Rainer Carter, Michael Van Den Bruel, Ann Verbakel, Jan Koshiaris, Constantinos Salim, Nahya Lubell, Yoel Turner, Paul Keitel, Kristina BMJ Glob Health Original Research INTRODUCTION: Early identification of children at risk of severe febrile illness can optimise referral, admission and treatment decisions, particularly in resource-limited settings. We aimed to identify prognostic clinical and laboratory factors that predict progression to severe disease in febrile children presenting from the community. METHODS: We systematically reviewed publications retrieved from MEDLINE, Web of Science and Embase between 31 May 1999 and 30 April 2020, supplemented by hand search of reference lists and consultation with an expert Technical Advisory Panel. Studies evaluating prognostic factors or clinical prediction models in children presenting from the community with febrile illnesses were eligible. The primary outcome was any objective measure of disease severity ascertained within 30 days of enrolment. We calculated unadjusted likelihood ratios (LRs) for comparison of prognostic factors, and compared clinical prediction models using the area under the receiver operating characteristic curves (AUROCs). Risk of bias and applicability of studies were assessed using the Prediction Model Risk of Bias Assessment Tool and the Quality In Prognosis Studies tool. RESULTS: Of 5949 articles identified, 18 studies evaluating 200 prognostic factors and 25 clinical prediction models in 24 530 children were included. Heterogeneity between studies precluded formal meta-analysis. Malnutrition (positive LR range 1.56–11.13), hypoxia (2.10–8.11), altered consciousness (1.24–14.02), and markers of acidosis (1.36–7.71) and poor peripheral perfusion (1.78–17.38) were the most common predictors of severe disease. Clinical prediction model performance varied widely (AUROC range 0.49–0.97). Concerns regarding applicability were identified and most studies were at high risk of bias. CONCLUSIONS: Few studies address this important public health question. We identified prognostic factors from a wide range of geographic contexts that can help clinicians assess febrile children at risk of progressing to severe disease. Multicentre studies that include outpatients are required to explore generalisability and develop data-driven tools to support patient prioritisation and triage at the community level. PROSPERO REGISTRATION NUMBER: CRD42019140542. BMJ Publishing Group 2021-01-20 /pmc/articles/PMC7818824/ /pubmed/33472837 http://dx.doi.org/10.1136/bmjgh-2020-003451 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Original Research Chandna, Arjun Tan, Rainer Carter, Michael Van Den Bruel, Ann Verbakel, Jan Koshiaris, Constantinos Salim, Nahya Lubell, Yoel Turner, Paul Keitel, Kristina Predictors of disease severity in children presenting from the community with febrile illnesses: a systematic review of prognostic studies |
title | Predictors of disease severity in children presenting from the community with febrile illnesses: a systematic review of prognostic studies |
title_full | Predictors of disease severity in children presenting from the community with febrile illnesses: a systematic review of prognostic studies |
title_fullStr | Predictors of disease severity in children presenting from the community with febrile illnesses: a systematic review of prognostic studies |
title_full_unstemmed | Predictors of disease severity in children presenting from the community with febrile illnesses: a systematic review of prognostic studies |
title_short | Predictors of disease severity in children presenting from the community with febrile illnesses: a systematic review of prognostic studies |
title_sort | predictors of disease severity in children presenting from the community with febrile illnesses: a systematic review of prognostic studies |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7818824/ https://www.ncbi.nlm.nih.gov/pubmed/33472837 http://dx.doi.org/10.1136/bmjgh-2020-003451 |
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