Meta-analysis of predictive symptoms for Ebola virus disease.
Introduction One of the leading challenges in the 2013-2016 West African Ebola virus disease (EVD) outbreak was how best to quickly identify patients with EVD, separating them from those without the disease, in order to maximise limited isolation bed capacity and keep health systems functioning. Met...
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ftdoajarticles:oai:doaj.org/article:4e78995457884ebbaa15a4a25881b8df 2023-05-15T15:09:34+02:00 Meta-analysis of predictive symptoms for Ebola virus disease. Vageesh Jain Andre Charlett Colin S Brown 2020-10-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0008799 https://doaj.org/article/4e78995457884ebbaa15a4a25881b8df EN eng Public Library of Science (PLoS) https://doi.org/10.1371/journal.pntd.0008799 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0008799 https://doaj.org/article/4e78995457884ebbaa15a4a25881b8df PLoS Neglected Tropical Diseases, Vol 14, Iss 10, p e0008799 (2020) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2020 ftdoajarticles https://doi.org/10.1371/journal.pntd.0008799 2022-12-31T07:50:09Z Introduction One of the leading challenges in the 2013-2016 West African Ebola virus disease (EVD) outbreak was how best to quickly identify patients with EVD, separating them from those without the disease, in order to maximise limited isolation bed capacity and keep health systems functioning. Methodology We performed a systematic literature review to identify all published data on EVD clinical symptoms in adult patients. Data was dual extracted, and random effects meta-analysis performed for each symptom to identify symptoms with the greatest risk for EVD infection. Results Symptoms usually presenting late in illness that were more than twice as likely to predict a diagnosis of Ebola, were confusion (pOR 3.04, 95% CI 2.18-4.23), conjunctivitis (2.90, 1.92-4.38), dysphagia (1.95, 1.13-3.35) and jaundice (1.86, 1.20-2.88). Early non-specific symptoms of diarrhoea (2.99, 2.00-4.48), fatigue (2.77, 1.59-4.81), vomiting (2.69, 1.76-4.10), fever (1.97, 1.10-4.52), muscle pain (1.65, 1.04-2.61), and cough (1.63, 1.24-2.14), were also strongly associated with EVD diagnosis. Conclusions The existing literature fails to provide a unified position on the symptoms most predictive of EVD, but highlights some early and late stage symptoms that in combination will be useful for future risk stratification. Confirmation of these findings across datasets (or ideally an aggregation of all individual patient data) will aid effective future clinical assessment, risk stratification tools and emergency epidemic response planning. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 14 10 e0008799 |
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Directory of Open Access Journals: DOAJ Articles |
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English |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Vageesh Jain Andre Charlett Colin S Brown Meta-analysis of predictive symptoms for Ebola virus disease. |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
Introduction One of the leading challenges in the 2013-2016 West African Ebola virus disease (EVD) outbreak was how best to quickly identify patients with EVD, separating them from those without the disease, in order to maximise limited isolation bed capacity and keep health systems functioning. Methodology We performed a systematic literature review to identify all published data on EVD clinical symptoms in adult patients. Data was dual extracted, and random effects meta-analysis performed for each symptom to identify symptoms with the greatest risk for EVD infection. Results Symptoms usually presenting late in illness that were more than twice as likely to predict a diagnosis of Ebola, were confusion (pOR 3.04, 95% CI 2.18-4.23), conjunctivitis (2.90, 1.92-4.38), dysphagia (1.95, 1.13-3.35) and jaundice (1.86, 1.20-2.88). Early non-specific symptoms of diarrhoea (2.99, 2.00-4.48), fatigue (2.77, 1.59-4.81), vomiting (2.69, 1.76-4.10), fever (1.97, 1.10-4.52), muscle pain (1.65, 1.04-2.61), and cough (1.63, 1.24-2.14), were also strongly associated with EVD diagnosis. Conclusions The existing literature fails to provide a unified position on the symptoms most predictive of EVD, but highlights some early and late stage symptoms that in combination will be useful for future risk stratification. Confirmation of these findings across datasets (or ideally an aggregation of all individual patient data) will aid effective future clinical assessment, risk stratification tools and emergency epidemic response planning. |
format |
Article in Journal/Newspaper |
author |
Vageesh Jain Andre Charlett Colin S Brown |
author_facet |
Vageesh Jain Andre Charlett Colin S Brown |
author_sort |
Vageesh Jain |
title |
Meta-analysis of predictive symptoms for Ebola virus disease. |
title_short |
Meta-analysis of predictive symptoms for Ebola virus disease. |
title_full |
Meta-analysis of predictive symptoms for Ebola virus disease. |
title_fullStr |
Meta-analysis of predictive symptoms for Ebola virus disease. |
title_full_unstemmed |
Meta-analysis of predictive symptoms for Ebola virus disease. |
title_sort |
meta-analysis of predictive symptoms for ebola virus disease. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2020 |
url |
https://doi.org/10.1371/journal.pntd.0008799 https://doaj.org/article/4e78995457884ebbaa15a4a25881b8df |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 14, Iss 10, p e0008799 (2020) |
op_relation |
https://doi.org/10.1371/journal.pntd.0008799 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0008799 https://doaj.org/article/4e78995457884ebbaa15a4a25881b8df |
op_doi |
https://doi.org/10.1371/journal.pntd.0008799 |
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PLOS Neglected Tropical Diseases |
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14 |
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10 |
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e0008799 |
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