association of clinical signs and symptoms of ebola viral disease with case fatality: a systematic review and meta-analysis
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2015
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Abstract
Background: Ebola virus disease (EVD) is a public health emergency of international concern. There is limited laboratory and clinical data available on patients with EVD. This is a meta-analysis to assess the utility of clinical signs, symptoms, and laboratory data in predicting mortality in EVD. Aim: To assess the utility of clinical signs, symptoms, and laboratory data in predicting mortality in EVD. Method:
Study selection criterion: EVD articles with more than 35 EVD cases that described the clinical features were included. Data collection and extraction: Articles were searched in Medline, PubMed, Ovid journals, and CDC and WHO official websites. Statistical methods: Pooled proportions were calculated using DerSimonian Laird method (random effects model). Results: Initial search identified 634 reference articles, of which 67 were selected and reviewed. Data were extracted from 10 articles (N=5,792) of EVD which met the inclusion criteria. Bleeding events (64.5% vs. 25.1%), abdominal pain (58.3% vs. 37.5%), vomiting (60.8% vs. 31.7%), diarrhea (69.9% vs. 37.8%), cough (31.6% vs. 22.3%), sore throat (47.7% vs. 19.8%), and conjunctivitis (39.3% vs. 20.3%) were more often present in pooled proportion of fatal cases as compared to EVD survivors. Conclusions: Clinical features of EVD that may be associated with higher mortality include bleeding events, vomiting, diarrhea, abdominal pain, cough, sore throat, and conjunctivitis. These patients should be identified promptly, and appropriate management should be instituted immediately.
| Reference Key |
moole2015journalassociation
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| Authors | ;Harsha Moole;Swetha Chitta;Darlyn Victor;Manasa Kandula;Vishnu Moole;Harshavardhan Ghadiam;Anusha Akepati;Charan Yerasi;Achuta Uppu;Sowmya Dharmapuri;Raghuveer Boddireddy;Jacqueline Fischer;Teresa Lynch |
| Journal | Mathematical biosciences |
| Year | 2015 |
| DOI |
10.3402/jchimp.v5.28406
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| URL | |
| Keywords |
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