Association of clinical signs and symptoms of Ebola viral disease with case fatality: a systematic review and meta-analysis

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.

• Ebola viral disease
• clinical signs
• clinical symptoms
• mortality
• meta-analysis
• systematic review

Acknowledgement

We would like to acknowledge the Research Open Access Article Publishing (ROAAP) Fund of the University of Illinois at Chicago for financial support towards the open access publishing fee for this article. Dr. Srinivas Puli's assistance with statistics and study design.