Meta-analysis of predictive symptoms for Ebola virus disease.

ABSTRACT:

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), dy

SUBMITTER: Jain V 

PROVIDER: S-EPMC7641466 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature