A systematic review and meta-analysis of patient data from the West Africa (2013–16) Ebola virus disease epidemic

Abstract

Background: Over 28 000 individuals were infected with Ebola virus during the West Africa (2013e2016) epidemic, yet there has been criticism of the lack of robust clinical descriptions of Ebola virus disease (EVD) illness from that outbreak. Objectives: To perform a meta-analysis of published data from the epidemic to describe the clinical presentation, evolution of disease, and predictors of mortality in individuals with EVD. To assess the quality and utility of published data for clinical and public health decision-making. Data sources: Primary articles available in PubMed and published between January 2014 and May 2017. Eligibility: Studies that sequentially enrolled individuals hospitalized for EVD and that reported acute clinical outcomes. Methods: We performed meta-analyses using random-effect models and assessed heterogeneity using the I 2 method. We assessed data representativeness by comparing meta-analysis estimates with WHO aggregate data. We examined data utility by examining the availability and compatibility of data sets. Results: In all, 3653 articles were screened and 34 articles were included, representing 16 independent cohorts of patients (18 overlapping cohorts) and at least 6168 individuals. The pooled estimate for case fatality rate was 51% (95% CI 46%e56%). However, pooling of estimates for clinical presentation, progression, and predictors of mortality in individuals with EVD were hampered by significant heterogeneity, and inadequate data on clinical progression. Our assessment of data quality found that heterogeneity was largely unexplained, and data availability and compatibility were poor. Conclusions: We have quantified a missed opportunity to generate reliable estimates of the clinical manifestations of EVD during the West Africa epidemic. Clinical data standards and data capture platforms are urgently needed.

Treatment of Ebola-related critical illness

“…After exposure to Ebola virus, an incubation period of 3-21 days (mean 12.7, SD 4.3 days) [29] ensues where symptoms (Fig. 1) might present [30]. It is not uncommon for viral RNA to be undetectable by reverse transcriptase-polymerase chain reaction (RT-PCR) in the first 1-3 days after symptom onset.…”

“…Blue indicates a meta-analysis approximate with low or moderate heterogeneity, red is for a high heterogeneity of pooled estimates, and grey is the WHO reference data. Adapted from Rojek AM et al [30] Some patients will progress to the second phase with asthenia and gastro-intestinal illness, including nausea, anorexia, abdominal pain, odynophagia, emesis and then watery diarrhea. This stage can range from mild symptoms to a severe state of illness characterized by intravascular volume depletion and electrolyte derangement [6,32], hypotension, metabolic acidosis, hepatitis, pancreatitis, hypoglycemia and renal injury.…”

“…In the third phase of illness [4], multi-organ failure may occur, with acute kidney failure, hepatic failure, cardiac dysfunction and shock, altered level of consciousness, seizures, coagulopathy (petechiae, ecchymoses, at venipuncture sites and bleeding from mucosal membranes and peri-partum) or death [30][31][32][33].…”

Meta-analysis of predictive symptoms for Ebola virus disease

“…The existing literature explores the predictive value of individual and groups of symptoms for EVD, but often fails to reach consistent conclusions or does not compare symptoms across those with and without the disease [8][9][10][11]. We therefore aimed to conduct a systematic review and meta-analysis to aggregate available data on symptom predictors for EVD, to see if we could provide clinicians with a more robust guide to the most specific clinical features of EVD across several countries and settings.…”

Core Minimal Datasets to Advance Clinical Research for Priority Epidemic Diseases

“…While these data have their most important benefits in improving patient management (through better recognition of disease complications and informing supportive care) and public health control, patient-based data are also used to determine key parameters for clinical trials, such as the inclusion criteria, the nature and rate of clinically relevant outcomes, and potential confounders. We suggest that adoption of clinical case registries (such as those used for rare cancers) provides a feasible option to produce standardized clinical data that have multiple clinical, public health, and research benefits [6].…”