Related Experiment Video
Updated: Mar 26, 2026

10:11
Modeling The Lifecycle Of Ebola Virus Under Biosafety Level 2 Conditions With Virus-like Particles Containing Tetracistronic Minigenomes
Published on: September 27, 2014
37.2K
Prognostic Indicators for Ebola Patient Survival
Emerging Infectious Diseases
|January 27, 2016
Summary
Viral load, indicated by PCR cycle threshold (Ct) values, significantly predicts survival in Ebola virus disease patients. Higher Ct values (lower viral load) correlate with better survival outcomes in Sierra Leone.
Area of Science:
- Infectious Diseases
- Virology
- Public Health
Background:
- Ebola virus disease (EVD) poses significant public health challenges.
- Predictive markers for EVD patient survival are crucial for clinical management.
- Early indicators can aid in resource allocation and patient care strategies.
Purpose of the Study:
- To evaluate the predictive value of two readily available indicators for survival in Ebola virus disease patients.
- To assess the association between time to healthcare admission and viral load (PCR Ct value) with EVD patient survival.
Main Methods:
- Retrospective analysis of 216 Ebola virus disease patients in Sierra Leone.
- Evaluation of time from symptom onset to healthcare facility admission.
- Assessment of quantitative real-time reverse transcription PCR (qRT-PCR) cycle threshold (Ct) values from the first positive blood sample as a surrogate for viral load.
Main Results:
- Time from symptom onset to healthcare facility admission did not show an association with survival.
- Viral load, indicated by qRT-PCR Ct values, was inversely associated with survival.
- Patients with higher Ct values (>24) had a significantly higher survival rate (87%) compared to those with lower Ct values (<24) (22%).
Conclusions:
- Quantitative real-time PCR cycle threshold (Ct) values are a strong predictor of survival in Ebola virus disease.
- Viral load, as determined by Ct values, is a more reliable prognostic indicator than time to admission.
- Ct values can assist clinicians in treatment decisions and managing patient and family expectations regarding prognosis.
