Rapid Decision Algorithm for Patient Triage during Ebola Outbreaks.

Algorithm Democratic Republic of the Congo Ebola clinical signs contact epidemics exposure outbreaks predictors symptomatology symptoms triage

Journal

Emerging infectious diseases
ISSN: 1080-6059
Titre abrégé: Emerg Infect Dis
Pays: United States
ID NLM: 9508155

Informations de publication

Date de publication:
Nov 2024
Historique:
medline: 25 10 2024
pubmed: 24 10 2024
entrez: 24 10 2024
Statut: ppublish

Résumé

The low specificity of Ebola virus disease clinical signs increases the risk for nosocomial transmission to patients and healthcare workers during outbreaks. Reducing this risk requires identifying patients with a high likelihood of Ebola virus infection. Analyses of retrospective data from patients suspected of having Ebola virus infection identified 13 strong predictors and time from disease onset as constituents of a prediction score for Ebola virus disease. We also noted 4 highly predictive variables that could distinguish patients at high risk for infection, independent of their scores. External validation of this algorithm on retrospective data revealed the probability of infection continuously increased with the score.

Identifiants

pubmed: 39447210
doi: 10.3201/eid3011.231650
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-11

Auteurs

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Classifications MeSH