Development of a Prediction Model for Ebola Virus Disease: A Retrospective Study in Nzérékoré Ebola Treatment Center, Guinea

Hdl Handle:
http://hdl.handle.net/10144/618749
Title:
Development of a Prediction Model for Ebola Virus Disease: A Retrospective Study in Nzérékoré Ebola Treatment Center, Guinea
Authors:
Loubet, P; Palich, R; Kojan, R; Peyrouset, O; Danel, C; Nicholas, S; Conde, M; Porten, K; Augier, A; Yazdanpanah, Y
Journal:
The American Journal of Tropical Medicine and Hygiene
Abstract:
The 2014 Ebola epidemic has shown the importance of accurate and rapid triage tools for patients with suspected Ebola virus disease (EVD). Our objective was to create a predictive score for EVD. We retrospectively reviewed all suspected cases admitted to the Ebola treatment center (ETC) in Nzérékoré, Guinea, between December 2, 2014, and February 23, 2015. We used a multivariate logistic regression model to identify clinical and epidemiological factors associated with EVD, which were used to create a predictive score. A bootstrap sampling method was applied to our sample to determine characteristics of the score to discriminate EVD. Among the 145 patients included in the study (48% male, median age 29 years), EVD was confirmed in 76 (52%) patients. One hundred and eleven (77%) patients had at least one epidemiological risk factor. Optimal cutoff value of fever to discriminate EVD was 38.5°C. After adjustment on presence of a risk factor, temperature higher than 38.5°C (odds ratio [OR] = 18.1, 95% confidence interval [CI] = 7.6-42.9), and anorexia (OR = 2.5, 95% CI = 1.1-6.1) were independently associated with EVD. The score had an area under curve of 0.85 (95% CI = 0.78-0.91) for the prediction of laboratory-confirmed EVD. Classification of patients in a high-risk group according to the score had a lower sensitivity (71% versus 86%) but higher specificity (85% versus 41%) than the existing World Health Organization algorithm. This score, which requires external validation, may be used in high-prevalence settings to identify different levels of risk in EVD suspected patients and thus allow a better orientation in different wards of ETC.
Publisher:
American Society of Tropical Medicine and Hygiene
Issue Date:
7-Dec-2016
URI:
http://hdl.handle.net/10144/618749
DOI:
10.4269/ajtmh.16-0026
PubMed ID:
27928085
Additional Links:
http://www.ajtmh.org
Submitted date:
2016-12-21
Language:
en
ISSN:
1476-1645
Appears in Collections:
Other Diseases

Full metadata record

DC FieldValue Language
dc.contributor.authorLoubet, Pen
dc.contributor.authorPalich, Ren
dc.contributor.authorKojan, Ren
dc.contributor.authorPeyrouset, Oen
dc.contributor.authorDanel, Cen
dc.contributor.authorNicholas, Sen
dc.contributor.authorConde, Men
dc.contributor.authorPorten, Ken
dc.contributor.authorAugier, Aen
dc.contributor.authorYazdanpanah, Yen
dc.date.accessioned2017-01-12T21:03:37Z-
dc.date.available2017-01-12T21:03:37Z-
dc.date.issued2016-12-07-
dc.date.submitted2016-12-21-
dc.identifier.citationDevelopment of a Prediction Model for Ebola Virus Disease: A Retrospective Study in Nzérékoré Ebola Treatment Center, Guinea. 2016, 95 (6):1362-1367 Am. J. Trop. Med. Hyg.en
dc.identifier.issn1476-1645-
dc.identifier.pmid27928085-
dc.identifier.doi10.4269/ajtmh.16-0026-
dc.identifier.urihttp://hdl.handle.net/10144/618749-
dc.description.abstractThe 2014 Ebola epidemic has shown the importance of accurate and rapid triage tools for patients with suspected Ebola virus disease (EVD). Our objective was to create a predictive score for EVD. We retrospectively reviewed all suspected cases admitted to the Ebola treatment center (ETC) in Nzérékoré, Guinea, between December 2, 2014, and February 23, 2015. We used a multivariate logistic regression model to identify clinical and epidemiological factors associated with EVD, which were used to create a predictive score. A bootstrap sampling method was applied to our sample to determine characteristics of the score to discriminate EVD. Among the 145 patients included in the study (48% male, median age 29 years), EVD was confirmed in 76 (52%) patients. One hundred and eleven (77%) patients had at least one epidemiological risk factor. Optimal cutoff value of fever to discriminate EVD was 38.5°C. After adjustment on presence of a risk factor, temperature higher than 38.5°C (odds ratio [OR] = 18.1, 95% confidence interval [CI] = 7.6-42.9), and anorexia (OR = 2.5, 95% CI = 1.1-6.1) were independently associated with EVD. The score had an area under curve of 0.85 (95% CI = 0.78-0.91) for the prediction of laboratory-confirmed EVD. Classification of patients in a high-risk group according to the score had a lower sensitivity (71% versus 86%) but higher specificity (85% versus 41%) than the existing World Health Organization algorithm. This score, which requires external validation, may be used in high-prevalence settings to identify different levels of risk in EVD suspected patients and thus allow a better orientation in different wards of ETC.en
dc.language.isoenen
dc.publisherAmerican Society of Tropical Medicine and Hygieneen
dc.relation.urlhttp://www.ajtmh.orgen
dc.rightsArchived with thanks to The American Journal of Tropical Medicine and Hygieneen
dc.titleDevelopment of a Prediction Model for Ebola Virus Disease: A Retrospective Study in Nzérékoré Ebola Treatment Center, Guineaen
dc.identifier.journalThe American Journal of Tropical Medicine and Hygieneen

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