Title |
Development of a Pediatric Ebola Predictive Score, Sierra Leone - Volume 24, Number 2—February 2018 - Emerging Infectious Diseases journal - CDC
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Published in |
Emerging Infectious Diseases, February 2018
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DOI | 10.3201/eid2402.171018 |
Pubmed ID | |
Authors |
Felicity Fitzgerald, Kevin Wing, Asad Naveed, Musa Gbessay, J.C.G. Ross, Francesco Checchi, Daniel Youkee, Mohamed Boie Jalloh, David E. Baion, Ayeshatu Mustapha, Hawanatu Jah, Sandra Lako, Shefali Oza, Sabah Boufkhed, Reynold Feury, Julia Bielicki, Elizabeth Williamson, Diana M. Gibb, Nigel Klein, Foday Sahr, Shunmay Yeung |
Abstract |
We compared children who were positive for Ebola virus disease (EVD) with those who were negative to derive a pediatric EVD predictor (PEP) score. We collected data on all children <13 years of age admitted to 11 Ebola holding units in Sierra Leone during August 2014-March 2015 and performed multivariable logistic regression. Among 1,054 children, 309 (29%) were EVD positive and 697 (66%) EVD negative, with 48 (5%) missing. Contact history, conjunctivitis, and age were the strongest positive predictors for EVD. The PEP score had an area under receiver operating characteristics curve of 0.80. A PEP score of 7/10 was 92% specific and 44% sensitive; 3/10 was 30% specific, 94% sensitive. The PEP score could correctly classify 79%-90% of children and could be used to facilitate triage into risk categories, depending on the sensitivity or specificity required. |
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United Kingdom | 4 | 40% |
Australia | 1 | 10% |
Unknown | 5 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 6 | 60% |
Practitioners (doctors, other healthcare professionals) | 4 | 40% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 40 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 9 | 23% |
Other | 6 | 15% |
Professor > Associate Professor | 3 | 8% |
Student > Master | 3 | 8% |
Student > Postgraduate | 2 | 5% |
Other | 7 | 18% |
Unknown | 10 | 25% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 12 | 30% |
Arts and Humanities | 3 | 8% |
Nursing and Health Professions | 3 | 8% |
Social Sciences | 2 | 5% |
Unspecified | 1 | 3% |
Other | 4 | 10% |
Unknown | 15 | 38% |