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New tool to diagnose Ebola uncovers some surprises

Date:
April 7, 2015
Source:
American College of Emergency Physicians
Summary:
Abdominal pain, fever and unexplained bleeding - which are commonly believed to indicate infection with the Ebola virus -- are not significantly predictive of the disease, according to the results of a study examining a new Ebola Prediction Score.
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Abdominal pain, fever and unexplained bleeding -- which are commonly believed to indicate infection with the Ebola virus -- are not significantly predictive of the disease, according to the results of a study examining a new Ebola Prediction Score published online Friday in Annals of Emergency Medicine ("Derivation and Internal Validation of the Ebola Prediction Score for Risk Stratification of Patients with Suspected Ebola Virus Disease").

"Not surprisingly, contact with a suspected or confirmed Ebola patient was the strongest independent predictor of having Ebola," said lead study author Adam Levine, MD, MPH, of Rhode Island Hospital in Providence, R.I. "What was surprising was that abdominal pain in combination with other Ebola-like symptoms actually turned out to be negatively predictive of Ebola. This may be because those patients actually had another disease like typhoid, which is more likely to cause abdominal pain."

Current World Health Organization and Medecins san Frontieres symptoms lists for Ebola include fever, nausea with vomiting, diarrhea, fatigue, abdominal pain, loss of appetite, muscle pain, joint pain, headache, difficulty breathing, difficulty swallowing, hiccups, unexplained bleeding and exposure to a suspected or confirmed Ebola patient within 21 days. However, Dr. Levin's Ebola Prediction Score tool demonstrates that just six of those symptoms together -- contact with an infected person, diarrhea, loss of appetite, muscle pain, difficulty swallowing and absence of abdominal pain -- accurately predicted infection with Ebola.

Diagnosing Ebola remains a significant challenge because initial symptoms are similar to those of many other diseases. This is the first study to empirically derive and internally validate a clinical prediction model for laboratory-confirmed Ebola. The Ebola Prediction Score can be used by clinicians in the context of an active Ebola epidemic for the purpose of separating patients in an isolation center.

"The current Ebola outbreak in West Africa is the largest on record and has overwhelmed the capacity of both local health systems and the international community," said Dr. Levine. "The Ebola Prediction Score will help clinicians risk-stratify patients already meeting one or more suspect definitions of Ebola. Given the devastation this epidemic has already caused, a low-cost, point-of-care test that can rapidly and definitively exclude Ebola in patients should be a research priority."

Ebola has affected 24,000 persons during the current epidemic, which is the largest recorded outbreak of Ebola in history. Over 10,000 people have died in West Africa, mainly in Sierra Leone, Liberia and Guinea.


Story Source:

Materials provided by American College of Emergency Physicians. Note: Content may be edited for style and length.


Journal Reference:

  1. Adam C. Levine, Pranav Prathap Shetty, Ryan Burbach, Sambhavi Cheemalapati, Justin Glavis-Bloom, Tess Wiskel, J. Kota T. Kesselly. Derivation and Internal Validation of the Ebola Prediction Score for Risk Stratification of Patients With Suspected Ebola Virus Disease. Annals of Emergency Medicine, 2015; DOI: 10.1016/j.annemergmed.2015.03.011

Cite This Page:

American College of Emergency Physicians. "New tool to diagnose Ebola uncovers some surprises." ScienceDaily. ScienceDaily, 7 April 2015. <www.sciencedaily.com/releases/2015/04/150407124128.htm>.
American College of Emergency Physicians. (2015, April 7). New tool to diagnose Ebola uncovers some surprises. ScienceDaily. Retrieved May 23, 2017 from www.sciencedaily.com/releases/2015/04/150407124128.htm
American College of Emergency Physicians. "New tool to diagnose Ebola uncovers some surprises." ScienceDaily. www.sciencedaily.com/releases/2015/04/150407124128.htm (accessed May 23, 2017).

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