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 The leading web portal for pharmacy resources, news, education and careers October 22, 2017
Pharmacy Choice - Pharmaceutical News - New Findings from University of Maryland in Brain Injuries Provides New Insights (Permutation entropy analysis of vital signs data for outcome... - October 22, 2017

Pharmacy News Article

 3/2/15 - New Findings from University of Maryland in Brain Injuries Provides New Insights (Permutation entropy analysis of vital signs data for outcome...

New Findings from University of Maryland in Brain Injuries Provides New Insights (Permutation entropy analysis of vital signs data for outcome prediction of patients with severe traumatic brain injury)

By a News Reporter-Staff News Editor at Pain & Central Nervous System Week Investigators publish new report on Nervous System Diseases and Conditions. According to news originating from Baltimore, Maryland, by NewsRx correspondents, research stated, "Permutation entropy is computationally efficient, robust to outliers, and effective to measure complexity of time series. We used this technique to quantify the complexity of continuous vital signs recorded from patients with traumatic brain injury (TBI)."

Our news journalists obtained a quote from the research from the University of Maryland, "Using permutation entropy calculated from early vital signs (initial 10-20% of patient hospital stay time), we built classifiers to predict in-hospital mortality and mobility, measured by 3-month Extended Glasgow Outcome Score (GOSE). Sixty patients with severe TBI produced a skewed dataset that we evaluated for accuracy, sensitivity and specificity. The overall prediction accuracy achieved 91.67% for mortality, and 76.67% for 3-month GOSE in testing datasets, using the leave-one-out cross validation. We also applied Receiver Operating Characteristic analysis to compare classifiers built from different learning methods."

According to the news editors, the research concluded: "Those results support the applicability of permutation entropy in analyzing the dynamic behavior of TBI vital signs for early prediction of mortality and long-term patient outcomes."

For more information on this research see: Permutation entropy analysis of vital signs data for outcome prediction of patients with severe traumatic brain injury. Computers in Biology and Medicine, 2015;56():167-174. Computers in Biology and Medicine can be contacted at: Pergamon-Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, England. (Elsevier - www.elsevier.com; Computers in Biology and Medicine - www.elsevier.com/wps/product/cws-home/351)

The news correspondents report that additional information may be obtained from K. Kalpakis, University of Maryland, Sch Med, Baltimore, MD 21201, United States. Additional authors for this research include S.M. Yang, P.F. Hu, C.F. Mackenzie, L.G. Stansbury, D.M. Stein and T.M. Scalea (see also Nervous System Diseases and Conditions).

Keywords for this news article include: Maryland, Hospital, Baltimore, United States, Brain Injuries, Craniocerebral Trauma, Traumatic Brain Injury, North and Central America, Nervous System Diseases and Conditions

Our reports deliver fact-based news of research and discoveries from around the world. Copyright 2015, NewsRx LLC



(c) 2015 NewsRx LLC

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