Literature DB >> 17292033

Diagnosis of febrile illnesses in returned travelers using the PC software GIDEON.

Mikio Kimura1, Mitsuo Sakamoto, Takuya Adachi, Hiroko Sagara.   

Abstract

BACKGROUND: The prompt and accurate diagnosis of febrile illnesses should have the highest priority when dealing with returned travelers. However, traditional diagnostic procedures aided by collecting information from printed materials may have drawbacks. Here, we conducted a retrospective study to evaluate the diagnostic capability of the software, Global Infectious Disease and Epidemiology Network (GIDEON).
METHOD: We recruited a total of 98 febrile travelers in whom an infectious disease diagnosis had been confirmed by microbiology and/or serology. The presence or absence of symptoms/signs and laboratory abnormalities, travel destination, entry and departure dates, and the date of onset were input into updated versions of GIDEON.
RESULTS: Overall, the correct diagnoses appeared on the differential diagnosis lists for 91% of the cases and ranked first for 52%. A correct diagnosis could be excluded from the differential diagnostic list by the presence of symptoms and signs irrelevant to the disease, which was demonstrated most clearly in a case of Lassa fever. We also found that a correct diagnosis can be listed lower than expected, probably due to the irrelevant database.
CONCLUSIONS: Improvements are required at the level of the developer and users are required to have adequate knowledge of infectious diseases for best use of the program. Despite these limitations, we believe that GIDEON is a novel and potentially powerful tool in infectious disease diagnosis.

Entities:  

Year:  2005        PMID: 17292033     DOI: 10.1016/j.tmaid.2004.08.003

Source DB:  PubMed          Journal:  Travel Med Infect Dis        ISSN: 1477-8939            Impact factor:   6.211


  4 in total

1.  Using a relational database to index infectious disease information.

Authors:  Jay A Brown
Journal:  Int J Environ Res Public Health       Date:  2010-05-04       Impact factor: 3.390

2.  Collaborative decision support and documentation in chemical safety with KnowSEC.

Authors:  Joachim Baumeister; Albrecht Striffler; Marc Brandt; Michael Neumann
Journal:  J Cheminform       Date:  2016-04-23       Impact factor: 5.514

3.  A rapid research needs appraisal methodology to identify evidence gaps to inform clinical research priorities in response to outbreaks-results from the Lassa fever pilot.

Authors:  Louise Sigfrid; Catrin Moore; Alex P Salam; Nicola Maayan; Candyce Hamel; Chantelle Garritty; Vittoria Lutje; Brian Buckley; Karla Soares-Weiser; Rachel Marshall; Mike Clarke; Peter Horby
Journal:  BMC Med       Date:  2019-06-11       Impact factor: 8.775

4.  A Bayesian classification model for discriminating common infectious diseases in Zhejiang province, China.

Authors:  Fudong Li; Yi Shen; Duo Lv; Junfen Lin; Biyao Liu; Fan He; Zhen Wang
Journal:  Medicine (Baltimore)       Date:  2020-02       Impact factor: 1.817

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.