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Use of a handheld, computerized device as a decision support tool for stroke classification.

Authors
 H. S. Nam  ;  M.-J. Cha  ;  Y. D. Kim  ;  E. H. Kim  ;  E. Park  ;  H. S. Lee  ;  C. M. Nam  ;  J. H. Heo 
Citation
 EUROPEAN JOURNAL OF NEUROLOGY, Vol.19(3) : 426-30, 2012 
Journal Title
 EUROPEAN JOURNAL OF NEUROLOGY 
ISSN
 1351-5101 
Issue Date
2012
MeSH
Adult ; Aged ; Aged, 80 and over ; Algorithms* ; Decision Support Techniques* ; Diagnosis, Computer-Assisted/instrumentation* ; Female ; Humans ; Male ; Middle Aged ; Software* ; Stroke/classification*
Keywords
cerebral infarction ; classification ; handheld computerized device
Abstract
BACKGROUND: The Trial of ORG 10172 in Acute Stroke Treatment (TOAST) classification has been widely used to determine etiology of ischemic stroke. However, interrater reliability is known to be modest. The complexity of abstraction and the interpretation of various clinical and laboratory data might limit the accuracy of the TOAST classification. In this study, we developed a computerized clinical decision support system for stroke classification that can be used in a handheld device and tested whether this system can improve diagnostic accuracy and reliability. METHODS: Based on the TOAST classification, a logical algorithm was developed and implemented on a handheld device, named iTOAST. After answering six questions using the touch interface, the stroke subtype result is displayed on the screen. Four neurology residents were randomly assigned to classify stroke subtypes using iTOAST or the conventional method (cTOAST). Using a crossover design, they classified the stroke subtypes of 70 patients. The standard subtypes were determined by three stroke experts. Correlated kappa coefficients using iTOAST compared with cTOAST were determined. RESULTS: The kappa (SE) value of iTOAST [0.790 (0.041), 95% CI: 0.707-0.870] was higher than that of cTOAST [0.692 (0.046), 95% CI: 0.600-0.782] (P<0.001). Neither sequence (P=0.857) nor period effect (P=0.999) was observed. CONCLUSIONS: The stroke classification tool using a handheld, computerized device was easy, accurate, and reliable over the conventional method. It may have additional benefit because a handheld, computerized device is accessible anytime and anywhere.
Full Text
http://onlinelibrary.wiley.com/doi/10.1111/j.1468-1331.2011.03530.x/abstract
DOI
21951521
Appears in Collections:
1. College of Medicine (의과대학) > Yonsei Biomedical Research Center (연세의생명연구원) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Neurology (신경과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Preventive Medicine and Public Health (예방의학교실) > 1. Journal Papers
Yonsei Authors
Kim, Young Dae(김영대) ORCID logo https://orcid.org/0000-0001-5750-2616
Nam, Jung Mo(남정모) ORCID logo https://orcid.org/0000-0003-0985-0928
Nam, Hyo Suk(남효석) ORCID logo https://orcid.org/0000-0002-4415-3995
Lee, Hye Sun(이혜선) ORCID logo https://orcid.org/0000-0001-6328-6948
Cha, Myoung Jin(차명진)
Heo, Ji Hoe(허지회) ORCID logo https://orcid.org/0000-0001-9898-3321
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/90208
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