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Computerized Adaptive Testing System of Functional Assessment of Stroke
Published on: January 7, 2019
Use of a handheld, computerized device as a decision support tool for stroke classification
1Department of Neurology, Yonsei University College of Medicine, Seoul, Korea.
European Journal of Neurology
|September 29, 2011
Summary
A new handheld device, iTOAST, improves the accuracy and reliability of classifying ischemic stroke subtypes compared to the conventional method. This computerized tool enhances diagnostic capabilities for stroke etiology determination.
Area of Science:
- Neurology
- Medical Informatics
- Clinical Decision Support
Background:
- The Trial of ORG 10172 in Acute Stroke Treatment (TOAST) classification is standard for determining ischemic stroke etiology.
- Modest interrater reliability and complexity of the TOAST classification can limit diagnostic accuracy.
- A computerized decision support system on a handheld device was developed to address these limitations.
Purpose of the Study:
- To develop and test a computerized clinical decision support system (iTOAST) for stroke classification.
- To evaluate if iTOAST improves diagnostic accuracy and reliability compared to the conventional method (cTOAST).
Main Methods:
- A logical algorithm based on TOAST criteria was implemented on a handheld device (iTOAST).
- Four neurology residents used iTOAST and cTOAST in a crossover design to classify 70 stroke patients.
- Stroke subtypes were determined by three experts; kappa coefficients were calculated for comparison.
Main Results:
- iTOAST achieved a higher kappa coefficient (0.790) than cTOAST (0.692), indicating improved reliability (P<0.001).
- No significant sequence or period effects were observed in the crossover design.
Conclusions:
- The iTOAST system offers an easy, accurate, and reliable method for stroke classification.
- Handheld, computerized devices provide accessible, anytime-anywhere support, potentially enhancing stroke care.
