An evidence‐based causative classification system for acute ischemic stroke

@article{Ay2005AnEC,
  title={An evidence‐based causative classification system for acute ischemic stroke},
  author={H Ay and Karen L. Furie and Aneesh Bhim Singhal and Wade S. Smith and A. Gregory Sorensen and Walter J. Koroshetz},
  journal={Annals of Neurology},
  year={2005},
  volume={58}
}
Regular, evidence‐based assignment of patients to etiologic stroke categories is essential to enable valid comparison among studies. We designed an algorithm (SSS‐TOAST) that incorporated recent advances in stroke imaging and epidemiology to identify the most probable TOAST category in the presence of evidence for multiple mechanisms. Based on the weight of evidence, each TOAST subtype was subdivided into 3 subcategories as “evident”, “probable”, or “possible”. Classification into the… 
A Computerized Algorithm for Etiologic Classification of Ischemic Stroke: The Causative Classification of Stroke System
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An automated version of the SSS-TOAST, the Causative Classification System (CCS), is presented to facilitate its utility in multicenter settings and allows rapid analysis of patient data with excellent intra- and inter-examiner reliability, suggesting a potential utility in improving the fidelity of stroke classification in multicEnter trials or research databases in which accurate subtyping is critical.
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The CASCADE criteria has moderate reliability when used by trained and experienced raters, which suggests that it can be used for classification in multicenter pediatric stroke studies, however, the moderate reliability of the arteriopathic subtypes suggests that further refinement is needed for defining subtypes.
MRI-based Algorithm for Acute Ischemic Stroke Subtype Classification
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This study shows that the MAGIC system is feasible and may be helpful to classify stroke subtype in the clinic and demonstrates that the Trial of Org 10172 in Acute Stroke Treatment (TOAST) of each stroke patient is classified.
Assessment of the Predictive Validity of Etiologic Stroke Classification
TLDR
The findings suggest that the major etiologic stroke subtypes are distinct categories with different stroke characteristics irrespective of the classification system used to identify them and show that CCS generates discrete Etiologic categories with more diverse clinical, imaging, and prognostic characteristics than either TOAST or ASCO.
Comparison of conventional and modern methods in determining ischemic stroke etiology by general and stroke neurologists
TLDR
The C CS system improved compliance in both stroke and general neurologists compared with TOAST, suggesting that the automatic, evidence-based, easily reproducible CCS system was superior to the TOAST system.
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