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The Causative Classification of Stroke system: an international reliability and optimization study.
E M Arsava1, E Ballabio, T Benner
1A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA.
Neurology
|October 6, 2010
Summary
The Causative Classification of Stroke System (CCS) demonstrates high interrater reliability for determining ischemic stroke subtypes. This supports its use in international multicenter studies for accurate stroke classification and communication.
Area of Science:
- Neurology
- Medical Informatics
Background:
- Accurate ischemic stroke subtype determination is essential for robust multicenter research.
- The Causative Classification of Stroke System (CCS) is an evidence-based algorithm for classifying stroke subtypes.
Purpose of the Study:
- To evaluate the interrater reliability of the CCS algorithm.
- To determine the suitability of CCS for international multicenter stroke studies.
Main Methods:
- Twenty International Stroke Genetics Consortium members from 13 centers independently classified 50 acute ischemic stroke cases using CCS.
- Interrater agreement was assessed using the kappa statistic.
Main Results:
- High kappa values were observed for causative classification (0.70-0.81) and phenotypic classification (0.79-0.95) across different subtype models.
- Correction of a software issue improved agreement, particularly for the 16-subtype model.
Conclusions:
- The CCS algorithm exhibits high interrater reliability for stroke subtype classification.
- CCS is a valuable tool for improving stroke classification consistency in multicenter studies and facilitating clear communication among researchers.
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