Advanced

The Causative Classification of Stroke system An international reliability and optimization study

Arsava, E. M.; Ballabio, E.; Benner, T.; Cole, J. W.; Delgado-Martinez, M. P.; Dichgans, M.; Fazekas, F.; Furie, K. L.; Illoh, K. and Jood, K., et al. (2010) In Neurology 75(14). p.1277-1284
Abstract
Background: Valid and reliable ischemic stroke subtype determination is crucial for well-powered multicenter studies. The Causative Classification of Stroke System (CCS, available at http://ccs.mgh.harvard.edu) is a computerized, evidence-based algorithm that provides both causative and phenotypic stroke subtypes in a rule-based manner. We determined whether CCS demonstrates high interrater reliability in order to be useful for international multicenter studies. Methods: Twenty members of the International Stroke Genetics Consortium from 13 centers in 8 countries, who were not involved in the design and development of the CCS, independently assessed the same 50 consecutive patients with acute ischemic stroke through reviews of abstracted... (More)
Background: Valid and reliable ischemic stroke subtype determination is crucial for well-powered multicenter studies. The Causative Classification of Stroke System (CCS, available at http://ccs.mgh.harvard.edu) is a computerized, evidence-based algorithm that provides both causative and phenotypic stroke subtypes in a rule-based manner. We determined whether CCS demonstrates high interrater reliability in order to be useful for international multicenter studies. Methods: Twenty members of the International Stroke Genetics Consortium from 13 centers in 8 countries, who were not involved in the design and development of the CCS, independently assessed the same 50 consecutive patients with acute ischemic stroke through reviews of abstracted case summaries. Agreement among ratings was measured by kappa statistic. Results: The kappa value for causative classification was 0.80 (95% confidence interval [ CI] 0.78-0.81) for the 5-subtype, 0.79 (95% CI 0.77-0.80) for the 8-subtype, and 0.70 (95% CI 0.69-0.71) for the 16-subtype CCS. Correction of a software-related factor that generated ambiguity improved agreement: kappa = 0.81 (95% CI 0.79-0.82) for the 5-subtype, 0.79 (95% CI 0.77-0.80) for the 8-subtype, and 0.79 (95% CI 0.78-0.80) for the 16-subtype CCS. The kappa value for phenotypic classification was 0.79 (95% CI 0.77-0.82) for supra-aortic large artery atherosclerosis, 0.95 (95% CI 0.93-0.98) for cardioembolism, 0.88 (95% CI 0.85-0.91) for small artery occlusion, and 0.79 (0.76-0.82) for other uncommon causes. Conclusions: CCS allows classification of stroke subtypes by multiple investigators with high reliability, supporting its potential for improving stroke classification in multicenter studies and ensuring accurate means of communication among different researchers, institutions, and eras. Neurology (R) 2010;75:1277-1284 (Less)
Please use this url to cite or link to this publication:
author
, et al. (More)
(Less)
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Neurology
volume
75
issue
14
pages
1277 - 1284
publisher
American Academy of Neurology
external identifiers
  • wos:000282883900013
  • scopus:77958177965
ISSN
1526-632X
DOI
10.1212/WNL.0b013e3181f612ce
language
English
LU publication?
yes
id
9ad9da53-2906-4df4-9713-12500653aacb (old id 1725697)
date added to LUP
2010-11-23 16:50:07
date last changed
2018-06-10 04:10:57
@article{9ad9da53-2906-4df4-9713-12500653aacb,
  abstract     = {Background: Valid and reliable ischemic stroke subtype determination is crucial for well-powered multicenter studies. The Causative Classification of Stroke System (CCS, available at http://ccs.mgh.harvard.edu) is a computerized, evidence-based algorithm that provides both causative and phenotypic stroke subtypes in a rule-based manner. We determined whether CCS demonstrates high interrater reliability in order to be useful for international multicenter studies. Methods: Twenty members of the International Stroke Genetics Consortium from 13 centers in 8 countries, who were not involved in the design and development of the CCS, independently assessed the same 50 consecutive patients with acute ischemic stroke through reviews of abstracted case summaries. Agreement among ratings was measured by kappa statistic. Results: The kappa value for causative classification was 0.80 (95% confidence interval [ CI] 0.78-0.81) for the 5-subtype, 0.79 (95% CI 0.77-0.80) for the 8-subtype, and 0.70 (95% CI 0.69-0.71) for the 16-subtype CCS. Correction of a software-related factor that generated ambiguity improved agreement: kappa = 0.81 (95% CI 0.79-0.82) for the 5-subtype, 0.79 (95% CI 0.77-0.80) for the 8-subtype, and 0.79 (95% CI 0.78-0.80) for the 16-subtype CCS. The kappa value for phenotypic classification was 0.79 (95% CI 0.77-0.82) for supra-aortic large artery atherosclerosis, 0.95 (95% CI 0.93-0.98) for cardioembolism, 0.88 (95% CI 0.85-0.91) for small artery occlusion, and 0.79 (0.76-0.82) for other uncommon causes. Conclusions: CCS allows classification of stroke subtypes by multiple investigators with high reliability, supporting its potential for improving stroke classification in multicenter studies and ensuring accurate means of communication among different researchers, institutions, and eras. Neurology (R) 2010;75:1277-1284},
  author       = {Arsava, E. M. and Ballabio, E. and Benner, T. and Cole, J. W. and Delgado-Martinez, M. P. and Dichgans, M. and Fazekas, F. and Furie, K. L. and Illoh, K. and Jood, K. and Kittner, S. and Lindgren, Arne and Majersik, J. J. and Macleod, M. J. and Meurer, W. J. and Montaner, J. and Olugbodi, A. A. and Pasdar, A. and Redfors, P. and Schmidt, R. and Sharma, P. and Singhal, A. B. and Sorensen, A. G. and Sudlow, C. and Thijs, V. and Worrall, B. B. and Rosand, J. and Ay, H.},
  issn         = {1526-632X},
  language     = {eng},
  number       = {14},
  pages        = {1277--1284},
  publisher    = {American Academy of Neurology},
  series       = {Neurology},
  title        = {The Causative Classification of Stroke system An international reliability and optimization study},
  url          = {http://dx.doi.org/10.1212/WNL.0b013e3181f612ce},
  volume       = {75},
  year         = {2010},
}