Stroke subtypes

I see absolutely nothing in this research that does one damn bit of good in helping stroke survivors recover better.

Assessment of the Predictive Validity of Etiologic Stroke Classification

E. Murat Arsava, MD^1,2; Johanna Helenius, MD^1,3,4; Ross Avery, BS^1,5; et al Mine H. Sorgun, MD^1,6; Gyeong-Moon Kim, MD, PhD^1,7; Octavio M. Pontes-Neto, MD, PhD^1,8; Kwang Yeol Park, MD^1,9; Jonathan Rosand, MD, MSc^10,11; Mark Vangel, PhD¹²; Hakan Ay, MD^1,10

Author Affiliations

JAMA Neurol. Published online February 27, 2017. doi:10.1001/jamaneurol.2016.5815

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• Editorial
  Stroke Etiologic Classification—Moving From Prediction to Precision
  Mitchell S. V. Elkind, MD, MS

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Key Points

Question  Can etiologic stroke subtyping generate categories with discrete clinical, imaging, and prognostic characteristics?
Findings  A head-to-head, blind evaluation of Causative Classification of Stroke, Trial of Org 10172 in Acute Stroke Treatment, and ASCO (A for atherosclerosis, S for small-vessel disease, C for cardiac source, and O for other cause) classification systems in 1816 consecutive patients with ischemic stroke revealed that all systems generated etiologic subtypes with different 90-day stroke recurrence, 90-day survival, admission stroke severity, and acute infarct burden. The Causative Classification of Stroke system redistributed 20% to 40% of the population assigned into the undetermined category by other systems into known subtypes and provided a greater discrimination for most of the stroke characteristics tested as compared with the Trial of Org 10172 in Acute Stroke Treatment and ASCO systems.
Meaning  Etiologic stroke classification identifies discrete categories with different stroke features.

Abstract

Importance  The ability of present-day etiologic stroke classification systems to generate subtypes with discrete stroke characteristics is not known.
Objective  To test the hypothesis that etiologic stroke subtyping identifies different disease processes that can be recognized through their different clinical courses.
Design, Setting, and Participants  We performed a head-to-head evaluation of the ability of the Causative Classification of Stroke (CCS), Trial of Org 10172 in Acute Stroke Treatment (TOAST), and ASCO (A for atherosclerosis, S for small-vessel disease, C for cardiac source, and O for other cause) classification systems to generate etiologic subtypes with different clinical, imaging, and prognostic characteristics in 1816 patients with ischemic stroke. This study included 2 cohorts recruited at separate periods; the first cohort was recruited between April 2003 and June 2006 and the second between June 2009 and December 2011. Data analysis was performed between June 2014 and May 2016.
Main Outcomes and Measures  Separate teams of stroke-trained neurologists performed CCS, TOAST, and ASCO classifications based on information available at the time of hospital discharge. We assessed the association between etiologic subtypes and stroke characteristics by computing receiver operating characteristic curves for binary variables (90-day stroke recurrence and 90-day mortality) and by calculating the ratio of between-category to within-category variability from the analysis of variance for continuous variables (admission National Institutes of Health Stroke Scale score and acute infarct volume).
Results  Among the 1816 patients included, the median age was 70 years (interquartile range, 58-80 years) (830 women [46%]). The classification systems differed in their ability to assign stroke etiologies into known subtypes; the size of the undetermined category was 33% by CCS, 53% by TOAST, and 42% by ASCO (P < .001 for all binary comparisons). All systems provided significant discrimination for the validation variables tested. For the primary validation variable (90-day recurrence), the area under the receiver operating characteristic curve was 0.71 (95% CI, 0.66-0.75) for CCS, 0.61 (95% CI, 0.56-0.67) for TOAST, and 0.66 (95% CI, 0.60-0.71) for ASCO (P = .01 for CCS vs ASCO; P < .001 for CCS vs TOAST; P  = .13 for ASCO vs TOAST). The classification systems exhibited similar discrimination for 90-day mortality. For admission National Institutes of Health Stroke Scale score and acute infarct volume, CCS generated more distinct subtypes with higher between-category to within-category variability than TOAST and ASCO.
Conclusions and Relevance  Our findings suggest that the major etiologic stroke subtypes are distinct categories with different stroke characteristics irrespective of the classification system used to identify them. We further show that CCS generates discrete etiologic categories with more diverse clinical, imaging, and prognostic characteristics than either TOAST or ASCO.