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Pathogenic Ischemic Stroke Phenotypes in the NINDS-Stroke Genetics Network

Journal article
Authors Hakan Ay
Ethem Murat Arsava
Gunnar Andsberg
Thomas Benner
Robert D. Brown Jr
Sherita N. Chapman
John W. Cole
Hossein Delavaran
Martin Dichgans
Gunnar Engström
Eva Giralt-Steinhauer
Raji P. Grewal
Katrina Gwinn
Christina Jern
Jordi Jimenez-Conde
Katarina Jood
Michael Katsnelson
Brett Kissela
Steven J. Kittner
Dawn O. Kleindorfer
Daniel L. Labovitz
Silvia Lanfranconi
Jin-Moo Lee
Manuel Lehm
Robin Lemmens
Chris Levi
Linxin Li
Arne Lindgren
Hugh S. Markus
Patrick F. McArdle
Olle Melander
Bo Norrving
Leema Reddy Peddareddygari
Annie Pedersen
Joanna Pera
Kristiina Rannikmäe
Kathryn M. Rexrode
David Rhodes
Stephen S. Rich
Jaume Roquer
Jonathan Rosand
Peter M. Rothwell
Tatjana Rundek
Ralph L. Sacco
Reinhold Schmidt
Markus Schürks
Stephan Seiler
Pankaj Sharma
Agnieszka Slowik
Cathie Sudlow
Vincent Thijs
Rebecca Woodfield
Bradford B. Worrall
James F. Meschia
Published in Stroke
Volume 45
Issue 12
Pages 3589-96
ISSN 0039-2499
Publication year 2014
Published at Institute of Biomedicine, Department of Medical and Clinical Genetics
Institute of Neuroscience and Physiology, Department of Clinical Neuroscience and Rehabilitation
Pages 3589-96
Language en
Keywords classification, pathogenesis, phenotype
Subject categories Neuroscience


BACKGROUND AND PURPOSE: NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium. METHODS: Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases. RESULTS: The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (κ 0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (κ 0.73; 95% confidence interval, 0.70-0.75). CONCLUSIONS: This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke.

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