EASY score (Eloquent, Age and baseline SYmptoms score) for outcome prediction in patients with acute ischemic stroke.

Acute ischemic stroke Brain eloquence CT scanner Stroke outcome

Journal

Clinical neurology and neurosurgery
ISSN: 1872-6968
Titre abrégé: Clin Neurol Neurosurg
Pays: Netherlands
ID NLM: 7502039

Informations de publication

Date de publication:
01 Apr 2021
Historique:
received: 28 01 2021
revised: 01 03 2021
accepted: 28 03 2021
pubmed: 20 4 2021
medline: 20 4 2021
entrez: 19 4 2021
Statut: aheadofprint

Résumé

A pragmatic tool for the early and reliable prediction of recovery in patients with acute ischemic stroke is needed. We aimed to test the addition of brain eloquent areas involvement in variables predicting poor outcome, using a simple scoring system. Retrospective study of patients with anterior circulation acute ischemic stroke treated with best medical treatment and/or endovascular reperfusion. Primary outcome measure was 3-months poor outcome (mRs 3-6). We developed a prognostic model based on clinical data and a quantitative scoring system of the main eloquent brain areas involved on early follow-up CT, and analyzed its accuracy to predict poor outcome comparatively to three other prognostic models. The final model was used to develop a score for outcome prediction based on the multivariable analysis. A total of 197 patients were included (poor outcome = 62; mean age 67 ± 15.1 years; 44% females). Independent predictors of poor outcome were increasing age (p < 0.001), baseline NIHSS (p = 0.03), and the involvement of two brain areas: posterior limb of internal capsule (p < 0.001) and postero-superior corona radiata (p < 0.001). This model showed to be the most accurate to predict poor outcome (Balance Accuracy = 77.74%; C-Statistic = 0.891). The derived risk score attributing points for each of these variables (EASY score) showed similar performances (Balance Accuracy = 82.11%; C-Statistic = 0.90). The EASY score is an easy-to-apply and accurate tool to predict the 3-months functional outcome after ischemic stroke, relying on simple clinical features and the assessment of two key eloquent brain areas on early follow-up CT.

Identifiants

pubmed: 33873121
pii: S0303-8467(21)00153-0
doi: 10.1016/j.clineuro.2021.106626
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

106626

Informations de copyright

Copyright © 2021 Elsevier B.V. All rights reserved.

Auteurs

Basile Kerleroux (B)

Neuroradiology Department, CHRU de Tours, 2 bd Tonnelé, Tours, France; Neuroradiology Department, CH Sainte-Anne, 1 Rue Cabanis, Paris, France. Electronic address: b.kerleroux@ghu-paris.fr.

Christophe Tomasino (C)

Neurology CHRU de Tours, 2 bd Tonnelé, Tours, France.

Diogo Soriano (D)

Engineering, Modeling and Applied Social Sciences Center - ABC Federal University Santo André, SP, Brazil.

Paula G Rodrigues (PG)

Engineering, Modeling and Applied Social Sciences Center - ABC Federal University Santo André, SP, Brazil.

Fernando Silva Moura (FS)

Engineering, Modeling and Applied Social Sciences Center - ABC Federal University Santo André, SP, Brazil.

Jean Philippe Cottier (JP)

Neuroradiology Department, CHRU de Tours, 2 bd Tonnelé, Tours, France.

Richard Bibi (R)

Neuroradiology Department, CHRU de Tours, 2 bd Tonnelé, Tours, France.

Denis Herbreteau (D)

Neuroradiology Department, CHRU de Tours, 2 bd Tonnelé, Tours, France.

Jean François Hak (JF)

Neuroradiology Department, CH Sainte-Anne, 1 Rue Cabanis, Paris, France; Neuroradiology Department, CHU La Timone, 264 Rue Saint Pierre, 13005, Marseille, France.

Héloïse Ifergan (H)

Neuroradiology Department, CHRU de Tours, 2 bd Tonnelé, Tours, France.

Kévin Janot (K)

Neuroradiology Department, CHRU de Tours, 2 bd Tonnelé, Tours, France.

Mariam Annan (M)

Neurology CHRU de Tours, 2 bd Tonnelé, Tours, France.

Grégoire Boulouis (G)

Neuroradiology Department, CHRU de Tours, 2 bd Tonnelé, Tours, France; Neuroradiology Department, CH Sainte-Anne, 1 Rue Cabanis, Paris, France.

Ana Paula Narata (AP)

Department of Neuroradiology, University Hospital of Southampton, Tremona Rd, Southampton, UK.

Classifications MeSH