Early Infarct Growth Rate Correlation With Endovascular Thrombectomy Clinical Outcomes: Analysis From the SELECT Study.


Journal

Stroke
ISSN: 1524-4628
Titre abrégé: Stroke
Pays: United States
ID NLM: 0235266

Informations de publication

Date de publication:
01 2021
Historique:
pubmed: 8 12 2020
medline: 17 4 2021
entrez: 7 12 2020
Statut: ppublish

Résumé

Time elapsed from last-known well (LKW) and baseline imaging results are influential on endovascular thrombectomy (EVT) outcomes. In a prospective multicenter cohort study of imaging selection for endovascular thrombectomy (SELECT [Optimizing Patient's Selection for Endovascular Treatment in Acute Ischemic Stroke], the early infarct growth rate (EIGR) was defined as ischemic core volume on perfusion imaging (relative cerebral blood flow<30%) divided by the time from LKW to imaging. The optimal EIGR cutoff was identified by maximizing the sum of the sensitivity and specificity to correlate best with favorable outcome and to improve its the predictability. Patients were stratified into slow progressors if EIGR<cutoff and fast progressors if EIGR≥the optimal cutoff. Good collaterals were defined on computed tomography perfusion as a hypoperfusion intensity ratio <0.4 and on computed tomography angiography as collateral score >2. The primary outcome was 90-day functional independence (modified Rankin Scale score =0-2). Of 445 consented, 361 (285 EVT, 76 medical management only) patients met the study inclusion criteria. The optimal EIGR was <10 mL/h; 200 EVT patients were slow and 85 fast progressors. Fast progressors had a higher median National Institutes of Health Stroke Scale (19 versus 15, The EIGR strongly correlates with both collateral status and clinical outcomes after EVT. Fast progressors demonstrated worse outcomes when receiving EVT beyond 6 hours of stroke onset as compared to those who received EVT within 6 hours. Registration: URL: https://clinicaltrials.gov. Unique identifier: NCT02446587.

Sections du résumé

BACKGROUND AND PURPOSE
Time elapsed from last-known well (LKW) and baseline imaging results are influential on endovascular thrombectomy (EVT) outcomes.
METHODS
In a prospective multicenter cohort study of imaging selection for endovascular thrombectomy (SELECT [Optimizing Patient's Selection for Endovascular Treatment in Acute Ischemic Stroke], the early infarct growth rate (EIGR) was defined as ischemic core volume on perfusion imaging (relative cerebral blood flow<30%) divided by the time from LKW to imaging. The optimal EIGR cutoff was identified by maximizing the sum of the sensitivity and specificity to correlate best with favorable outcome and to improve its the predictability. Patients were stratified into slow progressors if EIGR<cutoff and fast progressors if EIGR≥the optimal cutoff. Good collaterals were defined on computed tomography perfusion as a hypoperfusion intensity ratio <0.4 and on computed tomography angiography as collateral score >2. The primary outcome was 90-day functional independence (modified Rankin Scale score =0-2).
RESULTS
Of 445 consented, 361 (285 EVT, 76 medical management only) patients met the study inclusion criteria. The optimal EIGR was <10 mL/h; 200 EVT patients were slow and 85 fast progressors. Fast progressors had a higher median National Institutes of Health Stroke Scale (19 versus 15,
CONCLUSIONS
The EIGR strongly correlates with both collateral status and clinical outcomes after EVT. Fast progressors demonstrated worse outcomes when receiving EVT beyond 6 hours of stroke onset as compared to those who received EVT within 6 hours. Registration: URL: https://clinicaltrials.gov. Unique identifier: NCT02446587.

Identifiants

pubmed: 33280550
doi: 10.1161/STROKEAHA.120.030912
doi:

Banques de données

ClinicalTrials.gov
['NCT02446587']

Types de publication

Clinical Study Journal Article Multicenter Study Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

57-69

Auteurs

Amrou Sarraj (A)

Department of Neurology (A.S., J.G., D.P., F.S., H.K.), The University of Texas at Houston.

Ameer E Hassan (AE)

Neurology, University of Texas Rio Grande Valley, Harlingen (A.E.H.).

James Grotta (J)

Department of Neurology (A.S., J.G., D.P., F.S., H.K.), The University of Texas at Houston.

Spiros Blackburn (S)

Department of Neurosurgery (S.B., A.D., M.D.), The University of Texas at Houston.

Arthur Day (A)

Department of Neurosurgery (S.B., A.D., M.D.), The University of Texas at Houston.

Michael Abraham (M)

Department of Neurology, University of Kansas Medical Center (M.A.).

Clark Sitton (C)

Department of Neurosurgery (S.B., A.D., M.D.), The University of Texas at Houston.

Mark Dannenbaum (M)

Department of Neurosurgery (S.B., A.D., M.D.), The University of Texas at Houston.

Chunyan Cai (C)

Division of Clinical and Translational Science (C.C.), The University of Texas at Houston.

Deep Pujara (D)

Department of Neurology (A.S., J.G., D.P., F.S., H.K.), The University of Texas at Houston.

William Hicks (W)

Department of Neurology, OhioHealth - Riverside Methodist Hospital, Columbus (W.H., N.V., R.B.).

Nirav Vora (N)

Department of Neurology, OhioHealth - Riverside Methodist Hospital, Columbus (W.H., N.V., R.B.).

Ronald Budzik (R)

Department of Neurology, OhioHealth - Riverside Methodist Hospital, Columbus (W.H., N.V., R.B.).

Faris Shaker (F)

Department of Neurology (A.S., J.G., D.P., F.S., H.K.), The University of Texas at Houston.

Ashish Arora (A)

Cone Health, Greensboro, NC (A.A.).

Roy F Riascos (RF)

Department of Radiology (C.S., R.F.R.), The University of Texas at Houston.

Haris Kamal (H)

Department of Neurology (A.S., J.G., D.P., F.S., H.K.), The University of Texas at Houston.

Sheryl Martin-Schild (S)

Department of Neurology, Touro Infirmary and New Orleans East Hospital (S.M.-S.).

Maarten Lansberg (M)

Department of Neurology, Stanford University (M.L., G.W.A.).

Rishi Gupta (R)

Department of Neurology, WellStar Health System, Atlanta (R.G.).

Gregory W Albers (GW)

Department of Neurology, Stanford University (M.L., G.W.A.).

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