Similar admission NIHSS may represent larger tissue-at-risk in patients with right-sided versus left-sided large vessel occlusion.


Journal

Journal of neurointerventional surgery
ISSN: 1759-8486
Titre abrégé: J Neurointerv Surg
Pays: England
ID NLM: 101517079

Informations de publication

Date de publication:
Oct 2022
Historique:
received: 14 05 2021
accepted: 30 09 2021
pubmed: 15 10 2021
medline: 17 9 2022
entrez: 14 10 2021
Statut: ppublish

Résumé

We investigated the effects of the side of large vessel occlusion (LVO) on post-thrombectomy infarct volume and clinical outcome with regard to admission National Institutes of Health Stroke Scale (NIHSS) score. We retrospectively identified patients with anterior LVO who received endovascular thrombectomy and follow-up MRI. Applying voxel-wise general linear models and multivariate analysis, we assessed the effects of occlusion side, admission NIHSS, and post-thrombectomy reperfusion (modified Thrombolysis in Cerebral Infarction, mTICI) on final infarct distribution and volume as well as discharge modified Rankin Scale (mRS) score. We included 469 patients, 254 with left-sided and 215 with right-sided LVO. Admission NIHSS was higher in those with left-sided LVO (median (IQR) 16 (10-22)) than in those with right-sided LVO (14 (8-16), p>0.001). In voxel-wise analysis, worse post-thrombectomy reperfusion, lower admission NIHSS score, and poor discharge outcome were associated with right-hemispheric infarct lesions. In multivariate analysis, right-sided LVO was an independent predictor of larger final infarct volume (p=0.003). There was a significant three-way interaction between admission stroke severity (based on NIHSS), LVO side, and mTICI with regard to final infarct volume (p=0.041). Specifically, in patients with moderate stroke (NIHSS 6-15), incomplete reperfusion (mTICI 0-2b) was associated with larger final infarct volume (p<0.001) and worse discharge outcome (p=0.02) in right-sided compared with left-sided LVO. When adjusted for admission NIHSS, worse post-thrombectomy reperfusion is associated with larger infarct volume and worse discharge outcome in right-sided versus left-sided LVO. This may represent larger tissue-at-risk in patients with right-sided LVO when applying admission NIHSS as a clinical biomarker for penumbra.

Sections du résumé

BACKGROUND BACKGROUND
We investigated the effects of the side of large vessel occlusion (LVO) on post-thrombectomy infarct volume and clinical outcome with regard to admission National Institutes of Health Stroke Scale (NIHSS) score.
METHODS METHODS
We retrospectively identified patients with anterior LVO who received endovascular thrombectomy and follow-up MRI. Applying voxel-wise general linear models and multivariate analysis, we assessed the effects of occlusion side, admission NIHSS, and post-thrombectomy reperfusion (modified Thrombolysis in Cerebral Infarction, mTICI) on final infarct distribution and volume as well as discharge modified Rankin Scale (mRS) score.
RESULTS RESULTS
We included 469 patients, 254 with left-sided and 215 with right-sided LVO. Admission NIHSS was higher in those with left-sided LVO (median (IQR) 16 (10-22)) than in those with right-sided LVO (14 (8-16), p>0.001). In voxel-wise analysis, worse post-thrombectomy reperfusion, lower admission NIHSS score, and poor discharge outcome were associated with right-hemispheric infarct lesions. In multivariate analysis, right-sided LVO was an independent predictor of larger final infarct volume (p=0.003). There was a significant three-way interaction between admission stroke severity (based on NIHSS), LVO side, and mTICI with regard to final infarct volume (p=0.041). Specifically, in patients with moderate stroke (NIHSS 6-15), incomplete reperfusion (mTICI 0-2b) was associated with larger final infarct volume (p<0.001) and worse discharge outcome (p=0.02) in right-sided compared with left-sided LVO.
CONCLUSIONS CONCLUSIONS
When adjusted for admission NIHSS, worse post-thrombectomy reperfusion is associated with larger infarct volume and worse discharge outcome in right-sided versus left-sided LVO. This may represent larger tissue-at-risk in patients with right-sided LVO when applying admission NIHSS as a clinical biomarker for penumbra.

Identifiants

pubmed: 34645705
pii: neurintsurg-2021-017785
doi: 10.1136/neurintsurg-2021-017785
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

985-991

Subventions

Organisme : Doris Duke Charitable Foundation
ID : 2020097
Pays : United States
Organisme : NICHD NIH HHS
ID : K01 HD091283
Pays : United States
Organisme : NINDS NIH HHS
ID : K08 NS078110
Pays : United States
Organisme : NIA NIH HHS
ID : K76 AG059992
Pays : United States

Informations de copyright

© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: DF reports holding an equity interest in ai4medicine with no connection to the presented work. He also reports a pending patent for A clinical decision support system for stroke treatment (EP21159801.6). VIM reports receiving personal fees from ai4medicine outside the presented work. There is no connection, commercial exploitation, transfer or association between the projects of ai4medicine and the presented work. He also reports a pending patent for A clinical decision support system for stroke treatment (EP21159801.6). PS received research funding from Siemens Healthineers and the Neiman Health Policy Institute. KNS reports equity interests in Alva Health and serves on the advisory board for NControl.

Auteurs

Adrian Mak (A)

Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut, USA.
CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany.

Charles Matouk (C)

Neurosurgery, Yale University School of Medicine, New Haven, Connecticut, USA.

Emily W Avery (EW)

Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut, USA.

Jonas Behland (J)

Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut, USA.
CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany.

Dietmar Frey (D)

CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany.
Neurosurgery, Charité Universitätsmedizin Berlin, Berlin, Germany.

Vince Istvan Madai (VI)

CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany.
School of Computing and Digital Technology, Birmingham City University, Birmingham, UK.
QUEST Center for Transforming Biomedical Research, Berlin Institute of Health, Berlin, Germany.

Peter Vajkoczy (P)

Neurosurgery, Charité Universitätsmedizin Berlin, Berlin, Germany.

Ajay Malhotra (A)

Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut, USA.

Anthony Abou Karam (A)

Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut, USA.

Pina Sanelli (P)

Radiology, Feinstein Institute for Medical Research, Manhasset, New York, USA.

Guido J Falcone (GJ)

Neurology, Yale University School of Medicine, New Haven, Connecticut, USA.

Nils H Petersen (NH)

Neurology, Yale University School of Medicine, New Haven, Connecticut, USA.

Lauren Sansing (L)

Neurology, Yale University School of Medicine, New Haven, Connecticut, USA.

Kevin N Sheth (KN)

Neurology, Yale University School of Medicine, New Haven, Connecticut, USA.

Seyedmehdi Payabvash (S)

Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut, USA sam.payabvash@yale.edu.

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