The Los Angeles motor scale (LAMS) is independently associated with CT perfusion collateral status markers.

ASITN Acute ischemic stroke Collateral status LAMS Large Vessel Occlusion

Journal

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
ISSN: 1532-2653
Titre abrégé: J Clin Neurosci
Pays: Scotland
ID NLM: 9433352

Informations de publication

Date de publication:
11 May 2024
Historique:
received: 03 01 2024
revised: 31 03 2024
accepted: 07 05 2024
medline: 13 5 2024
pubmed: 13 5 2024
entrez: 12 5 2024
Statut: aheadofprint

Résumé

The Los Angeles Motor Scale (LAMS) is an objective tool that has been used to rapidly assess and predict the presence of large vessel occlusion (LVO) in the pre-hospital setting successfully in several studies. However, studies assessing the relationship between LAMS score and CT perfusion collateral status (CS) markers such as cerebral blood volume (CBV) index, and hypoperfusion intensity ratio (HIR) are sparse. Our study therefore aims to assess the association of admission LAMS score with established CTP CS markers CBV Index and HIR in AIS-LVO cases. In this prospectively collected, retrospectively reviewed analysis, inclusion criteria were as follows: a) CT angiography (CTA) confirmed anterior circulation LVO from 9/1/2017 to 10/01/2023, and b) diagnostic CT perfusion (CTP). Logistic regression analysis was performed to assess the relationship between admission LAMS with CTP CS markers HIR and CBV Index. p ≤ 0.05 was considered significant. In total, 285 consecutive patients (median age = 69 years; 56 % female) met our inclusion criteria. Multivariable logistic regression analysis adjusting for sex, age, ASPECTS, tPA, premorbid mRS, admission NIH stroke scale, prior history of TIA, stroke, atrial fibrillation, diabetes mellitus, hyperlipidemia, coronary artery disease and hypertension, admission LAMS was found to be independently associated with CBV Index (adjusted OR:0.82, p < 0.01), and HIR (adjusted OR:0.59, p < 0.05). LAMS is independently associated with CTP CS markers, CBV index and HIR. This finding suggests that LAMS may also provide an indirect estimate of CS.

Sections du résumé

BACKGROUND AND AIM OBJECTIVE
The Los Angeles Motor Scale (LAMS) is an objective tool that has been used to rapidly assess and predict the presence of large vessel occlusion (LVO) in the pre-hospital setting successfully in several studies. However, studies assessing the relationship between LAMS score and CT perfusion collateral status (CS) markers such as cerebral blood volume (CBV) index, and hypoperfusion intensity ratio (HIR) are sparse. Our study therefore aims to assess the association of admission LAMS score with established CTP CS markers CBV Index and HIR in AIS-LVO cases.
MATERIALS AND METHODS METHODS
In this prospectively collected, retrospectively reviewed analysis, inclusion criteria were as follows: a) CT angiography (CTA) confirmed anterior circulation LVO from 9/1/2017 to 10/01/2023, and b) diagnostic CT perfusion (CTP). Logistic regression analysis was performed to assess the relationship between admission LAMS with CTP CS markers HIR and CBV Index. p ≤ 0.05 was considered significant.
RESULTS RESULTS
In total, 285 consecutive patients (median age = 69 years; 56 % female) met our inclusion criteria. Multivariable logistic regression analysis adjusting for sex, age, ASPECTS, tPA, premorbid mRS, admission NIH stroke scale, prior history of TIA, stroke, atrial fibrillation, diabetes mellitus, hyperlipidemia, coronary artery disease and hypertension, admission LAMS was found to be independently associated with CBV Index (adjusted OR:0.82, p < 0.01), and HIR (adjusted OR:0.59, p < 0.05).
CONCLUSION CONCLUSIONS
LAMS is independently associated with CTP CS markers, CBV index and HIR. This finding suggests that LAMS may also provide an indirect estimate of CS.

Identifiants

DOI: 10.1016/j.jocn.2024.05.005 PMID: 38735251
pubmed: 38735251
pii: S0967-5868(24)00184-X
doi: 10.1016/j.jocn.2024.05.005
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

32-37

Informations de copyright

Copyright © 2024 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Dhairya A Lakhani (DA)

Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA. Electronic address: dhairyalakhani@gmail.com.

Tejas R Mehta (TR)

Department of Neurology, University of missouri, Columbia, MO, USA.

Aneri B Balar (AB)

Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA.

Manisha Koneru (M)

Cooper Medical School of Rowan University, Camden, NJ, USA.

Sijin Wen (S)

Department of Biostatistics, West Virginia University, Morgantown, WV, USA.

Burak Berksu Ozkara (BB)

Department of Neuroradiology, MD Anderson Medical Center, Houston, TX.

Justin Caplan (J)

Department of Neurology, Johns Hopkins University, Baltimore, MD, USA.

Adam A Dmytriw (AA)

Department of Radiology, Harvard Medical School, Boston, MA, USA.

Richard Wang (R)

Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA.

Hanzhang Lu (H)

Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA.

Meisam Hoseinyazdi (M)

Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA.

Mehreen Nabi (M)

Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA.

Ishan Mazumdar (I)

Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA.

Andrew Cho (A)

Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA.

Kevin Chen (K)

Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA.

Sadra Sepehri (S)

Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA.

Nathan Hyson (N)

Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA.

Risheng Xu (R)

Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA.

Victor Urrutia (V)

Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA.

Licia Luna (L)

Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA.

Argye H Hillis (AH)

Department of Neurology, Johns Hopkins University, Baltimore, MD, USA.

Jeremy J Heit (JJ)

Department of Neurology, Stanford University, Stanford, CA, USA.

Greg W Albers (GW)

Department of Neurology, Stanford University, Stanford, CA, USA.

Ansaar T Rai (AT)

Department of Neuroradiology, West Virginia University, Morgantown, WV, USA.

Tobias D Faizy (TD)

Department of Radiology, Neuroendovascular Division - University Medical Center Münster, Germany.

Max Wintermark (M)

Department of Neuroradiology, MD Anderson Medical Center, Houston, TX.

Kambiz Nael (K)

Division of Neuroradiology, Department of Radiology, University of California San Francisco, CA, USA.

Vivek S Yedavalli (VS)

Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA.

Classifications MeSH