Effect of Known Atrial Fibrillation and Anticoagulation Status on the Prehospital Identification of Large Vessel Occlusion

Grewal, Parneet; Lahoti, Sourabh; Aroor, Sushanth; Snyder, K; Pettigrew, L. Creed; Goldstein, Larry B.

doi:10.1016/j.jstrokecerebrovasdis.2019.104404

Cited by 6 publications

(4 citation statements)

References 10 publications

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“…Recent studies have suggested that AF is more com mon in the LVO subgroup stroke population [4][5][6]. Giv en the association between left atrial enlargement (LAE) and AF [7,8], we hypothesized LAE may be associated with LVO and thereby indicate potential stroke aetiology and direct secondary management.…”

Section: Introductionmentioning

confidence: 96%

Left Atrial Enlargement on Non-Gated CT Is Associated with Large Vessel Occlusion in Acute Ischaemic Stroke

Butt

Dhillon

Lenthall

et al. 2021

Cerebrovasc Dis Extra

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Background: Recent reports have suggested that atrial fibrillation (AF) is more prevalent in the large vessel occlusion (LVO) subgroup of acute ischaemic stroke patients. Given the association between left atrial enlargement (LAE) and AF, we sought to evaluate the feasibility of assessing LAE on non-gated CT and its association with LVO in the hyperacute stroke setting. Methods: We analysed our prospectively collected database that included all stroke patients referred for consideration of endovascular treatment between April 14, 2020, and May 21, 2020. During this period, a CT chest was included in our regional stroke protocol to aid triage of patients suspected for COVID-19 from which cardiac measurements were obtained. Patients were dichotomized into LVO and no-LVO groups, and LA measurements were trichotomized into normal, borderline, and enlarged. Univariate analyses were performed between groups. Results: Of the included 38 patients, 21 were categorized as LVO and 17 as no LVO. There was a statistically significant association between LAE and LVO (p = 0.028). No significant difference was demonstrated between groups for the baseline AF and other clinical characteristics, except for baseline NIHSS (p = 0.0005). There was excellent inter- and intra-rater reliability (ICC = 0.969) for LA measurements. Conclusion: Our study provides preliminary data to suggest LAE is more prevalent in the LVO stroke subgroup at presentation and can be reliably assessed on non-gated CT in the hyperacute setting. These findings have potential implications for stratifying secondary management and may prompt a more rigorous pursuit of occult AF or other cardiac causes of stroke.

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Section: Introductionmentioning

confidence: 96%

Left Atrial Enlargement on Non-Gated CT Is Associated with Large Vessel Occlusion in Acute Ischaemic Stroke

Butt

Dhillon

Lenthall

et al. 2021

Cerebrovasc Dis Extra

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“…Recent studies have found higher rates of LVO amongst patients with atrial fibrillation but not in those already taking oral anticoagulants [11,12]. Our findings suggest that anticoagulated patients tend to have more severe strokes and higher rates of LVO and intracranial hemorrhage.…”

Section: Discussionmentioning

confidence: 39%

Contraindications to intravenous thrombolysis in prehospital triage of thrombectomy candidates

Rodríguez‐Pardo

Secades‐García

Riera-López³

et al. 2020

Euro J of Neurology

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Background and purpose The existence of contraindications to intravenous thrombolysis (IVT) is considered a criterion for direct transfer of patients with suspected acute stroke to thrombectomy‐capable centers in the prehospital setting. Our aim was to assess the utility of this criterion in a setting where routing protocols are defined by the Madrid – Direct Referral to Endovascular Center (M‐DIRECT) prehospital scale. Methods This was a post hoc analysis of the M‐DIRECT study. Reported contraindications to IVT were retrospectively collected from emergency medical services reports and categorized into late window, anticoagulant treatment and other contraindications. Final diagnosis and treatment rates were compared between patients with and without reported IVT contraindications and according to anticoagulant treatment or late window categories. Results The M‐DIRECT study included 541 patients. Reported IVT contraindications were present in 227 (42.0%) patients. Regarding final diagnosis no significant differences were found between patients with or without reported IVT contraindications: ischaemic stroke (any) 65.6% vs. 62.1%, ischaemic stroke with large vessel occlusion (LVO) 32.2% vs. 28.3%, hemorrhagic stroke 15.4% vs. 15.6%, stroke mimic 18.9% vs. 22.3% respectively. Amongst patients with LVO, endovascular thrombectomy (EVT) was performed less often in the presence of IVT contraindications (56.2% vs. 74.2%). M‐DIRECT‐positive patients had higher rates of LVO and EVT compared with M‐DIRECT‐negative patients independent of reported IVT contraindications. Conclusions Reported IVT contraindications alone do not increase EVT likelihood and should not be considered to determine routing in urban stroke networks.

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“…There have been some attempts to attach AF to various scales with heterogeneous results. A retrospective analysis has shown no improvement in the accuracy of four broadly used short stroke scales when AF was added as an element [18]. In contrast, another study found that the adding of AF to the Los Angeles Motor Scale (LAMS) could significantly improve its ability to detect LVOs [19].…”

Section: Discussionmentioning

confidence: 99%

Optimization of Large Vessel Occlusion Detection in Acute Ischemic Stroke Using Machine Learning Methods

Tarkanyi

Tényi²,

Hollós³

et al. 2022

Life

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The early detection of large-vessel occlusion (LVO) strokes is increasingly important as these patients are potential candidates for endovascular therapy, the availability of which is limited. Prehospital LVO detection scales mainly contain symptom variables only; however, recent studies revealed that other types of variables could be useful as well. Our aim was to comprehensively assess the predictive ability of several clinical variables for LVO prediction and to develop an optimal combination of them using machine learning tools. We have retrospectively analysed data from a prospectively collected multi-centre stroke registry. Data on 41 variables were collected and divided into four groups (baseline vital parameters/demographic data, medical history, laboratory values, and symptoms). Following the univariate analysis, the LASSO method was used for feature selection to select an optimal combination of variables, and various machine learning methods (random forest (RF), logistic regression (LR), elastic net method (ENM), and simple neural network (SNN)) were applied to optimize the performance of the model. A total of 526 patients were included. Several neurological symptoms were more common and more severe in the group of LVO patients. Atrial fibrillation (AF) was more common, and serum white blood cell (WBC) counts were higher in the LVO group, while systolic blood pressure (SBP) was lower among LVO patients. Using the LASSO method, nine variables were selected for modelling (six symptom variables, AF, chronic heart failure, and WBC count). When applying machine learning methods and 10-fold cross validation using the selected variables, all models proved to have an AUC between 0.736 (RF) and 0.775 (LR), similar to the performance of National Institutes of Health Stroke Scale (AUC: 0.790). Our study highlights that, although certain neurological symptoms have the best ability to predict an LVO, other variables (such as AF and CHF in medical history and white blood cell counts) should also be included in multivariate models to optimize their efficiency.

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Effect of Known Atrial Fibrillation and Anticoagulation Status on the Prehospital Identification of Large Vessel Occlusion

Cited by 6 publications

References 10 publications

Left Atrial Enlargement on Non-Gated CT Is Associated with Large Vessel Occlusion in Acute Ischaemic Stroke

Left Atrial Enlargement on Non-Gated CT Is Associated with Large Vessel Occlusion in Acute Ischaemic Stroke

Contraindications to intravenous thrombolysis in prehospital triage of thrombectomy candidates

Optimization of Large Vessel Occlusion Detection in Acute Ischemic Stroke Using Machine Learning Methods

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