The Large ARtery Intracranial Occlusion Stroke Scale: A New Tool With High Accuracy in Predicting Large Vessel Occlusion

Management of possible stroke by laypeople in pre-hospital setting: who should we train?

BACKGROUND AND AIM

The pre-hospital management of a possible stroke is fundamental for the transport of patients to the correct HUB facility; thus, they must be transported to the Emergency Department (ED) by EMS vehicles. Our study aims to analyze the factors correlated with a higher probability of accessing the ED through the EMS in this event.

METHODS

This is a retrospective observational study. All accesses in the 120 EDs of the Lombardy region, with a diagnosis of discharge whose symptoms could resemble CPSS, were analyzed between 1 January 2019 and 31 December 2019.

RESULTS

We identified an increased probability of using the EMS vehicles of 0,05% (I.C. 95%: 0.04% - 0.06%; p<0.0001) for each additional year of age, considering patients aged 20 to 100 years and the percentage was significantly higher in the female population (58% vs 49%; p<0.001). Moreover, we calculated that the incidence of stroke was approximately 140 cases per 100,000 inhabitants.

CONCLUSIONS

Only half of the citizens in the Lombardy region use the EMS in case of suspicion of stroke; further information campaigns are essential to educate citizens. Information strategies should be directed especially at men between 30 and 59 years old.

Emerging Detection Techniques for Large Vessel Occlusion Stroke: A Scoping Review

Background: Large vessel occlusion (LVO) is the obstruction of large, proximal cerebral arteries and can account for up to 46% of acute ischaemic stroke (AIS) when both the A2 and P2 segments are included (from the anterior and posterior cerebral arteries). It is of paramount importance that LVO is promptly recognised to provide timely and effective acute stroke management. This review aims to scope recent literature to identify new emerging detection techniques for LVO. As a good comparator throughout this review, the commonly used National Institutes of Health Stroke Scale (NIHSS), at a cut-off of ≥11, has been reported to have a sensitivity of 86% and a specificity of 60% for LVO. Methods: Four electronic databases (Medline via OVID, CINAHL, Scopus, and Web of Science), and grey literature using OpenGrey, were systematically searched for published literature investigating developments in detection methods for LVO, reported from 2015 to 2021. The protocol for the search was published with the Open Science Framework (10.17605/OSF.IO/A98KN). Two independent researchers screened the titles, abstracts, and full texts of the articles, assessing their eligibility for inclusion. Results: The search identified 5,082 articles, in which 2,265 articles were screened to assess their eligibility. Sixty-two studies remained following full-text screening. LVO detection techniques were categorised into 5 groups: stroke scales (n = 30), imaging and physiological methods (n = 15), algorithmic and machine learning approaches (n = 9), physical symptoms (n = 5), and biomarkers (n = 3). Conclusions: This scoping review has explored literature on novel and advancements in pre-existing detection methods for LVO. The results of this review highlight LVO detection techniques, such as stroke scales and biomarkers, with good sensitivity and specificity performance, whilst also showing advancements to support existing LVO confirmatory methods, such as neuroimaging.

Comparison of Prehospital Scales for Predicting Large Anterior Vessel Occlusion in the Ambulance Setting

Importance

The efficacy of endovascular thrombectomy (EVT) for symptomatic large anterior vessel occlusion (sLAVO) sharply decreases with time. Because EVT is restricted to comprehensive stroke centers, prehospital triage of patients with acute stroke codes for sLAVO is crucial, and although several prediction scales are already in use, external validation, head-to-head comparison, and feasibility data are lacking.

Objective

To conduct external validation and head-to-head comparisons of 7 sLAVO prediction scales in the emergency medical service (EMS) setting and to assess scale feasibility by EMS paramedics.

Design, Setting, and Participants

This prospective cohort study was conducted between July 2018 and October 2019 in a large urban center in the Netherlands with a population of approximately 2 million people and included 2 EMSs, 3 comprehensive stroke centers, and 4 primary stroke centers. Participants were consecutive patients aged 18 years or older for whom an EMS-initiated acute stroke code was activated. Of 2812 acute stroke codes, 805 (28.6%) were excluded, because no application was used or no clinical data were available, leaving 2007 patients included in the analyses.

Exposures

Applications with clinical observations filled in by EMS paramedics for each acute stroke code enabling reconstruction of the following 7 prediction scales: Los Angeles Motor Scale (LAMS); Rapid Arterial Occlusion Evaluation (RACE); Cincinnati Stroke Triage Assessment Tool; Prehospital Acute Stroke Severity (PASS); gaze-face-arm-speech-time; Field Assessment Stroke Triage for Emergency Destination; and gaze, facial asymmetry, level of consciousness, extinction/inattention.

Main Outcomes and Measures

Planned primary and secondary outcomes were sLAVO and feasibility rates (ie, the proportion of acute stroke codes for which the prehospital scale could be reconstructed). Predictive performance measures included accuracy, sensitivity, specificity, the Youden index, and predictive values.

Results

Of 2007 patients who received acute stroke codes (mean [SD] age, 71.1 [14.9] years; 1021 [50.9%] male), 158 (7.9%) had sLAVO. Accuracy of the scales ranged from 0.79 to 0.89, with LAMS and RACE scales yielding the highest scores. Sensitivity of the scales ranged from 38% to 62%, and specificity from 80% to 93%. Scale feasibility rates ranged from 78% to 88%, with the highest rate for the PASS scale.

Conclusions and Relevance

This study found that all 7 prediction scales had good accuracy, high specificity, and low sensitivity, with LAMS and RACE being the highest scoring scales. Feasibility rates ranged between 78% and 88% and should be taken into account before implementing a scale.

Usefulness of a single-parameter tool for the prediction of large vessel occlusion in acute stroke

BACKGROUND

In acute stroke, large vessel occlusion (LVO) should be promptly identified to guide patient's transportation directly to comprehensive stroke centers (CSC) for mechanical thrombectomy (MT). In many cases, prehospital multi-parameter scores are used by trained emergency teams to identify patients with high probability of LVO. However, in several countries, the first aid organization without intervention of skilled staff precludes the on-site use of such scores. Here, we assessed the accuracy of LVO prediction using a single parameter (i.e. complete hemiplegia) obtained by bystander's telephone-based witnessing.

PATIENTS AND METHODS

This observational, single-center study included consecutive patients who underwent intravenous thrombolysis at the primary stroke center and/or were directly transferred to a CSC for MT, from January 1, 2015 to March 1, 2020. We defined two groups: patients with initial hemiplegia (no movement in one arm and leg and facial palsy) and patients without initial hemiplegia, on the basis of a bystander's witnessing.

RESULTS

During the study time, 874 patients were included [mean age 73 years (SD 13.8), 56.7% men], 320 with initial hemiplegia and 554 without. The specificity of the hemiplegia criterion to predict LVO was 0.88, but its sensitivity was only 0.53.

CONCLUSION

Our results suggest that the presence of hemiplegia as witnessed by a bystander can predict LVO with high specificity. This single criterion could be used for decision-making about direct transfer to CSC for MT when the absence of emergency skilled staff precludes the patient's on-site assessment, especially in regions distant from a CSC.

Management of acute ischemic stroke

Stroke is the leading cause of long term disability in developed countries and one of the top causes of mortality worldwide. The past decade has seen substantial advances in the diagnostic and treatment options available to minimize the impact of acute ischemic stroke. The key first step in stroke care is early identification of patients with stroke and triage to centers capable of delivering the appropriate treatment, as fast as possible. Here, we review the data supporting pre-hospital and emergency stroke care, including use of emergency medical services protocols for identification of patients with stroke, intravenous thrombolysis in acute ischemic stroke including updates to recommended patient eligibility criteria and treatment time windows, and advanced imaging techniques with automated interpretation to identify patients with large areas of brain at risk but without large completed infarcts who are likely to benefit from endovascular thrombectomy in extended time windows from symptom onset. We also review protocols for management of patient physiologic parameters to minimize infarct volumes and recent updates in secondary prevention recommendations including short term use of dual antiplatelet therapy to prevent recurrent stroke in the high risk period immediately after stroke. Finally, we discuss emerging therapies and questions for future research.

An Introduction to Software Tools, Data, and Services for Geospatial Analysis of Stroke Services

Background: There is interest in the use geospatial data for development of acute stroke services given the importance of timely access to acute reperfusion therapy. This paper aims to introduce clinicians and citizen scientists to the possibilities offered by open source softwares (R and Python) for analyzing geospatial data. It is hoped that this introduction will stimulate interest in the field as well as generate ideas for improving stroke services.

Method: Instructions on installation of libraries for R and Python, source codes and links to census data are provided in a notebook format to enhance experience with running the software. The code illustrates different aspects of using geospatial analysis: (1) creation of choropleth (thematic) map which depicts estimate of stroke cases per post codes; (2) use of map to help define service regions for rehabilitation after stroke.

Results: Choropleth map showing estimate of stroke per post codes and service boundary map for rehabilitation after stroke. Conclusions The examples in this article illustrate the use of a range of components that underpin geospatial analysis. By providing an accessible introduction to these areas, clinicians and researchers can create code to answer clinically relevant questions on topics such as service delivery and service demand.