Prehospital Large Vessel Occlusion Research Articles

Headpulse measurement can reliably identify large-vessel occlusion stroke in prehospital suspected stroke patients: Results from the EPISODE-PS-COVID study.

Large-vessel occlusion (LVO) stroke represents one-third of acute ischemic stroke (AIS) in the United States but causes two-thirds of poststroke dependence and >90% of poststroke mortality. Prehospital LVO stroke detection permits efficient emergency medical systems (EMS) transport to an endovascular thrombectomy (EVT)-capable center. Our primary objective was to determine the feasibility of using a cranial accelerometry (CA) headset device for prehospital LVO stroke detection. Our secondary objective was development of an algorithm capable of distinguishing LVO stroke from other conditions. We prospectively enrolled consecutive adult patients suspected of acute stroke from 11 study hospitals in four different U.S. geographical regions over a 21-month period. Patients received device placement by prehospital EMS personnel. Headset data were matched with clinical data following informed consent. LVO stroke diagnosis was determined by medical chart review. The device was trained using device data and Los Angeles Motor Scale (LAMS) examination components. A binary threshold was selected for comparison of device performance to LAMS scores. A total of 594 subjects were enrolled, including 183 subjects who received the second-generation device. Usable data were captured in 158 patients (86.3%). Study subjects were 53% female and 56% Black/African American, with median age 69 years. Twenty-six (16.4%) patients had LVO and 132 (83.6%) were not LVO (not-LVO AIS, 33; intracerebral hemorrhage, nine; stroke mimics, 90). COVID-19 testing and positivity rates (10.6%) were not different between groups. We found a sensitivity of 38.5% and specificity of 82.7% for LAMS ≥ 4 in detecting LVO stroke versus a sensitivity of 84.6% (p < 0.0015 for superiority) and specificity of 82.6% (p = 0.81 for superiority) for the device algorithm (CA + LAMS). Obtaining adequate recordings with a CA headset is highly feasible in the prehospital environment. Use of the device algorithm incorporating both CA and LAMS data for LVO detection resulted in significantly higher sensitivity without reduced specificity when compared to the use of LAMS alone.

Abstract TMP13: Prehospital Stroke Scales Are Non-Inferior to NIHSS in Prediction of Intravenous Thrombolysis Use in a Large Telestroke Network

Introduction: Recent studies report similar outcomes with antiplatelet drugs and intravenous thrombolysis (IVT) in patients with minor nondisabling ischemic stroke. These patients still meet emergent triage criteria and can increase the burden on stroke systems through prehospital stroke activation. Prehospital large vessel occlusion (LVO) scales can improve triage of LVO patients but have not been evaluated as tools to predict IVT administration. We sought to determine if common LVO scales can predict IVT use in a large academic telestroke practice. Methods: This retrospective study included all video telestroke consults performed in a large academic telestroke network from 2019-2020. Patients were excluded if they were on anticoagulation, presented beyond 4.5 hours from last known well, or family declined IVT due to goals of care. We recorded presenting NIHSS and IVT recommendations. NIHSS was used to calculate 7 LVO scales (RACE, G-FAST, FAST-ED, VAN, PASS, 3I-SS, and C-STAT). Scale performance was assessed by calculating area under curve (AUC) and compared to NIHSS total score using the DeLong test. Youden cutpoint was established for each scale and subsequently used to calculate sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and accuracy. Results: A total of 513 patients were included; 205/513 (40%) were recommended IVT. Median (IQR) NIHSS was 1 (0-3) in non-IVT patients and 6 (4-11) in IVT patients. The RACE and G-FAST scales were noninferior to the NIHSS in predicting IVT recommendation (Table 1). Conclusion: The RACE and G-FAST scales may be useful triage tools to identify patients needing emergent stroke evaluation for consideration of IVT.

Large‐Vessel Occlusion Stroke Knowledge and Training for Stroke Severity Assessment Among Emergency Medical Services Personnel in the United States

BACKGROUND Prehospital identification of large‐vessel occlusion (LVO) stroke facilitates the development of a regional triage protocol that could lead to an improvement in intrahospital and interhospital workflows. This requires stroke education of emergency medical services (EMS) personnel to improve stroke recognition, severity assessment, and prenotification. However, the current state of EMS personnel's knowledge of LVO stroke, their training for stroke severity assessment, and their preferences for educational methods are unknown. We conducted a nationwide EMS survey across the United States to glean insights that can inform and customize future EMS educational efforts. METHODS The Society of Vascular and Interventional Neurology, in collaboration with EMS World , created an online questionnaire for EMS personnel. It included 12 multiple‐choice and free‐response questions designed to test participants’ clinical knowledge of LVO, knowledge of stroke center certification levels, prior LVO educational experiences, preferences for educational content delivery, and perspectives on prehospital hurdles to stroke care. All subscribers of EMS World received a survey link via email. RESULTS Of the 38 486 subscribers of EMS World , the survey email was opened by 1830, of whom 1107 completed the survey across all states in the United States, with a response rate of 2.9%. Most of the respondents identified themselves as paramedics/emergency medical technicians (91%). The number of patients with stroke that survey participants transported in the past year was &lt;10 for 618 (56%). Only 285 (26%) participants answered both LVO knowledge questions correctly, and only 128 (12%) respondents correctly identified all types of stroke centers with thrombectomy capability. A total of 362 EMS personnel (33%) denied receiving training to perform LVO severity assessment. Respondents who received training to perform an LVO scale demonstrated nearly twice the prevalence of LVO knowledge (30.6% versus 15.7%; prevalence ratio, 1.94 [95% CI, 1.50–2.53]) than respondents who did not receive training. The top hurdle to prehospital LVO education was identified as the lack of standardized LVO training by 535 (48%) respondents. CONCLUSIONS EMS providers in the United States reported inadequate LVO training and demonstrated gaps in knowledge of LVO, stroke severity scales, and stroke center levels. Systematic efforts to enhance and standardize the educational content and delivery of LVO education are needed.

Optimizing Patient-Centered Stroke Care and Research in the Prehospital Setting.

Over the past decades, continuous technological advances and the availability of novel therapies have enabled treatment of more acute medical conditions than ever before. Many of these treatments, such as intravenous thrombolysis and mechanical thrombectomy for acute ischemic stroke, are highly time sensitive. This has raised interest in shifting advanced acute care from hospitals to the prehospital setting. Key objectives of advanced prehospital stroke care may include (1) early targeted treatments in the prehospital setting, for example, intravenous thrombolysis for acute stroke, and (2) advanced prehospital diagnostics such as prehospital large vessel occlusion and intracranial hemorrhage detection, to help inform patient triage and potentially reduce subsequent workload in emergency departments. Major challenges that may hamper a swift transition to more advanced prehospital care are related to conducting clinical trials in the prehospital setting to provide sufficient evidence for emergency interventions, as well as ambulance design, infrastructure, emergency medical service personnel training and workload, and cost barriers. Utilizing new technologies such as telemedicine, mobile stroke units and portable diagnostic devices, customized software applications, and smart storage space management may help surmount these challenges and establish efficient, targeted care strategies that are achievable in the prehospital setting. In this article, we delineate the paradigm of shifting advanced stroke care to the prehospital setting and outline future directions in providing evidence-based, patient-centered prehospital care. While we use acute stroke as an illustrative example, these principles are not limited to stroke patients and can be applied to prehospital triage for any time-critical disease.

Mechanical Thrombectomy Global Access For Stroke (MT-GLASS): A Mission Thrombectomy (MT-2020 Plus) Study.

Despite the well-established potent benefit of mechanical thrombectomy (MT) for large vessel occlusion (LVO) stroke, access to MT has not been studied globally. We conducted a worldwide survey of countries on 6 continents to define MT access (MTA), the disparities in MTA, and its determinants on a global scale. Our survey was conducted in 75 countries through the Mission Thrombectomy 2020+ global network between November 22, 2020, and February 28, 2021. The primary end points were the current annual MTA, MT operator availability, and MT center availability. MTA was defined as the estimated proportion of patients with LVO receiving MT in a given region annually. The availability metrics were defined as ([current MT operators×50/current annual number of estimated thrombectomy-eligible LVOs]×100 = MT operator availability) and ([current MT centers×150/current annual number of estimated thrombectomy-eligible LVOs]×100= MT center availability). The metrics used optimal MT volume per operator as 50 and an optimal MT volume per center as 150. Multivariable-adjusted generalized linear models were used to evaluate factors associated with MTA. We received 887 responses from 67 countries. The median global MTA was 2.79% (interquartile range, 0.70-11.74). MTA was <1.0% for 18 (27%) countries and 0 for 7 (10%) countries. There was a 460-fold disparity between the highest and lowest nonzero MTA regions and low-income countries had 88% lower MTA compared with high-income countries. The global MT operator availability was 16.5% of optimal and the MT center availability was 20.8% of optimal. On multivariable regression, country income level (low or lower-middle versus high: odds ratio, 0.08 [95% CI, 0.04-0.12]), MT operator availability (odds ratio, 3.35 [95% CI, 2.07-5.42]), MT center availability (odds ratio, 2.86 [95% CI, 1.84-4.48]), and presence of prehospital acute stroke bypass protocol (odds ratio, 4.00 [95% CI, 1.70-9.42]) were significantly associated with increased odds of MTA. Access to MT on a global level is extremely low, with enormous disparities between countries by income level. The significant determinants of MT access are the country's per capita gross national income, prehospital LVO triage policy, and MT operator and center availability.

Abstract Number: LBA3 Head Pulse For Ischemic Stroke Detection Prehospital Study During COVID‐19 Pandemic (EPISODE‐PS‐COVID): Initial Trial Results

Introduction Prehospital identification of large vessel occlusion (LVO) ischemic stroke using stroke scoring tools based upon physical exam findings is highly user‐dependent and associated with poor specificity. Measurement of the “headpulse” by cranial accelerometry has been previously shown to reliably identify LVO in a hospitalized group of suspected stroke patients, but the utility of this technology in the prehospital environment remains unclear. The EPISODE‐PS‐COVID study was designed to evaluate the use of a novel triaxial cranial accelerometry device (Harmony, MindRhythm, Inc.) for predicting LVO using prehospital data. Methods Paramedics from multiple emergency medical services (EMS) agencies were trained in placement of the Harmony device. Patients suspected of LVO stroke by EMS personnel received placement of the non‐invasive headband device in the field, and prehospital data were collected over a 3‐minute period prior to hospital arrival. Headpulse data were then compared to clinical data collected during a subsequent emergency department (ED) and hospital visit, including results of brain computed tomography angiogram (CTA) as the gold standard for LVO diagnosis. Patients were consented for inclusion in the study after hospital arrival, utilizing a delayed consent model, as approved by the local institutional review board (IRB). Los Angeles Motor Scale (LAMS) scores were also calculated by prehospital providers for comparison with headpulse measurements. Results A total of 377 enrollments were made at six participating hospitals over a period of 18 months (April 2021 – September 2022), including 92 subjects with recordings free of technical recording errors who were able to provide informed consent for use of their data. Nine (9.8%) subjects were confirmed to have LVO by subsequent CTA, while 15 (16.3%) were diagnosed with non‐LVO ischemic stroke, seven (7.6%) with intracranial hemorrhage, and 61 (66.3%) with stroke mimics. The Harmony device algorithm correctly identified seven of nine LVO strokes, resulting in 78% sensitivity, as well as 82 of 83 non‐LVO diagnoses (99% specificity, p &lt; 0.0001). In this data set, contemporaneous LAMS score demonstrated 44% sensitivity and 82% specificity (p = 0.087). Device innovation during the trial significantly reduced the number of technical errors. Device performance numerically exceeded the LAMS score, with p = 0.099. Conclusions Data from this pilot study suggest that the Harmony device has a sensitivity and specificity that may be non‐inferior to the LAMS score when tested in an undifferentiated population of suspected stroke patients. Although the sample size is underpowered to test for superiority, enrollment in the trial is ongoing. A blinded, pivotal trial will begin soon. The use of a non‐invasive device to detect LVO has substantial implications for prehospital LVO stroke management, including the potential for improved triage and improved outcomes for patients with LVO stroke, without delaying care for non‐LVO stroke patients.

Abstract TMP46: Large Vessel Occlusion Stroke Knowledge And Clinical Training In Emergency Medical Service Personnel In The United States

Background: Stroke education of emergency medical service (EMS) personnel improves stroke recognition, prenotification, and thrombolytic delivery. Prehospital identification of large vessel occlusion (LVO) stroke may facilitate the creation of a regional bypass protocol and improvement of intrahospital and interhospital workflows. However, the current status of EMS personnel’s knowledge of LVO, their stroke severity assessment training, and preferences in educational methods have not been studied. We conducted an EMS survey across the United States. Methods: The Society of Vascular and Interventional Neurology (SVIN) in collaboration with EMS-World created an online questionnaire distributed to all subscribers of EMS-World involved in pre-hospital work. It included 12 multiple-choice questions to test participants on LVO knowledge, stroke center certification levels, prior LVO education, and preferences on educational content delivery. Results: The survey email was opened by 1830 subscribers out of whom 1107 (60%) completed the survey across 50 states in the United States. Respondents identified themselves as paramedics/EMTs (91.4%), ground critical care (5.7%) and flight crew (2.9%). The number of stroke patients that survey participants transported in the past year was &lt;10 for 618 (55.8%), 10 to 25 for 332 (30%), and &gt;25 (14.2%). Two hundred eighty-five (25.8%) participants answered both LVO knowledge questions correctly and 379 (34.2%) answered one correctly. Only 128 (11.6%) correctly identified all types of centers with thrombectomy capability. Although 877 (79.2%) were familiar with at least one stroke severity scale, 376 (34%) denied receiving training to perform them. Five sixty-seven (51.2%) respondents preferred in-person training for LVO training and 429 (38.8%) an online training program. About half of all respondents (535,48%) picked 'lack of standardized LVO training' as the greatest hurdle to pre-hospital LVO management. Conclusion: EMS providers in the United States reported inadequate LVO training and demonstrated gaps in knowledge of LVO, stroke severity scales, and stroke center levels. Systematic efforts to enhance and standardize the educational content and delivery of LVO education are urgently needed.

Impact of prehospital stroke triage implementation on patients with intracerebral hemorrhage.

Little is known about how prehospital triage using large vessel occlusion (LVO) stroke prediction scales affects patients with intracerebral hemorrhage (ICH). We aimed to investigate whether the Stockholm Stroke Triage System (SSTS) implemented in 2017 has affected timing and outcomes of acute ICH neurosurgery, and to assess system triage accuracy for ICH with a neurosurgical indication or LVO thrombectomy. Observational cohort study. In the Stockholm Region, we compared surgical timing, functional outcome, and death at 3 months in patients transported by code-stroke ground ambulance who had ICH neurosurgery, 2 years before versus 2 years after SSTS implementation. We also calculated triage precision metrics for treatment with either ICH neurosurgery or thrombectomy. A total of 36 patients undergoing ICH neurosurgery were included before SSTS implementation and 30 after. No significant difference was found in timing of neurosurgery [median 7.5 (4.9-20.7) versus 9.1 (6.1-12.5) h after onset], distribution of functional outcomes (median 4 versus 4), and death at 3 months [3/29 (9%) versus 5/35 (17%)] before versus after implementation, respectively. The SSTS routed a larger proportion of patients subsequently undergoing ICH neurosurgery directly to the comprehensive stroke center: 13/36 (36%) before versus 18/30 (60%) after implementation. Overall system triage accuracy for ICH neurosurgery or thrombectomy was high at 90%, with 92% specificity and 65% sensitivity. The SSTS, initially designed for prehospital LVO stroke triage, routed more patients with neurosurgical indication for ICH directly to the comprehensive stroke center. This did not significantly affect surgical timing or outcomes.

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

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.

Comparison of large vessel occlusion scales using prehospital patient reports.

Prehospital identification of large vessel occlusion (LVO) holds significant potential to decrease the onset-to-treatment time. Several prehospital scales have been developed to identify LVO but data on their comparison has been limited. The aim of this study was to review the currently available prehospital LVO scales and compare their performance using prehospital data. All patients transported by ambulance using stroke code on a six-month period were enrolled into the study. The prehospital patient reports were retrospectively evaluated by two investigators using sixteen LVO scales identified by literature search and expert opinion. After the evaluation, the computed tomography angiography results were reviewed by a neuroradiologist to confirm or exclude LVO. Sixteen different LVO scales met the predetermined study criteria and were selected for further comparison. Using them, a total of 610 evaluations were registered. The sensitivity of the scales varied between 8%-73%, specificity between 71%-97% and overall accuracy between 71%-87%. The areas under curve (AUC) varied between 0.61-0.80 for the whole scale range and 0.53%-0.74 for the scales' binary cut-offs. The Field Assessment Stroke Triage for Emergency Destination (FAST-ED) was the only scale with AUC>0.8. Regarding scales' binary cut-offs, The FAST-ED (0.70), Gaze - Face Arm Speech Time (G-FAST) (0.74) and Emergency Medical Stroke Assessment (EMSA) (0.72) were the only scales with AUC>0.7. In a comparison of 16 different LVO scales, the FAST-ED, G-FAST and EMSA achieved the highest overall performance.

Prehospital identification of large vessel occlusion using the FAST-ED score.

The prehospital identification of stroke patients with large vessel occlusion (LVO) enables appropriate hospital selection and reduces the onset-to-treatment time. The aim of this study was to investigate whether the Field Assessment Stroke Triage for Emergency Destination (FAST-ED) scale could be reconstructed from existing prehospital patient reports and to compare its performance with neurologist's clinical judgement using the same prehospital data. All patients transported by ambulance using stroke code on a six-month period were registered for the study. The prehospital patient reports were retrospectively evaluated using the FAST-ED scale by two investigators. The performance of FAST-ED score (≥4 points) in LVO identification was compared to neurologist's clinical judgement ('LVO or not'). The presence of LVO was verified using computed tomography angiography imaging. A total of 610 FAST-ED scores were obtained. The FAST-ED had a sensitivity of 57.8%, specificity of 87.2%, positive predictive value (PPV) of 37.3%, negative predictive value (NPV) of 93.4% and area under curve (AUC) of 0.724. Interclass correlation coefficient for both raters over the entire range of FAST-ED was 0.92 (0.88-0.94). The neurologist's clinical judgement raised sensitivity to 79.4%, NPV to 97.1% and PPV to 45.0% with an AUC of 0.837 (p<.05). The existing patient report data could be feasibly used to reconstruct FAST-ED scores to identify LVO. The binary FAST-ED score had a moderate sensitivity and good specificity for prehospital LVO identification. However, the FAST-ED was surpassed by neurologist's clinical judgement which further increased the sensitivity of identification.

Detection of Large Vessel Occlusion Stroke in the Prehospital Setting: Electroencephalography as a Potential Triage Instrument.

A reliable and fast instrument for prehospital detection of large vessel occlusion (LVO) stroke would be a game-changer in stroke care, because it would enable direct transportation of LVO stroke patients to the nearest comprehensive stroke center for endovascular treatment. This strategy would substantially improve treatment times and thus clinical outcomes of patients. Here, we outline our view on the requirements of an effective prehospital LVO detection method, namely: high diagnostic accuracy; fast application and interpretation; user-friendliness; compactness; and low costs. We argue that existing methods for prehospital LVO detection, including clinical scales, mobile stroke units and transcranial Doppler, do not fulfill all criteria, hindering broad implementation of these methods. Instead, electroencephalography may be suitable for prehospital LVO detection since in-hospital studies have shown that quantification of hypoxia-induced changes in the electroencephalography signal have good diagnostic accuracy for LVO stroke. Although performing electroencephalography measurements in the prehospital setting comes with challenges, solutions for fast and simple application of this method are available. Currently, the feasibility and diagnostic accuracy of electroencephalography in the prehospital setting are being investigated in clinical trials.

Prospective Evaluation of a Two-Scale Protocol for Prehospital Large Vessel Occlusion Detection

Background and purposes: Stroke severity scales may expedite prehospital large vessel occlusion (LVO) stroke detection, but few are validated for paramedic use. We evaluated the feasibility of introducing the Cincinnati Stroke Triage Assessment Tool (C-STAT) in the field and its capacity to detect LVO stroke. Methods: We performed a prospective paramedic-based study assessing C-STAT in the field on patients currently redirected to two comprehensive stroke centers (CSC), based on a Cincinnati Prehospital Stroke Scale (CPSS) score of 3/3. C-STAT was administered by on-site paramedics with telephone guidance from trained centralized clinical support paramedics. Results: Between October 2018 and November 2019, C-STAT scores were obtained in 188/218 (86.2%) patients, among which 118/188 (62.8%) were positive. Paramedics reported performing the C-STAT in less than 5 minutes on 170/188 (90.4%) patients and noted no difficulties administering the scale in 151/188 (80.3%). A positive C-STAT identified 51/68 (75%) LVO strokes in the cohort, demonstrating a 43% (95% CI: 38%–48%) positive and 76% (95% CI: 66%–83%) negative predictive value for LVO stroke diagnosis. In a cohort of 100 patients with CPSS 3/3, requiring a positive C-STAT for redirection would decrease CSC patient volume by 37 but miss 9 of 36 LVO strokes. Conclusion: Prehospital administration of the C-STAT was feasible, using a model of minimal paramedic training and real-time telephone guidance. A protocol based on both a CPSS 3/3 and a positive C-STAT would decrease CSC redirected patient volume by one-third but would miss one-quarter of LVO strokes when compared to a CPSS-based protocol.

Current Methods for the Prehospital Detection of Large Vessel Occlusion (LVO) Ischemic Stroke

This review describes the technologies and methods currently utilized to detect large vessel occlusion (LVO) ischemic stroke in the prehospital setting. A comparison of various LVO stroke scales, including their similarities and differences, is included. Emerging technology, novel stroke detection methods, and likely areas of future research are discussed. Many prehospital stroke detection scales have been described previously in the medical literature, characterized by varying degrees of efficacy. Despite their cost-effectiveness and ease of use, prehospital stroke scales do not reliably detect LVO. Current efforts in prehospital LVO stroke detection are aimed at improving upon the sensitivity and specificity of these scales, leveraging new screening technologies to streamline LVO triage and decrease time-to-intervention. The prehospital stroke scales that we reviewed differ greatly in many respects, including their definition of LVO and the type and number of items tested. Despite the tremendous global effort made to rapidly triage and deliver LVO stroke patients to definitive treatment centers, no single scale has emerged with both a high positive predictive value (PPV) and negative predictive value (NPV). This has led to a lack of consensus, preventing widespread adoption of a single scale for prehospital LVO detection. Despite the ever-increasing number of stroke scales available to the prehospital clinician, LVO detection remains a challenge. Future advances in prehospital LVO stroke detection are expected to involve new and improved in-field diagnostic testing.

Field Assessment of Critical Stroke by Emergency Services for Acute Delivery to a Comprehensive Stroke Center: FACE2AD.

Patients with acute ischemic stroke (AIS) due to large vessel occlusion (LVO) should be triaged to an endovascular-capable hospital by the emergency medical service (EMS). We designed a prehospital LVO prediction scale based on EMS assessments. In the derivation cohort, 1157 patients transferred to our hospital by the EMS because of suspected stroke within 24 h of onset were retrospectively examined. Factors associated with AIS due to LVO were identified based on the EMS assessment, and a prehospital scale identifying LVO was developed. The accuracy of this scale was validated in 502 consecutive patients who were transferred to 4 stroke centers, and its accuracy was compared with those of 4 previously reported scales. AIS due to LVO was diagnosed in 149 of 1157 patients (13%) in the derivation cohort. One point each was assigned for facial palsy, arm weakness, consciousness impairment (cannot say his/her name), atrial fibrillation, and diastolic blood pressure ≤ 85 mmHg, with two points for conjugate eye deviation (FACE2AD scale). In the derivation cohort, with the optimal cut-point of FACE2AD ≥ 3 determined by the area under the curve (AUC; 0.88; 95% confidence interval 0.87-0.90), sensitivity, specificity, positive predictive value, and negative predictive value for FACE2AD to predict LVO were 0.85, 0.80, 0.39, and 0.97, respectively. In the validation cohort, the FACE2AD scale had higher accuracy, with an AUC value of 0.84 for predicting LVO compared with the other scales (all p < 0.01). The FACE2AD scale is a simple, reliable tool for identifying AIS due to LVO by the EMS.

Vision, Aphasia, Neglect Assessment for Large Vessel Occlusion Stroke

Background and PurposeVision, Aphasia, Neglect (VAN) is a large vessel occlusion (LVO) screening tool that was initially tested in a small study where emergency department (ED) nurses were trained to perform VAN assessment on stroke code patients. We aimed to validate the VAN assessment in a larger inpatient dataset. MethodsWe utilized a large dataset and used National Institute of Health Stroke Scale (NIHSS) performed by physicians to extrapolate VAN. VAN was compared to NIHSS greater than or equal to 6 and established prehospital LVO screening tools including Rapid Arterial Occlusion Evaluation scale (RACE), Field Assessment Stroke Triage for Emergency Destination (FAST-ED), and Cincinnati Pre-hospital Stroke Scale (CPSS). Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and area under receiver operating characteristics curve was calculated to estimate the predictive value of LVO. ResultsVAN was comparable in sensitivity (79% versus 80%) and NPV (88% versus 87%) to NIHSS greater than or equal to 6. It was superior in specificity (69% versus 57%), PPV (53% versus 46%) and accuracy to NIHSS greater than or equal to 6 (72% versus 64%) with significant receiver operating curve (.74 versus .69, P = .02).VAN also had comparable area under the curve when compared to RACE, FAST-ED, and CPSS however slightly lower accuracy (69%-73%) compared to RACE (76%), FAST-ED (77%), and CPSS (75%). VAN had the highest NPV among all screening assessments (88%). ConclusionsVAN is a simple screening tool that can identify LVOs with adequate accuracy in hospital setting. Future studies need to be conducted in prehospital setting to validate its utility to detect LVOs in the field.

Decision Analysis Model for Prehospital Triage of Patients With Acute Stroke.

Background and Purpose- We used a decision analysis approach to analyze triage strategies for patients with acute stroke symptoms while accounting for prehospital large vessel occlusion (LVO) screening methods and key time metrics. Methods- Our decision analysis compared anticipated functional outcomes for patients within the IV-tPA (intravenous tissue-type plasminogen activator) treatment window in the mothership and drip-and-ship frameworks. Key branches of the model included IV-tPA eligibility, presence of an LVO, and endovascular therapy eligibility. Our decision analysis evaluated 2 prehospital LVO screening approaches: (1) no formal screening and (2) the use of clinical LVO screening scales. An excellent outcome was defined as modified Rankin Scale scores 0-1. Probabilities and workflow times were guideline-based or imputed from published studies. In sensitivity analyses, we individually and jointly varied transport time to the nearest primary stroke center, additional time required to transport directly to a comprehensive stroke center, and LVO screening scale predictive probabilities. We evaluated 2 separate scenarios: one in which ideal time metrics were achieved and one under current real-world metrics. Results- In the ideal metrics scenario, the drip-and-ship strategy was almost always favored in the absence of formal LVO screening. For patients screened positive for an LVO, mothership was favored if the additional transport time to the comprehensive stroke center was <3 to 23 minutes. Under real-world conditions, in which primary stroke center workflow is slower than ideal, the mothership strategy was favored in more scenarios, regardless of formal LVO screening. For example, mothership was favored with an additional transport time to the comprehensive stroke center of <32 to 99 minutes for patients screened positive for an LVO and <28 to 39 minutes in the absence of screening. Conclusions- Joint consideration of LVO probability, screening, workflow times, and transport times may improve prehospital stroke triage. Drip-and-ship was more favorable when more ideal primary stroke center workflow times were modeled.

Performance of the RACE Score for the Prehospital Identification of Large Vessel Occlusion Stroke in a Suburban/Rural EMS Service

Introduction: Emergency Medical Services (EMS) providers may identify and preferentially transport patients experiencing large vessel occlusion (LVO) stroke to appropriate treatment centers. The Rapid Arterial oCclusion Evaluation (RACE) scale was created for prehospital LVO detection, yet few studies have evaluated its function in real-world EMS settings. Our objective was to assess the prehospital performance of the RACE scale for detecting LVO stroke following implementation at a large suburban/rural agency in the United States. Methods: In this retrospective analysis, all 9-1-1 patients with an EMS provider primary or secondary impression of stroke treated by the agency between June 1, 2016 and November 1, 2017 were eligible for inclusion. Patient data were abstracted using a standardized form completed by receiving hospitals. Performance for LVO detection at each RACE cutoff value was evaluated using sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). A receiver operating characteristic (ROC) curve was used to evaluate the discrimination of the RACE scale overall. A secondary analysis of RACE for patients experiencing strokes best treated at comprehensive stroke centers (LVO and intracerebral hemorrhage [ICH]) was conducted. Results: There were 440 patients with a documented RACE score and hospital outcome data included in the analysis. About half (51%, n = 220) were female and the median age was 70 years (IQR: 59–81). Last known well time was under 4.5 hours for 76% of patients (n = 261). Over half (61%, n = 269) had a hospital discharge diagnosis of stroke and 64/440 (15%) were classified as LVO. The ROC curve demonstrated adequate discrimination with a c-statistic of 0.72. Performance for identifying LVO in the prehospital setting was greatest for RACE scores ≥5 with a sensitivity of 66% and specificity of 72%, PPV of 29%, and NPV of 93%. A RACE score ≥5 for both LVO and ICH demonstrated sensitivity: 63%, specificity: 77%, PPV: 47% and NPV: 86%. Conclusion: The RACE scale demonstrated acceptable discrimination, yet the sensitivity and positive predictive value were lower in this cohort of EMS professionals in the United States than in the original validation study conducted in Spain. Further work is needed to determine the optimal prehospital screening tool for identification of LVO.

Abstract WP288: Impact of Prehospital LVO Tools on the Delay of Care and Redistribution of Patients between Primary and Comprehensive Stroke Centers

Introduction: Several tools have been developed aimed at predicting large vessel occlusion (LVO) in the prehospital setting. If these tools are used to bypass Alteplase-but-not-thrombectomy-capable hospitals, this would speed the care for some patients, delay it for others, and unnecessarily redistribute some patients between hospitals. Methods: We examined a hypothetical scenario of 1,000 patients evaluated by EMS for possible stroke. We used data published by RACE (Rapid Arterial oCclusion Evaluation) that included 357 patients to calculate the rates of the different stroke subtypes. Ischemic stroke represented 67.2% of patients, hemorrhagic stroke 14.6%, transient ischemic attack 5.6%, and stroke mimic 12.6%. We applied the following assumptions: rate of LVO as 20% of total ischemic stroke, all patients evaluated by EMS within 3 hours from their last known well time with a rate of tPA utilization is 50%, endovascular-capable hospital is further away, similar door-to-needle (DTN) time in all hospitals, delay in DTN in false positive patients, and delay in door-to-groin time (DTG) in false negative patients. Seven tools were studied using published values for sensitivity and specificity. Results: Using no tools would lead to evaluation of all patients at the nearer hospital first, leading to delay in DTG of all 134 LVO patients, however no delay in DTN. Comparing the various tools, DTN delay would be highest with Cincinnati Prehospital Stroke Severity Scale (CPSSS; n=175) and least with 3-item stroke scale (3I-SS; n=23). DTG delay would be highest with Prehospital Acute Stroke Severity (PASS) and Field Assessment Stroke Triage for Emergency Destination (FAST-ED) (n=52 for both) and least with RACE (n=20). Redistribution of patients would be highest with CPSSS and lowest with 3I-SS (reduction in patient volume to non-thrombectomy capable hospital 63% and 16% respectively and increase in volume for the thrombectomy-capable hospital by 371% and 19% respectively). Conclusion: Current tools have a very wide variation in performance. Although some tools would likely reduce the delay in DTG time for most (but not all) LVO patients, they risk delaying care for other patients and may cause an unnecessary redistribution of patients between hospitals.

Abstract TP298: Early and Extended Time Window Prehospital Large Vessel Occlusion Scale Application: A Retrospective Analysis

Introduction: Multiple trials have validated thrombectomy as a viable option in acute stroke patients with Anterior Large Vessel Occlusion (LVO). As a consequence, there has been a dire need for proper routing of patients. Currently, there are established prehospital scales but limited evidence for late window LVO screening. Methods: We assessed 748 patients, from June 2016 to June 2018, who presented within a 24 hour last known well time (LKWT) and were assessed with RAPID neuroimaging and CT angiography. An analysis was completed of patients with LVOs versus those without a LVO. Patient’s medical records were reviewed to obtain their baseline presenting NIHSS, which was used to derive 14 corresponding LVO stroke scale values. Patients excluded had absent NIHSS values and unknown LKWT. LVO stroke scales excluded evaluated history of seizures, seizure at onset, grip strength, or age &gt; 45 as criteria. Results: A total of 748 consecutive patients (67 years, 51% male, 49% African American) were analyzed with 110 confirmed anterior LVO, 476 patients in the 0-6-hour (hr) window, and 272 in the 6-24-hr window. In the 0-6-hr window, the top three scales in sensitivity were ranked in order of C-STAT (0.83) &gt; MaPSS (0.81) &gt; VAN (0.80). In the 6-24-hr window, the top three scales that ranked equally in sensitivity were MaPSS (0.75), VAN (0.75), and C-STAT (0.75). In the 0-6-hr window, the top three scales in specificity were ranked in order of 3-ISS (0.88) &gt; MiPSS (0.76) &gt; FPSS (0.72) = sNIHSS-8 (0.72). In the 6-24-hr window, the top three scales in specificity were ranked in order of 3-ISS (0.90) &gt; MiPSS (0.84) &gt; FPSS (0.83). (See Table 1). Conclusion: To correctly identify as many patients as possible in the pre-hospital setting with the available scales, the data suggests that C-STAT, VAN, and MaPSS are effective within the early and late windows. To reduce routing of incorrect prehospital LVO identification, the data suggests that 3-ISS, MiPSS, and FPSS are effective in the early and late windows