Stroke Code Patients Research Articles

The In-Hospital Code Stroke: A Look Back and the Road Ahead.

With increased patient volumes and complexity, stroke occurrence in hospitalized patients has become relatively more common. The process of activating a code stroke in-hospital differs in many institutions. An emergency team-based response to inpatient acute code stroke is warranted, with many protocols modeled similarly to the cardiac arrest response. However, several studies have demonstrated delays in recognition and management of acute stroke in-hospital as compared to those arriving directly to the emergency department (ED). Furthermore, there are several shared challenges with code stroke resuscitation in the emergency department and the ward, which include the assembly of ad hoc teams and requirement of access to urgent imaging. Delays in activating in-hospital code stroke contributes to increased morbidity, mortality, prolonged hospitalization, and associated health care costs. In the following commentary, we discuss the current landscape of acute in-hospital code stroke protocols, review the differences in neurologic outcomes between inpatient vs ED/out-of-hospital code stroke patients, and propose future directions for in-hospital code stroke paradigms for improved patient outcomes and quality of care.

Performance of An Automated Algorithm in Large and Medium Vessel Occlusion Detection: A Real-World Experience.

Fast, accurate detection of large (LVO) and medium vessel occlusion (MeVO) is critical for triage and management of acute ischemic stroke. Multiple AIbased software products are commercially available. However, their strengths and limitations for detection of vessel occlusion in the context of expanding indications for mechanical thrombectomy are not entirely understood. We aimed to investigate the performance of a fully automated commercial detection algorithm to identify large and medium vessel occlusions in Code Stroke patients. We utilized a single-center, institutional, retrospective registry of all consecutive code stroke patients with CTA and automated processing using Viz.ai presenting at a comprehensive stroke center between March 2020 and February 2023. LVO was categorized as anterior LVO (aLVO), defined as occlusion of the intracranial internal cerebral artery or M1-middle cerebral artery (MCA), and posterior LVO (pLVO), defined as occlusion of the basilar artery or V4-vertebral artery. MeVO was defined as occlusion of the M2-MCA, A1/A2-anterior cerebral artery, or P1/P2-posterior cerebral artery. Reports from 12 board-certified radiologists were considered the gold standard. We analyzed the performance of the automated algorithm using STARD guidelines. Our primary outcome was accuracy of anterior LVO (aLVO) by the software. Secondary outcomes were accuracy of the software to detect three additional categories: all LVO (aLVO and pLVO), aLVO with M2-MCA, and aLVO with MeVO. Of 3,590 code stroke patients, 3,576 were technically sufficient for analysis by the automated software (median age 67 years; 51% female; 68% White), of which 616 (17.2%) had vessel occlusions. The respective sensitivity and specificity for all four pre-specified categories were: aLVO: 91% (87-94%), 93% (92-94%); all LVO: 73% (68-77%), 92% (91-93%); aLVO with M2-MCA:74% (70-78%), 93% (92-94%); aLVO with all MeVO: 65% (61-69%), and 93% (92-94%). The automated algorithm demonstrated high accuracy in identifying anterior LVO with lower performance for pLVO and MeVO. It is crucial for acute stroke teams to be aware of the discordance between automated algorithm results and true rates of LVO and MeVO for timely diagnosis and triage. LVO = large vessel occlusion; aLVO = anterior large vessel occlusion; pLVO = posterior large vessel occlusion; MeVO = medium vessel occlusion; EVT= endovascular thrombectomy; AI = artificial intelligence; ACA = anterior cerebral artery; PCA = posterior cerebral artery; BA = basilar artery; VA = vertebral artery.

Prehospital stroke detection scales: A head-to-head comparison of 7 scales in patients with suspected stroke.

Several prehospital scales have been designed to aid paramedics in identifying stroke patients in the ambulance setting. However, external validation and comparison of these scales are largely lacking. To compare all published prehospital stroke detection scales in a large cohort of unselected stroke code patients. We conducted a systematic literature search to identify all stroke detection scales. Scales were reconstructed with prehospital acquired data from two observational cohort studies: the Leiden Prehospital Stroke Study (LPSS) and PREhospital triage of patients with suspected STrOke (PRESTO) study. These included stroke code patients from four ambulance regions in the Netherlands, including 15 hospitals and serving four million people. For each scale, we calculated the accuracy, sensitivity and specificity for a diagnosis of stroke (ischemic, hemorrhagic or TIA). Moreover, we assessed the proportion of stroke patients who received reperfusion treatment with intravenous thrombolysis or endovascular thrombectomy that would have been missed by each scale. We identified 14 scales, of which seven (CPSS, FAST, LAPSS, MASS, MedPACS, OPSS, and sNIHSS-EMS) could be reconstructed. Of 3317 included stroke code patients, 2240 (67.5%) had a stroke (1528 ischemic, 242 hemorrhagic, 470 TIA) and 1077 (32.5%) a stroke mimic. Of ischemic stroke patients, 715 (46.8%) received reperfusion treatment. Accuracies ranged from 0.60 (LAPSS) to 0.66 (MedPACS, OPSS and sNIHSS-EMS), sensitivities from 66% (LAPSS) to 84% (MedPACS and sNIHSS-EMS), and specificities from 28% (sNIHSS-EMS) to 49% (LAPSS). MedPACS, OPSS and sNIHSS-EMS missed the fewest reperfusion-treated patients (10.3-11.2%), whereas LAPSS missed the most (25.5%). Prehospital stroke detection scales generally exhibited high sensitivity but low specificity. While LAPSS performed poorest, MedPACS, sNIHSS-EMS and OPSS demonstrated the highest accuracy and missed the fewest reperfusion-treated stroke patients. Use of the most accurate scale could reduce unnecessary stroke code activations for patients with a stroke mimic by almost a third, but at the cost of missing 16% of strokes and 10% of patients who received reperfusion treatment.

Factors impacting D-dimer levels in patients with acute ischemic cerebrovascular events

Background and objectivesA better understanding of the factors influencing D-dimer levels in code stroke patients is needed to guide further investigations of concomitant thrombotic conditions. This study aimed to investigate the impact of time from symptom onset and other factors on D-dimer levels in patients with acute ischemic stroke (AIS) or transient ischemic attack (TIA). MethodsData on consecutive AIS and TIA patients treated at our tertiary-care stroke center between January 2015 and December 2020 were retrospectively assessed. Patients with available D-dimer levels were evaluated for eligibility. Multivariable non-linear regression analyses were performed. ResultsIn total, 2467 AIS patients and 708 TIA patients were included. The median D-dimer levels differed between the AIS and TIA groups (746 µg/L [interquartile range 381–1468] versus 442 µg/L [interquartile range 244–800], p<0.001). In AIS patients, an early increase in D-dimer levels was demonstrated within the first 6 h (standardized beta coefficient [β] 0.728; 95% confidence interval [CI] 0.324–1.121). This was followed by an immediate decrease (β −13.022; 95% CI −20.401 to −5.643) and then by a second, late increase after 35 h (β 11.750; 95% CI 4.71–18.791). No time-dependent fluctuation in D-dimer levels was observed in TIA patients. ConclusionThe time from symptom onset may affect D-dimer levels in patients with AIS but not those with TIA. Further studies confirming these findings and validating time-specific variations are needed to enable D-dimer levels to be used efficiently as an acute stroke and thrombotic risk biomarker.

Abstract TP52: Reducing Door-to-Imaging Times in Acute Stroke Patients Presenting to the Emergency Department by Private Vehicle: Triage Hallway versus Room Evaluation

Background: Delays in IV thrombolytic and thrombectomy treatments are associated with worse outcomes after ischemic stroke. The objective of our study was to compare door-to-CT imaging times among Code Stroke patients who presented by private vehicle and were evaluated by a physician in the emergency department (ED) either in the triage hallway or the emergency department room. Methods: We prospectively collected real-time data on Code Stroke patients presenting by private vehicle to a primary stroke center from May 1, 2022 through September 18, 2022. A Code Stroke was activated for all patients presenting to the emergency room with positive BE-FAST symptoms occurring within 24 hours from last known normal time. Patients were evaluated by a physician either in the triage hallway or an ED room prior to CT imaging. We compared baseline demographic data, NIHSS scores and door-to-CT times in patients evaluated by the physician in the ED triage hallway versus the ED room. Results: Of 55 patients who presented to the ED by private vehicle during the study period, the mean age was 54 ± 15 years, 53% were female and 45% non-white. The median NIHSS score was 1 [IQR 0-4]. There were 27 (49%) patients who underwent physician evaluation in the triage hallway and the remaining went into a patient room before going to CT. The median NIHSS scores for evaluations in the room were higher than in the triage hallway (2 vs 0, p=0.037). Overall, median time from door-to-CT was 11 minutes for patients who went directly from the triage hallway to CT and 21 minutes for patients who were roomed prior to CT (p=0.005). Conclusions: This study found that Code Stroke patients presenting by private vehicle and evaluated by an emergency physician in the triage hallway saved 10 minutes in door-to-CT time compared with physician evaluation in a room.

Abstract NS3: Nurse Led Interventions Improve the Timeliness of Blood Pressure Reduction in Patients Presenting With Acute Nontraumatic Intracerebral Hemorrhage

Introduction: The 2022 AHA/ASA Guidelines for Intracerebral Hemorrhage (ICH) recommend initiating treatment and lowering blood pressure (BP) within 2 hours of ICH onset and reaching the target systolic BP of 130-150mmHg within one hour of treatment initiation. This study evaluates the effectiveness of nursing education at a Comprehensive Stroke Center (CSC) on improving the timeliness of BP medication administration and BP reduction in ICH patients. Methods: Emergency Department (ED) code stroke patients with a diagnosis of ICH were included in the analysis from 6/2022-12/2022 (pre-intervention) and 1/2023-6/2023 (post-intervention). Guideline based education regarding the importance of timely medication administration was provided in nursing huddles. Nurse to patient ratios were changed to 1:1 until goal BP achieved. BP medications were also placed in the CT scanner pyxis for immediate access. Baseline demographics, NIHSS, ICH score, and door to blood pressure reduction related time metrics were collected. Data were analyzed using R package. Results: 34 patients were analyzed, 12 (35%) pre and 22 (65%) post-intervention. Patient demographics and characteristics were not different between both groups (Table 1). Time from first BP medication order to BP in range improved: 62(46.7-80) vs 43(33-52.3) mins p=0.02. In addition, the time from door to Systolic BP 130-150mmHg improved 81 (68.5-91.3) vs 56 (37.38-73.5) mins p=0.02 (Table 2). Conclusion: Guideline based education is effective in promoting nursing-led interventions to achieve timely BP reduction of ICH patients to the target goal of 130-150 mmHg.

Elimination of Emergency Department Ambulance Divert during the COVID-19 Pandemic Was Not Associated with an Increase in the Average Number of Ambulance Arrivals per Day

Introduction During the COVID-19 pandemic, ambulance divert in our EMS system reached critical levels. We hypothesized that eliminating ambulance divert would not be associated with an increase in the average number of daily ambulance arrivals. Our study objective was to quantify the EMS and emergency department (ED) effects of eliminating ambulance divert during the COVID-19 pandemic. Methods Regional hospital divert data were obtained for the 10-county Twin Cities metro from MNTrac, a state-supported online system designed to allow hospitals to indicate their divert status to EMS. ED metrics are reported for a single Level I trauma center and were obtained by a deidentified data pull from our electronic medical record covering the 12 months prior to the elimination of divert (2021) and the 12 months after divert elimination (2022). The decision to eliminate divert occurred in November 2021, based on data available through October, with an implementation date of January 2022. The primary study outcome was to quantify the effect of the elimination of divert on the number of ambulances arriving per day at the study hospital. Results Regional utilization of ambulance divert increased steadily by 859% from January to October 2021 when 355 individual divert events occurred, totaling 809 h (34 days). There was no significant difference in the number of ambulances that arrived to the study hospital in 2021 (30,774) vs 2022 (30,421) p = 0.15. As compared to 2021, in 2022 there was no significant increase in mean ambulance arrivals per day (84/day vs 83/day, p = 0.08), time to room Emergency Severity Index level 2 (ESI) patients (28 min vs 28 min, p = 0.90), or time to obtain emergent head CT in acute “code stroke” patients (12 min vs 12 min, p = 0.15). Ambulance turnaround interval in the ED did not appreciably increase (16 min vs 17 min, p = 0.15). Conclusion Elimination of ambulance divert was not associated with increases in the number of mean daily ambulance arrivals or EMS turnaround intervals, delays in ESI 2 patients being placed in beds, or prolonged time to head CT in stroke code patients.

Comparison of Prehospital Assessment by Paramedics and In-Hospital Assessment by Physicians in Suspected Stroke Patients: Results From 2 Prospective Cohort Studies.

It is unknown if ambulance paramedics adequately assess neurological deficits used for prehospital stroke scales to detect anterior large-vessel occlusions. We aimed to compare prehospital assessment of these stroke-related deficits by paramedics with in-hospital assessment by physicians. We used data from 2 prospective cohort studies: the LPSS (Leiden Prehospital Stroke Study) and PRESTO study (Prehospital Triage of Patients With Suspected Stroke). In both studies, paramedics scored 9 neurological deficits in stroke code patients in the field. Trained physicians scored the National Institutes of Health Stroke Scale (NIHSS) at hospital presentation. Patients with transient ischemic attack were excluded because of the transient nature of symptoms. Spearman rank correlation coefficient (rs) was used to assess correlation between the total prehospital assessment score, defined as the sum of all prehospital items, and the total NIHSS score. Correlation, sensitivity and specificity were calculated for each prehospital item with the corresponding NIHSS item as reference. We included 2850 stroke code patients. Of these, 1528 had ischemic stroke, 243 intracranial hemorrhage, and 1079 stroke mimics. Correlation between the total prehospital assessment score and NIHSS score was strong (rs=0.70 [95% CI, 0.68-0.72]). Concerning individual items, prehospital assessment of arm (rs=0.68) and leg (rs=0.64) motor function correlated strongest with corresponding NIHSS items, and had highest sensitivity (arm 95%, leg 93%) and moderate specificity (arm 71%, leg 70%). Neglect (rs=0.31), abnormal speech (rs=0.50), and gaze deviation (rs=0.51) had weakest correlations. Neglect and gaze deviation had lowest sensitivity (52% and 66%) but high specificity (84% and 89%), while abnormal speech had high sensitivity (85%) but lowest specificity (65%). The overall prehospital assessment of stroke code patients correlates strongly with in-hospital assessment. Prehospital assessment of neglect, abnormal speech, and gaze deviation differed most from in-hospital assessment. Focused training on these deficits may improve prehospital triage.

Association of admission plasma glucose level and cerebral computed tomographic perfusion deficit volumes

IntroductionHyperglycemia in acute ischemic stroke (AIS) is frequent and associated with worse outcome. Yet, strict glycemic control in AIS patients has failed to yield beneficial outcome. So far, the underlying pathophysiological mechanisms of admission hyperglycemia in AIS have remained not fully understood. We aimed to evaluate the yet equivocal association of hyperglycemia with computed tomographic perfusion (CTP) deficit volumes. Patients and methodsWe included 832 consecutive AIS and transient ischemic attack (TIA) patients who underwent CTP as a part of screening for recanalization treatment (stroke code) between 3/2018 and 10/2020, from the prospective cohort of Helsinki Stroke Quality Registry. Associations of admission glucose level (AGL) and CTP deficit volumes, namely ischemic core, defined as relative cerebral blood flow <30%, and hypoperfusion lesions Time-to-maximum (Tmax) >6 s and Tmax >10s, as determined with RAPID® software, were analyzed with a linear regression model adjusted for age, sex, C-reactive protein, and time from symptom onset to imaging. ResultsAGL median was 6.8 mmol/L (interquartile range 5.9–8.0 mmol/L), and 222 (27%) patients were hyperglycemic (glucose >7.8 mmol/L) on admission. In non-diabetic patients (643 [77%]), AGL was significantly associated with volume of Tmax.>6 s (regression coefficient [RC] 4.8, 95% confidence interval [CI] 0.49–9.1), of Tmax >10s (RC 4.6, 95% CI 1.2–8.1), and of ischemic core (RC 2.6, 95% CI 0.64–4.6). No significant associations were shown in diabetic patients. ConclusionAdmission hyperglycemia appears to be associated with both larger volume of hypoperfusion lesions and of ischemic core in non-diabetic stroke code patients with AIS and TIA.

Prehospital Stroke Triage: A Modeling Study on the Impact of Triage Tools in Different Regions

Background and purpose Direct transportation to a thrombectomy-capable intervention center is beneficial for patients with ischemic stroke due to large vessel occlusion (LVO), but can delay intravenous thrombolytics (IVT). The aim of this modeling study was to estimate the effect of prehospital triage strategies on treatment delays and overtriage in different regions. Methods We used data from two prospective cohort studies in the Netherlands: the Leiden Prehospital Stroke Study and the PRESTO study. We included stroke code patients within 6 h from symptom onset. We modeled outcomes of Rapid Arterial oCclusion Evaluation (RACE) scale triage and triage with a personalized decision tool, using drip-and-ship as reference. Main outcomes were overtriage (stroke code patients incorrectly triaged to an intervention center), reduced delay to endovascular thrombectomy (EVT), and delay to IVT. Results We included 1798 stroke code patients from four ambulance regions. Per region, overtriage ranged from 1-13% (RACE triage) and 3-15% (personalized tool). Reduction of delay to EVT varied by region between 24 ± 5 min (n = 6) to 78 ± 3 (n = 2), while IVT delay increased with 5 (n = 5) to 15 min (n = 21) for non-LVO patients. The personalized tool reduced delay to EVT for more patients (25 ± 4 min [n = 8] to 49 ± 13 [n = 5]), while delaying IVT with 3-14 min (8-24 patients). In region C, most EVT patients were treated faster (reduction of delay to EVT 31 ± 6 min (n = 35), with RACE triage and the personalized tool. Conclusions In this modeling study, we showed that prehospital triage reduced time to EVT without disproportionate IVT delay, compared to a drip-and-ship strategy. The effect of triage strategies and the associated overtriage varied between regions. Implementation of prehospital triage should therefore be considered on a regional level.

Establishing a pediatric acute stroke protocol: experience of a new pediatric stroke program and predictors of acute stroke.

Pediatric stroke is among the top 10 causes of death in pediatrics. Rapid recognition and treatment can improve outcomes in select patients, as evidenced by recent retrospective studies in pediatric thrombectomy. We established a collaborative protocol involving the vascular neurology and pediatric neurology division in our institution to rapidly diagnose and treat pediatric suspected stroke. We also prospectively collected data to attempt to identify predictors of acute stroke in pediatric patients. IRB approval was obtained to prospectively collect clinical data on pediatric code stroke activations based on timing metrics in resident-physician note templates. The protocol emphasized magnetic resonance imaging over computed tomography imaging when possible. We analyzed performance of the system with descriptive statistics. We then performed a Bayesian statistical analysis to search for predictors of pediatric stroke. There were 40 pediatric code strokes over the 2.5-year study period with a median age of 10.8 years old. 12 (30%) of patients had stroke, and 28 (70%) of code stroke patients were diagnosed with a stroke mimic. Median time from code stroke activation to completion of imaging confirming or ruling out stroke was 1 h. In the Bayesian analysis, altered mental status, hemiparesis, and vasculopathy history were associated with increased odds of stroke, though credible intervals were wide due to the small sample size. A trainee developed and initiated pediatric acute stroke protocol quickly implemented a hospital wide change in management that led to rapid diagnosis and triage of pediatric stroke and suspected stroke. No additional personnel or resources were needed for this change, and we encourage other hospitals and emergency departments to implement similar systems. Additionally, hemiparesis and altered mental status were predictors of stroke for pediatric acute stroke activation in our Bayesian statistical analysis. However credible intervals were wide due to the small sample size. Further multicenter data collection could more definitively analyze predictors of stroke, as well as the help in the creation of diagnostic tools for clinicians in the emergency setting.

Abstract TP77: Point Of Care Inr And R-tpa Decision Making In Acute Ischemic Stroke

Introduction: IV r-tPA is the standard of care treatment in acute ischemic stroke presenting within 4.5 hours of last known well. Exclusion criteria for administering IV r-tPA include conditions that predispose to bleeding, including an INR of ≥ 1.7 . Point of care (POC) INR testing is significantly faster than laboratory derived INR results and can expedite IV r-tPA administration. However, POC INR testing is less accurate than laboratory-based testing with an acceptable variance range of +/- 0.4, which may lead to improper r-tPA exclusion or inclusion. Objectives: We demonstrate the utility of a protocolized approach to POC INR testing in acute ischemic stroke, in which known or suspected warfarin use requires a lab INR result to determine if r-tPA is contraindicated when POC INR is between 1.3-2.1. This approach prevents IV r-tPA from being inappropriately administered or withheld. Methods: We stratified a subset of real world paired POC and laboratory INR results (n=892) for stroke code patients at our institution from January 1st through July 4 th , 2022 by known or suspected warfarin status and calculated a positive predictive value for POC INR &gt; 1.7. Results: Fifty-four of 892 paired POC and laboratory INR results represented patients with known or suspected warfarin use. Twenty-five (46%) had a POC INR within 1.3-2.1 warranting a lab INR verification prior to safe administration of r-tPA. Thirteen of which had a POC INR &lt; 1.7 but a lab INR of ≥ 1.7. In 5.25% of cases where the POC INR &gt; 1.7 the laboratory INR was &lt; 1.7. The positive predictive value for POC INR &gt;= 1.7 among patients with known or suspected warfarin status is 88.2%. Conclusions: POC INR testing rapidly screens for coagulopathy in IV tPA eligible stroke patients, but due to inherent inaccuracy may inadvertently rule patients in or out for IV r-tPA treatment. Our institution has instituted a policy of requiring laboratory verified INR results when the POC INR is within +/- 0.4 of the laboratory based INR tPA cutoff. In our 892 patient sample, this policy would prevent 13 patients from inadvertently receiving IV tPA due to an inaccurate POC INR. Up to five percent of patients excluded from r-tPA based on POC INR may in-fact be treatment candidates.

411EMF Measurement of Cost of Boarding Code Stroke Patients in the Emergency Department Using Time-Driven Activity-Based Costing

Emergency department (ED) boarding is associated with patient care and safety risks. However, reports show it is worsening over time. There is an abundance of research on the effects of boarding on patients, staff, and emergency department operations. However, there is a clear paucity of research into the financial effects of boarding. We sought to measure the cost of boarding code stroke patients using time-driven activity-based costing and compare how this cost related to the overall cost of inpatient care.

Determinants and Trends of the Use of Intravenous Thrombolysis for Minor Stroke: A Population-Based Study, 2016 to 2020.

We analyzed the main factors associated with intravenous thrombolysis (IVT) in patients with minor ischemic stroke. Data were obtained from a prospective, government-mandated, population-based registry of stroke code patients in Catalonia (6 Comprehensive Stroke Centers, 8 Primary Stroke Centers, and 14 TeleStroke Centers). We selected patients diagnosed with ischemic stroke and National Institutes of Health Stroke Scale (NIHSS) ≤5 at hospital admission from January 2016 to December 2020. We excluded patients with a baseline modified Rankin Scale score of ≥3, absolute contraindication for IVT, unknown stroke onset, or admitted to hospital beyond 4.5 after stroke onset. The main outcome was treatment with IVT. We performed univariable and binary logistic regression analyses to identify the most important factors associated with IVT. We included 2975 code strokes; 1433 (48.2%) received IVT of which 30 (2.1%) had a symptomatic hemorrhagic transformation. Patients treated with IVT as compared to patients who did not receive IVT were more frequently women, had higher NIHSS, arrived earlier to hospital, were admitted to a Comprehensive Stroke Centers, and had large vessel occlusion. After binary logistic regression, NIHSS score 4 to 5 (odds ratio, 40.62 [95% CI, 31.73-57.22]; P<0.001) and large vessel occlusion (odds ratio, 16.39 [95% CI, 7.25-37.04]; P<0.001) were the strongest predictors of IVT. Younger age, female sex, baseline modified Rankin Scale score of 0, earlier arrival to hospital (<120 minutes after stroke onset), and the type of stroke center were also independently associated with IVT. The weight of large vessel occlusion on IVT was higher in patients with lower NIHSS. Minor stroke female patients, with higher NIHSS, arriving earlier to the hospital, presenting with large vessel occlusion and admitted to a Comprehensive Stroke Centers were more likely to receive intravenous thrombolysis.

Evaluating Stroke Code Activation Pathway in Emergency Departments study

To describe the clinical characteristics and outcomes of Code Stroke activations in an ED and determine predictors of a final diagnosis of stroke or transient ischemic attack (TIA) diagnosis. This was a retrospective analysis of Code Stroke activations through an ED over 2 years at a quaternary stroke referral centre. Stroke Registry data was used to identify cases with clinical information abstracted from electronic medical records. The primary outcome was a final diagnosis of acute stroke or TIA and the secondary outcome was access to reperfusion therapies (thrombolysis and or endovascular clot retrieval). The study analysed data from 1354 Code Stroke patients in ED. Of all Code Strokes, 51% had a stroke or TIA diagnosis on discharge. Patient characteristics independently associated with increased risk of stroke were increasing age, pre-arrival notification by ambulance, elevated BP or presence of weakness or speech impairment as the initial presenting symptoms. Dizziness/vertigo/vestibular neuritis were the most common alternative diagnoses. One hundred and thirty-five patients (10%) underwent reperfusion therapy. Pre-arrival notification by ambulance was associated with higher proportion of eventual stroke/TIA diagnosis (68% vs 46%, P< 0.001) and significantly lower door to CT and door to needle times for patients undergoing thrombolysis. In a cohort of patients requiring Code Stroke activation in an ED, increased age, systolic blood pressure and weakness and speech impairment increased the risk of stroke. Prehospital notification was associated with lower door to needle times for patients undergoing thrombolysis.

Disparities Influencing Functional Outcomes Between Rural and Urban Patients With Acute Stroke.

IntroductionThere is scarce information in Latin America about factors related to stroke patient outcomes in rural areas compared to urban ones.ObjectiveTo evaluate functional outcomes of stroke code patients from rural and urban areas and their relationship with socioeconomic disparity.MethodsProspective cohort study included patients of urban, semi-urban, and rural origin with stroke code from a high complexity hospital in southwestern Colombia between 2018 and 2019. Demographic, clinical data modified Rankin at discharge, and 3-month follow-up were analyzed. The poverty index, barriers to health access and availability of ambulances by the municipality was assessed at an ecological level.ResultsFive hundred and fifty five stroke patients were registered, 21.2% from rural areas, 432 (77.98%) had an ischemic stroke. There were no significant differences in sociodemographic factors and medical background. Urban patients had lower reperfusion therapies rates (23.25%). Favorable mRS at discharge (<3) was higher in urban areas (63.03%) and mortality was superior in rural patients (13.56%). The ambulance rate in semi-urban and rural areas was as low as 0.03 per 100.000 inhabitants, the poverty index was 11.9% in urban areas vs. 23.3% in semi urban and rural areas.ConclusionsRural patients treated in our center were more likely to present with severe strokes and unfavorable mRS at hospital discharge and 3-month follow-up compared to urban, despite having similar risk factors. There is an inverse relationship, which is not related to the poverty rate or the percentage of people with barriers to access to health. There is a need for further studies that assess barriers inherent in rural patients and establish a regional stroke network.

Abstract WMP26: Performance Improvement During A Pandemic: Implementing Weekly Case Review To Decrease Door-to-CT And Door-to-Needle Times For Code Stroke Patients

Background and Purpose: When reviewing Code Stroke workflow data early in the COVID pandemic, a delay in obtaining CT brain imaging for stroke patients was identified. This study was aimed at improving Door-to-CT and Door-to-IVtPA bolus times by developing an Emergency Department (ED) led process improvement (PI) team to identify and track root causes for delays, provide feedback after fallouts, and recognize care teams after successful cases. Our primary goal was to demonstrate improved trends for performance metrics utilizing a novel method of process improvement, data collection, analysis, and dissemination. Methods: All ED patients activated as a Code Stroke were included in a weekly workflow review conducted by the PI team. Patients with a Door-to-CT of &gt; 20 minutes were analyzed by the team via an in-depth chart review to identify the root cause of the delay. Specific metrics analyzed included Door-to-CT times and Door-to-IVtPA bolus times, along with the percentage of cases that met process metric time goals. Implementation of the weekly review began September 31, 2020, with the pre-implementation period corresponding to the prior nine months and the post-implementation period being the ensuing nine months. Metrics were analyzed using a control chart based on monthly metric averages, standard deviations (SD), and both an upper and lower control limit defined as 1 sigma level of variability from the average. Results: The average Door-to-CT time pre-implementation was 30.6 minutes versus 22.8 minutes post-implementation, with a percentage goal within 20 minutes pre- and post-implementation of 47% and 66%.The average Door-to-IVtPA Bolus time pre-implementation was 40.1 minutes versus 31.5 minutes post-implementation, with a percentage goal &lt;30 minutes pre and post-implementation of 42% and 56%.The SD for Door-to-CT average improved from 4.81 to 3.76, while the Door-to-IVtPA Bolus average SD decreased from 9.26 to 8.53. Conclusion: Reviewing identification, activation, and treatment times for all ED Code Stroke patients during the COVID pandemic was associated with significantly reduced imaging and treatment times.

Abstract WP108: Is Infarct Core Growth Truly Linear? Follow-up Infarct Volume Estimation By Rapid Baseline Infarct Growth Rate And Linear Model

Background: Current guidelines for recanalization treatment are based on the time window between symptom onset and treatment in addition to ischemic core and perfusion lesion volumes by computed tomography perfusion imaging (CTP). Linear growth of infarction is commonly assumed.The aim was to test, whether measured follow-up infract volume (FIV) could be approximated from the linear growth model (eFIV) based on CTP baseline infarct growth rate.We assumed the infarct growth to stop, when recanalization was achieved or when the eFIV reached the volume of the perfusion lesion (T max &gt;6s volume). Methods: All consecutive stroke code patients from 11/2015-9/2019 transferred to Helsinki University Hospital as candidates for endovascular treatment (EVT) were screened; patients with large vessel occlusion (LVO), EVT, CTP and known time of symptom onset were included to study.The infarct growth rate was calculated by dividing the CTP core by the time from symptom onset to baseline imaging.eFIV was calculated by infarct growth rate multiplied with the time from baseline imaging to recanalization or follow-up imaging. We assumed a performance of +/- 19% for the accuracy of the CTP core assessment. FIV was measured from the 24h non-enhanced computed tomography images. Recanalization was defined as modified Treatment in Cerebral Infarction (mTICI) scale as successful (TICI 2b or 3) or futile (TICI 0,1,2a). Results: Out of 5234 patients, 48 had LVO and EVT, CTP imaging and known time of symptom onset (Figure 1). In 40/48 (83%) patients, infarct growth was not within the 19% margins of linear growth. eFIV exceeded FIV in 25/42 patients with successful recanalization (median absolute difference 25 mL,7-73). Conclusions: eFIV from linearly approximated growth model did not support linear growth of the infarct.

Clinical Differences Between Stroke and Stroke Mimics in Code Stroke Patients.

BackgroundThe code stroke system is designed to identify stroke patients who may benefit from reperfusion therapy. It is essential for emergency physicians to rapidly distinguish true strokes from stroke mimics to activate code stroke. This study aimed to investigate the clinical and neurological characteristics that can be used to differentiate between stroke and stroke mimics in the emergency department (ED).MethodsWe conducted a retrospective observational study of code stroke patients in the ED from January to December 2019. The baseline characteristics and the clinical and neurological features of stroke mimics were compared with those of strokes.ResultsA total of 409 code stroke patients presented to the ED, and 125 (31%) were diagnosed with stroke mimics. The common stroke mimics were seizures (21.7%), drug toxicity (12.0%), metabolic disorders (11.2%), brain tumors (8.8%), and peripheral vertigo (7.2%). The independent predictors of stroke mimics were psychiatric disorders, dizziness, altered mental status, and seizure-like movements, while current smoking, elevated systolic blood pressure, atrial fibrillation on the initial electrocardiogram, hemiparesis as a symptom, and facial palsy as a sign suggested a stroke. In addition, the likelihood of a stroke in code stroke patients tended to increase as the number of accompanying deficits increased from the following set of seven focal neurological deficits: hemiparesis (or upper limb monoparesis), unilateral limb sensory change, facial palsy, dysarthria, aphasia (or neglect), visual field defect, and oculomotor disorder (P < 0.001).ConclusionSome clinical and neurological characteristics have been identified to help differentiate stroke mimics from true stroke. In particular, the likelihood of stroke tended to increase as the number of accompanying focal neurological deficits increased.

The Role of Vascular Imaging atReferral Centers in the Drip and Ship Paradigm

BackgroundIn drip-and-ship protocols, non-invasive vascular imaging (NIVI) at Referral Centers (RC), although recommended, is not consistently performed and its value is uncertain. We evaluated the role of NIVI at RC, comparing patients with (VI+) and without (VI-) vascular imaging in several outcomes. MethodsObservational, multicenter study from a prospective government-mandated population-based registry of code stroke patients. We selected acute ischemic stroke patients, initially assessed at RC from January-2016 to June-2020. We compared and analyzed the rates of patients transferred to a Comprehensive Stroke Center (CSC) for Endovascular Treatment (EVT), rates of EVT and workflow times between VI+ and VI- patients. ResultsFrom 5128 ischemic code stroke patients admitted at RC; 3067 (59.8%) were VI+, 1822 (35.5%) were secondarily transferred to a CSC and 600 (11.7%) received EVT. Among all patients with severe stroke (NIHSS ≥16) at RC, a multivariate analysis showed that lower age, thrombolytic treatment, and VI+ (OR:1.479, CI95%: 1.117-1.960, p=0.006) were independent factors associated to EVT.The rate of secondary transfer to a CSC was lower in VI+ group (24.6% vs. 51.6%, p<0.001). Among transferred patients, EVT was more frequent in VI+ than VI- (48.6% vs. 21.7%, p<0.001).Interval times as door-in door-out (median-minutes 83.5 vs. 82, p= 0.13) and RC-Door to puncture (median-minutes 189 vs. 178, p= 0.47) did not show differences between both groups. ConclusionIn the present study, NIVI at RC improves selection for EVT, and is associated with receiving EVT in severe stroke patients. Time-metrics related to drip-and-ship model were not affected by NIVI.