Prehospital Stroke Recognition Research Articles

Artificial intelligence to enhance prehospital stroke diagnosis and triage: a perspective.

As health systems organize to deliver the highest quality stroke care to their patients, there is increasing emphasis being placed on prehospital stroke recognition, accurate diagnosis, and efficient triage to improve outcomes after stroke. Emergency medical services (EMS) personnel currently rely heavily on dispatch accuracy, stroke screening tools, bypass protocols and prehospital notification to care for patients with suspected stroke, but novel tools including mobile stroke units and telemedicine-enabled ambulances are already changing the landscape of prehospital stroke care. Herein, the authors provide our perspective on the current state of prehospital stroke diagnosis and triage including several of these emerging trends. Then, we provide commentary to highlight potential artificial intelligence (AI) applications to improve stroke detection, improve accurate and timely dispatch, enhance EMS training and performance, and develop novel stroke diagnostic tools for prehospital use.

Experiences from a cluster-randomized trial (ParaNASPP) exploring triage and diagnostic accuracy in paramedic-suspected stroke: a qualitative interview study.

Timely prehospital stroke recognition was explored in the Paramedic Norwegian Acute Stroke Prehospital Project (ParaNASPP) by implementation of stroke education for paramedics and use of the National Institutes of Health Stroke Scale (NIHSS) through a mobile application. The study tested triage and facilitated communication between paramedics and stroke physicians. To complement the quantitative results of the clinical trial, a qualitative approach was used to identify factors that influence triage decisions and diagnostic accuracy in prehospital stroke recognition experienced by paramedics and stroke physicians. Semi-structured qualitative individual interviews were performed following an interview guide. Informants were recruited from the enrolled paramedics and stroke physicians who participated in the ParaNASPP trial from Oslo University Hospital. Interviews were audio recorded, transcribed verbatim and approached inductively using the principles of thematic analysis. Fourteen interviews were conducted, with seven paramedics and seven stroke physicians. Across both groups two overarching themes were identified related to triage decisions and diagnostic accuracy in prehospital stroke recognition: prehospital NIHSS reliably improves clinical assessment and communication quality; overtriage is widely accepted whilst undertriage is not. Paramedics and stroke physicians described how prehospital NIHSS improved communication quality and reliably improved prehospital clinical assessment. The qualitative results support a rationale of an application algorithm to decide which NIHSS items should prompt immediate prenotification rather than a complete NIHSS as default.

A retrospective study on machine learning-assisted stroke recognition for medical helpline calls

Advanced stroke treatment is time-dependent and, therefore, relies on recognition by call-takers at prehospital telehealth services to ensure fast hospitalisation. This study aims to develop and assess the potential of machine learning in improving prehospital stroke recognition during medical helpline calls. We used calls from 1 January 2015 to 31 December 2020 in Copenhagen to develop a machine learning-based classification pipeline. Calls from 2021 are used for testing. Calls are first transcribed using an automatic speech recognition model and then categorised as stroke or non-stroke using a text classification model. Call-takers achieve a sensitivity of 52.7% (95% confidence interval 49.2–56.4%) with a positive predictive value (PPV) of 17.1% (15.5–18.6%). The machine learning framework performs significantly better (p < 0.0001) with a sensitivity of 63.0% (62.0–64.1%) and a PPV of 24.9% (24.3–25.5%). Thus, a machine learning framework for recognising stroke in prehospital medical helpline calls may become a supportive tool for call-takers, aiding in early and accurate stroke recognition.

Interactive Training of the Emergency Medical Services Improved Prehospital Stroke Recognition and Transport Time.

Background and PurposeAcute stroke treatment outcomes are predicated on reperfusion timeliness which can be improved by better prehospital stroke identification. We aimed to assess the effect of interactive emergency medical services (EMS) training on stroke recognition and prehospital care performance in a very high-risk cardiovascular risk population in Lithuania.MethodsWe conducted a single-center interrupted time-series study between March 1, 2019 and March 15, 2020. Two-hour small-group interactive stroke training sessions were organized for 166 paramedics serving our stroke network. We evaluated positive predictive value (PPV) and sensitivity for stroke including transient ischemic attack identification, onset-to-door time, and hospital-based outcomes during 6-months prior and 3.5 months after the training. The study outcomes were compared between EMS providers in urban and suburban areas.ResultsIn total, 677 suspected stroke cases and 239 stroke chameleons (median age 75 years, 54.8% women) were transported by EMS. After the training, we observed improved PPV for stroke recognition (79.8% vs. 71.8%, p = 0.017) and a trend of decreased in-hospital mortality (7.8% vs. 12.3, p = 0.070). Multivariable logistic regression models adjusted for age, gender, EMS location, and stroke subtype showed an association between EMS stroke training and improved odds of stroke identification (adjusted odds ratio [aOR] 1.6 [1.1–2.3]) and onset-to-door ≤ 90 min (aOR 1.6 [1.1–2.5]). The improvement of PPV was observed in urban EMS (84.9% vs. 71.2%, p = 0.003), but not in the suburban group (75.0% vs. 72.6%, p = 0.621).ConclusionsThe interactive EMS training was associated with a robust improvement of stroke recognition, onset to hospital transport time, and a trend of decreased in-hospital mortality. Adapted training strategies may be needed for EMS providers in suburban areas. Future studies should evaluate the long-term effects of the EMS training and identify optimal retraining intervals.

Significant Stroke Knowledge Deficiencies in Community Physician Improved with Stroke 120

Background and Purpose: In the existing model of community health service in China, community general practitioners play important roles in health promotion as well as prehospital stroke recognition and management. We recently engineered Stroke 120 based on FAST for China. This investigation aimed to investigate its acceptance in community physicians and promote their stroke related knowledge. Methods: We conducted an stroke education session to community physicians or family doctors (total of 435 participants), teaching both FAST and Stroke 120. Online survey was distributed to the participants before and after the education session to evaluate the awareness of stroke and the acceptance of the stroke recognition tool. Results: Significant stroke knowledge deficiencies were found in community physicians. After the education session, percent of the participants knew that the thrombolytic therapeutic window (<4.5 hours) was improved from 54.0% to 91.6% (P < .001). A total of 88.5% of them would send their patients who had stroke to the nearest hospital with stroke center by emergency medical service, compared to baseline (64.4%, P < .001). In total, 95.2% of them would recommend thrombolytic therapy in the treatment of acute ischemic stroke compared to 82.7% (baseline P < .001). Although majority mastered both FAST (95.5%) and Stroke 120 (98.0%) through our education session, 96.3% of them believe that Stroke 120 is the most suitable for Chinese in stroke education. Conclusions: Stroke 120 strategy was well accepted by the community physicians in China and in the meantime improved knowledge regarding stroke was observed.

The role of the Cincinnati Prehospital Stroke Scale in the emergency department: evidence from a systematic review and meta-analysis.

IntroductionStroke is one of the leading causes of morbidity, disability, and mortality in high-income countries. Early prehospital stroke recognition plays a fundamental role, because most clinical decisions should be made within the first hours after onset of symptoms. The Cincinnati Prehospital Stroke Scale (CPSS) is a validated screening tool whose utilization is suggested during triage. The aim of this study is to review the role of the CPSS by assessing its sensitivity and specificity in prehospital and hospital settings.MethodsA systematic review and a meta-analysis of the literature reporting the CPSS sensitivity and specificity among patients suspected of stroke were undertaken. Electronic databases were searched up to December 2018, and the quality assessment was carried out by using the Revised Quality Assessment of Diagnostic Accuracy Studies −2 (QUADAS-2).ResultsEleven studies were included in the meta-analysis. Results showed an overall sensitivity of 82.46% (95% confidence interval [CI] 74.83–88.09%) and specificity of 56.95% (95% CI 41.78–70.92). No significant differences were found in terms of sensitivity when CPSS was performed by physicians (80.11%, 95% CI 66.14–89.25%) or non-physicians (81.11%, 95% CI 69.78–88.87%). However, administration by physicians resulted in higher specificity (73.57%, 95% CI 65.78–80.12%) when compared to administration by non-physicians (50.07%, 95% CI 31.54–68.58%). Prospective studies showed higher specificity 71.61% (95% CI 61.12–80.18%) and sensitivity 86.82% (95% CI 74.72–93.63) when compared to retrospective studies which showed specificity of 33.37% (95% CI 22.79–45.94%) and sensitivity of 78.52% (95% CI 75.08–81.60).ConclusionsThe CPSS is a standardized and easy-to-use stroke screening tool whose implementation in emergency systems protocols, along with proper and consistent coordination with local, regional, and state agencies, medical authorities and local experts are suggested.

Pre-hospital stroke recognition in a UK centralised stroke system: a qualitative evaluation of current practice.

Background:A significant number of patients conveyed via ambulance to hyper acute stroke units (HASU) with suspected stroke have other diagnoses. This may delay treatment for non-stroke patients and cause burden to stroke teams. The Greater Manchester (GM) Connected Health Cities (CHC) stroke project links historical North West Ambulance Service NHS Trust (NWAS) data with Salford Royal Hospital electronic data to study stroke pathway compliance and accuracy of paramedic diagnosis and aims to use these data to improve pre-hospital clinicians’ accurate recognition of stroke through development of service improvement innovations. We report on supplementary qualitative work required to understand stroke recognition from the pre-hospital clinician’s perspective.Methods:Focus groups and semi-structured interviews were conducted with pre-hospital clinicians of various grades, working in the GM area of NWAS. Focus groups and interviews were audio recorded and transcribed verbatim. We used thematic analysis informed by normalisation process theory (NPT) to analyse the data. This theory helps us to understand how innovations are developed, implemented and sustained into healthcare practice.Results:Sixteen pre-hospital clinicians took part in two focus groups, one dyad interview and five one-to-one interviews. Analysis identified that respondents were unaware of false positive stroke rates entering onto the stroke pathway. Pre-hospital clinicians receive limited feedback from jobs and this impedes their ability to learn from their experiences. Respondents reported difficulty in ruling out stroke in certain patient cohorts and difficulty in recognising differential diagnoses. They expressed a lack of confidence to rule out stroke in the pre-hospital setting. They also expressed greater concern for ‘missed strokes’.Conclusion:The qualitative findings support the development of innovations to improve accurate recognition of stroke in the pre-hospital setting.An enhanced FAST tool, better relations with HASU clinicians, feedback and education on the stroke pathway and differential diagnoses were all considered useful to improve accurate stroke recognition.

A Pilot Study Validating Video-Based Training on Pre-Hospital Stroke Recognition

Delays in recognizing stroke during pre-hospital emergency medical system (EMS) care may affect triage and transport time to an appropriate stroke ready hospital and may preclude patients from receiving time dependent treatment. All EMS transports in a large urban area in the stroke belt were evaluated for transport destinations, triage and transport time and stroke recognition following distribution ofan educational training video to local EMS services. Following video training, local paramedics will improve stroke recognition and shorten triage and transport time to appropriate stroke centers of care. A training module (<10 min) containing a stroke triage scenario, instruction on the Cincinnati Prehospital Stroke Score (CPSS) and the Los Angeles Prehospital Stroke Score (LAPSS) and 'where to transport' stroke patients was distributed and viewed by 96 paramedics. Data was collected from February to October 2016. Stroke recognition was determined from one primary stroke center (PSC) hospital's confirmation of EMS delivered patients (Site A). Yearly stroke recognition percentages of 44% from Site A in 2014 were used as baseline. A total of 34,833 emergency 911 response transports were made with a total of 502 (1.4%) suspected strokes identified by paramedics. Median [IQR] triage and transport time for stroke transports was 33 [27-41] min. The PSC hospitals received a 5% increase in stroke transports and non-specific care facilities decreased by 7%. From 8,554 transports to site A (PSC) confirmed strokes totalled 107 transports with 139 suspected strokes by paramedics. Of these transports, 60 were correctly identified by paramedics (positive predictive value of 43%, sensitivity of 56%). By the second month following training, recognition percentages increased from baseline to 64%. At five months, percentages of correct stroke identification had dropped to 36%. Video based training improved stroke recognition by an additional 19%, but continual monthly or quarterly training is recommended for maintenance of increased stroke recognition.

Abstract WP233: A Pilot Study Validating Video-based Training on Pre-hospital Stroke Recognition

Introduction: Delays in recognizing stroke during pre-hospital emergency medical system (EMS) care may affect triage+transport time to appropriate stroke ready hospitals and may preclude patients from receiving time dependent treatment. All EMS transports in a large urban area in the stroke belt were evaluated for transport destinations, triage+transport time and stroke recognition following distribution of an educational training video to local EMS services. Hypothesis: Following video training local paramedics will improve stroke recognition, shorten triage+transport time, and increase stroke transports to primary stroke centers (PSC) of care. Methods: A training module (&lt;10 min) containing a stroke scene scenario, instruction on the Cincinnati Prehospital Stroke Score (CPSS) and the Los Angeles Prehospital Stroke Score (LAPSS) and ‘where to transport’ stroke patients was distributed and viewed by 94 paramedics. Data was collected from February to October 2016. Stroke recognition was determined from one PSC hospital’s confirmation of EMS delivered patients (site A). Stroke recognition percentages from site A collected in 2014 were used as baseline. Results: A total of 35,207 emergency 911 response transports were made with a total of 506 (1.4%) paramedic identified strokes. Average triage+transport time for stroke transports was 33 +/- 0.7 minutes. The PSC hospitals received a 5% increase in stroke transports and the non-specific care facilities decreased by 7%. The PSC stroke confirmation totaled 130 transports with 140 suspected strokes by paramedics and 71 of 130 confirmed strokes correctly identified by paramedics (positive predictive value of 50.7%, sensitivity of 54.6%). By the third month following training, recognition percentages increased from 54% at baseline to 73%. At five months, percentages of correct stroke identification had dropped to pre-training levels. Conclusion: The training improved stroke recognition by an additional 19% with follow-up training recommended at five months.

Abstract WP220: Onset to Needle Times Differ in Patients with Varying Stroke Severity: A Retrospective Review of a National Stroke Audit

Introduction: Outcomes following stroke thrombolysis have been observed to be largely dependent on time to treatment. Patients with more severe strokes have more obvious symptoms and are easily diagnosed while patients with milder strokes are often in a grey area where misdiagnosis (particularly as resolving TIA) is common, therefore leading to delayed thrombolysis. Time to treatments are not only influenced by in-hospital factors, but pre-hospital factors as well. Delaying treatment in minor stroke patients might have detrimental effects and diminish chances of good outcome. We wished to examine the effects of stroke severity on onset to needle times (OTN) and door to needle times (DTN) using a national stroke data set. Methods: A retrospective analysis was done on patients who were eligible for and treated with recombinant tissue-type plasminogen activator (rt-PA). Data for all patients in Scotland treated with alteplase between 2010 and 2013 was available from the Scottish Stroke Care Audit (SSCA). Components of the thrombolysis service delivery pathway was compared between minor (NIHSS score of ≤5) and more severe stroke (NIHSS score of ≥6) patients. Results: OTNs and DTNs are both negatively correlated to pre-treatment NIH scores. However, OTN shows greater correlation to pre-treatment NIH scores (r=-0.212 p&lt;001) than did DTN (r=-0.057, p=0.021). Minor stroke patients have longer onset to admission times (105.5 vs. 83 minutes; p&lt;0.001), OTNs (180 vs. 160 minutes; p&lt;0.001), admission to scan times (37 vs. 31 minutes; p=0.004), and were younger (71.22 vs. 74.18 years; p&lt;0.001). Conclusion: This study confirms evidence that minor stroke patients are experiencing delayed thrombolysis, which could reduce the opportunity for benefit for stroke survivors. The reasons for this delay appear to include pre-hospital stroke recognition and response, and also in-hospital patient/clinician decision making as the risks and benefits may be viewed differently in milder strokes. Stroke care guidelines could consider using OTNs as a stroke care standard instead of DTNs in future reviews of management standards.

Accuracy of prehospital stroke recognition by paramedics and TPA therapy rate after transportation

Accuracy of prehospital stroke recognition by paramedics and TPA therapy rate after transportation

Design and validation of a clinical scale for prehospital stroke recognition, severity grading and prediction of large vessel occlusion: the shortened NIH Stroke Scale for emergency medical services

ObjectiveTo develop an NIH Stroke Scale (NIHSS)-compatible, all-in-one scale for rapid and comprehensive prehospital stroke assessment including stroke recognition, severity grading and progression monitoring as well as prediction of large...

Abstract TP241: Concordance of Pre-hospital Stroke Recognition by Medical Dispatchers and Paramedics in an Urban County

Background: Immediately after a stroke, the time it takes to reach a designated stroke center can determine the patient’s chances of recovery or permanent disability. In pre-hospital care, the first level of care occurs when 911 is called, second when the paramedics arrive and triage, and third, transport to the nearest primary stroke center (PSC). When emergency medical dispatchers (EMD) initially recognize stroke they provide critical stroke triage codes guiding the paramedic’s decision in appropriate hospital choice, saving time and improving patient recovery. This study assessed EMD and paramedic stroke recognition and performance in an urban area. Hypothesis: EMD recognition of stroke would provide paramedics adequate codes for correct recognition and influence transports to area primary stroke centers (PSCs). Methods: All emergency medical service (EMS) transports in an urban county area (392,664 population) during 2014 were retrospectively analyzed. The transports encompassed True/Negatives, False/Positives, False/Negatives and True/Positives for data on the number and percentages of EMS correctly identified stroke ground transport 911 calls. Dispatch impressions of calls were compared to paramedic decisions and confirmed by hospital ICD-9-CM billing codes 430-438. Transports to area PSC and non-PSC hospitals were determined. Results: Over 12 months, in N=40,171 total transports, EMDs impression of strokes were n=942 with 51.3% confirmed as strokes by paramedics. The other 47.6% of calls reported as strokes by EMDs were coded by paramedics as syncope/fainting, altered level of consciousness, abdominal pain, diabetic, behavioral, cardiac rhythm disturbance and seizures. Paramedic reported strokes were coded by dispatchers as 52.0% strokes/CVA or as headaches, sick person, unconscious/fainting, fall victim, chest pain, convulsions/seizures and breathing problems. Significantly more stroke-related deliveries were made to PSCs (55%, p&lt;0.001) than other area facilities. Hospital confirmation by discharge data services of paramedic coded strokes provided a true positive predictive value of 44.8% and sensitivity of 25%. Conclusion: EMS dispatch and paramedic services could benefit from stroke recognition education.

Spotlight on the June 7 Issue

#### Notable in Neurology This issue features an article that assesses the utility of the Cincinnati Prehospital Stroke Scale and Recognition of Stroke in the Emergency Room tools in evaluating children presenting to the emergency department with brain attack symptoms. A featured article focuses on the effects of white noise galvanic vestibular stimulation on dynamic walking stability in patients with bilateral vestibulopathy. ### Phenotypic characteristics of Alzheimer patients carrying an ABCA7 mutation![Graphic][1]</img> The authors evaluated medical records, including laboratory and CSF analyses; neuroimaging studies; and neuropathology data. They found that patients carrying ABCA7 loss-of-function mutations exhibited an Alzheimer disease … [1]: /embed/inline-graphic-1.gif

Performance of bedside stroke recognition tools in discriminating childhood stroke from mimics.

To assess the utility of the Cincinnati Prehospital Stroke Scale (CPSS) and Recognition of Stroke in the Emergency Room (ROSIER) tools in children presenting to the emergency department (ED) with brain attack symptoms. The ROSIER and CPSS tools were retrospectively applied to 101 children with stroke, presenting from 2003 to 2010, and prospectively to 279 children with mimics, presenting from 2009 to 2010. Positive CPSS was defined as ≥1 positive sign (face/asymmetrical arm weakness, speech disturbance). Positive ROSIER was defined as a score of ≥1. Accuracy and interrater agreement between the tools and patients' true status were assessed for combined stroke types and arterial stroke (AIS) and hemorrhagic stroke (HS) subtypes vs mimics. Stroke subtypes included AIS (55), HS (34), TIA (10), and sinovenous thrombosis (2). Mimic diagnoses included migraine (84), first seizure (45), Bell palsy (29), and conversion disorders (18). Both tools had poor reliability and accuracy for combined strokes vs mimics (CPSS κ 0.36, receiver operator characteristic curve [ROC] 0.66; ROSIER κ 0.32, ROC 0.60) and for AIS vs mimics (CPSS κ 0.37, ROC 0.79; ROSIER κ 0.30, ROC 0.77). Both tools performed inadequately for HS vs mimics (CPSS κ -0.03, ROC 0.51; ROSIER κ -0.02, ROC 0.52). Adult stroke recognition tools perform poorly in children and require modification to be useful for pediatric stroke identification. This study provides Class II evidence that, for children presenting to the ED with brain attack symptoms, the CPSS and ROSIER tools do not accurately distinguish strokes from mimics.

Paramedic Perspectives on Barriers to Prehospital Acute Stroke Recognition

ABSTRACTBackground: Emergency Medical Service (EMS) providers are tasked with rapid evaluation, stabilization, recognition, and transport of acute stroke patients. Although prehospital stroke scales were developed to assist with stroke recognition, unrecognized challenges exist in the prehospital setting that hinder accurate assessment of stroke. The goal of this qualitative study was to systematically understand the challenges and barriers faced by paramedics in recognizing stroke presentations in the field. Methods: Paramedics from 12 EMS agencies serving a mix of rural, suburban, and urban communities in the State of California participated in five focus group discussions. Group size ranged from 3–8, with a total of 28 participants. Demographics of the participants were collected and focus group recordings were transcribed verbatim. Transcripts were subjected to deductive and inductive coding, which identified recurrent and divergent themes. Results: Strong consensus existed around constraints to prehospital stroke recognition; participants cited the diversity of stroke presentations, linguistic diversity, and exam confounded by alcohol and or drug use as barriers to initial evaluation. Also, lack of educational feedback from hospital staff and physicians and continuing medical education on stroke were reported as major deterrents to enhancing their diagnostic acumen. Across groups, participants reported attempting to foster relationships with hospital personnel to augment their educational needs, but this was easier for rural than urban providers. Conclusions: While challenges to stroke recognition in the field were slightly different for rural and urban EMS, participants concurred that timely, systematic feedback on individual patients and case-based training would strengthen early stroke recognition skills.

Clinical Predictors of Accurate Prehospital Stroke Recognition: Oostema JA, Konen J, Chassee T, et al. Stroke. 2015;46:1513-1517

Clinical Predictors of Accurate Prehospital Stroke Recognition: Oostema JA, Konen J, Chassee T, et al. Stroke. 2015;46:1513-1517

Knowledge of Community General Practitioners and Nurses on Pre-Hospital Stroke Prevention and Treatment in Chongqing, China

Background and PurposeThis study aimed to investigate the knowledge of community general practitioners (GPs) and nurses about pre-hospital stroke recognition, treatment and management and secondary stroke prevention; to identify the sociodemographic and educational factors influencing knowledge.MethodsA self-designed test questionnaire was applied in a self-administered close-exam setting among 480 GPs and nurses working in community health centers (stations) in eight urban districts of Chongqing.ResultsA total of 331 (69%) valid test questionnaires were returned. Of the 331 participants, 39% were aware of the clinical guidelines for cerebrovascular diseases, whereas 48% considered themselves to have stroke management capabilities. The correct rate of answering questions of pre-hospital recognition and management knowledge was as low as 24%, the correct rate of secondary stroke prevention knowledge was only 38%. In terms of the total score for stroke prevention and treatment knowledge, there were significant differences between the medical staff with different specialties before engaging in community health services and whether they have received GP training (P <0.05).ConclusionThe community GPs and nurses in the urban districts of Chongqing clearly lack knowledge of stroke, and the levels of stroke prevention and treatment urgently need to be improved.

Clinical Predictors of Accurate Prehospital Stroke Recognition

Prehospital activation of in-hospital stroke response hastens treatment but depends on accurate emergency medical services (EMS) stroke recognition. We sought to measure EMS stroke recognition accuracy and identify clinical factors associated with correct stroke identification. Using EMS and hospital records, we assembled a cohort of EMS-transported suspect, confirmed, or missed ischemic stroke or transient ischemic attack cases. The sensitivity and positive predictive value (PPV) for EMS stroke recognition were calculated using the hospital discharge diagnosis as the gold standard. We used multivariable logistic regression analysis to determine the association between Cincinnati Prehospital Stroke Scale use and EMS stroke recognition. During a 12-month period, 441 EMS-transported patients were enrolled; of which, 371 (84.1%) were EMS-suspected strokes and 70 (15.9%) were EMS-missed strokes. Overall, 264 cases (59.9%) were confirmed as either ischemic stroke (n=186) or transient ischemic attack (n=78). The sensitivity of EMS stroke recognition was 73.5% (95% confidence interval, 67.7-78.7), and PPV was 52.3% (95% confidence interval, 47.1-57.5). Sensitivity (84.7% versus 30.9%; P<0.0001) and PPV (56.2% versus 30.4%; P=0.0004) were higher among cases with Cincinnati Prehospital Stroke Scale documentation. In multivariate analysis, Cincinnati Prehospital Stroke Scale documentation was independently associated with EMS sensitivity (odds ratio, 12.0; 95% confidence interval, 5.7-25.5) and PPV (odds ratio, 2.5; 95% confidence interval, 1.3-4.7). EMS providers recognized 3 quarters of the patients with ischemic stroke and transient ischemic attack; however, half of EMS-suspected strokes were false positives. Documentation of a Cincinnati Prehospital Stroke Scale was associated with higher EMS stroke recognition sensitivity and PPV.

STROKE MIMICS IN THE PRE-HOSPITAL SETTING

Accurate identification of stroke patients is essential to ensure appropriate and timely treatment. Stroke mimics—patients initially suspected to have suffered a stroke who are subsequently diagnosed with a condition other...