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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.

ABSTRACT: OBJECTIVE:To 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 vessel occlusion (LVO). METHODS:Emergency medical services (EMS) personnel and stroke physicians (n=326) rated each item of the NIHSS regarding suitability for prehospital use; best rated items were included. Stroke recognition was evaluated retrospectively in 689 consecutive patients with acute stroke or stroke mimics, prediction of LVO in 741 consecutive patients with ischaemic stroke with acute vessel imaging independent of admission NIHSS score. RESULTS:Nine of the NIHSS items were rated as 'suitable for prehospital use.' After excluding two items in order to increase specificity, the final scale (termed shortened NIHSS for EMS, sNIHSS-EMS) consists of 'level of consciousness', 'facial palsy', 'motor arm/leg', 'sensory', 'language' and 'dysarthria'. Sensitivity for stroke recognition of the sNIHSS-EMS is 91% (95% CI 86 to 94), specificity 52% (95% CI 47 to 56). Receiver operating curve analysis revealed an optimal cut-off point for LVO prediction of ?6 (sensitivity 70% (95% CI 65 to 76), specificity 81% (95% CI 76 to 84), positive predictive value 70 (95% CI 65 to 75), area under the curve 0.81 (95% CI 0.78 to 0.84)). Test characteristics were non-inferior to non-comprehensive scales. CONCLUSIONS:The sNIHSS-EMS may overcome the sequential use of multiple emergency stroke scales by permitting parallel stroke recognition, severity grading and LVO prediction. Full NIHSS-item compatibility allows for evaluation of stroke progression starting at the prehospital phase.

SUBMITTER: Purrucker JC

PROVIDER: S-EPMC5589005 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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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.

Purrucker Jan Christoph JC Härtig Florian F Richter Hardy H Engelbrecht Andreas A Hartmann Johannes J Auer Jonas J Hametner Christian C Popp Erik E Ringleb Peter Arthur PA Nagel Simon S Poli Sven S

BMJ open 20170901 9

<h4>Objective</h4>To 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 vessel occlusion (LVO).<h4>Methods</h4>Emergency medical services (EMS) personnel and stroke physicians (n=326) rated each item of the NIHSS regarding suitability for prehospital use; best rated items were included. Stroke recognition was evaluated re ...[more]

PMID: 28864702

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Project description:Background and objectivesEndovascular thrombectomy (EVT) is standard treatment for anterior large vessel occlusion stroke (LVO-a stroke). Prehospital diagnosis of LVO-a stroke would reduce time to EVT by allowing direct transportation to an EVT-capable hospital. We aim to evaluate the diagnostic accuracy of dry electrode EEG for the detection of LVO-a stroke in the prehospital setting.MethodsELECTRA-STROKE was an investigator-initiated, prospective, multicenter, diagnostic study, performed in the prehospital setting. Adult patients were eligible if they had suspected stroke (as assessed by the attending ambulance nurse) and symptom onset <24 hours. A single dry electrode EEG recording (8 electrodes) was performed by ambulance personnel. Primary endpoint was the diagnostic accuracy of the theta/alpha frequency ratio for LVO-a stroke (intracranial ICA, A1, M1, or proximal M2 occlusion) detection among patients with EEG data of sufficient quality, expressed as the area under the receiver operating characteristic curve (AUC). Secondary endpoints were diagnostic accuracies of other EEG features quantifying frequency band power and the pairwise derived Brain Symmetry Index. Neuroimaging was assessed by a neuroradiologist blinded to EEG results.ResultsBetween August 2020 and September 2022, 311 patients were included. The median EEG duration time was 151 (interquartile range [IQR] 151-152) seconds. For 212/311 (68%) patients, EEG data were of sufficient quality for analysis. The median age was 74 (IQR 66-81) years, 90/212 (42%) were women, and the median baseline NIH Stroke Scale was 1 (IQR 0-4). Six (3%) patients had an LVO-a stroke, 109/212 (51%) had a non-LVO-a ischemic stroke, 32/212 (15%) had a transient ischemic attack, 8/212 (4%) had a hemorrhagic stroke, and 57/212 (27%) had a stroke mimic. AUC of the theta/alpha ratio was 0.80 (95% CI 0.58-1.00). Of the secondary endpoints, the pairwise derived Brain Symmetry Index in the delta frequency band had the highest diagnostic accuracy (AUC 0.91 [95% CI 0.73-1.00], sensitivity 80% [95% CI 38%-96%], specificity 93% [95% CI 88%-96%], positive likelihood ratio 11.0 [95% CI 5.5-21.7]).DiscussionThe data from this study suggest that dry electrode EEG has the potential to detect LVO-a stroke among patients with suspected stroke in the prehospital setting. Toward future implementation of EEG in prehospital stroke care, EEG data quality needs to be improved.Trial registration informationClinicalTrials.gov identifier: NCT03699397.Classification of evidenceThis study provides Class II evidence that prehospital dry electrode scalp EEG accurately detects LVO-a stroke among patients with suspected acute stroke.

Project description:Background and purposeConsidering the highly time-dependent therapeutic effect of endovascular treatment in patients with large vessel occlusion-associated acute ischemic stroke, prehospital identification of large vessel occlusion and subsequent triage for direct transport to a comprehensive stroke center offers an intriguing option for optimizing patient pathways.MethodsThis prospective in-field validation study included 200 patients with suspected acute ischemic stroke who were admitted by emergency medical service to a comprehensive stroke center. Ambulances were equipped with smartphones running an app-based Field Assessment Stroke Triage for Emergency Destination scale for transmission prior to admission. The primary measure was the predictive accuracy of the transmitted Field Assessment Stroke Triage for Emergency Destination for large vessel occlusion and the secondary measure the predictive accuracy for endovascular treatment.ResultsA Field Assessment Stroke Triage for Emergency Destination ⩾4 revealed very good accuracy to detect large vessel occlusion-related acute ischemic stroke with a sensitivity of 82.4% (95% confidence interval = 65.5-93.2), specificity of 78.3% (95% confidence interval = 71.3-84.3), and an area under the curve c-statistics of 0.89 (95% confidence interval = 0.85-0.94). Field Assessment Stroke Triage for Emergency Destination ⩾4 correctly identified 84% of patients who received endovascular treatment [73.5% specificity (95% confidence interval = 66.4-79.8)] with an area under the curve c-statistics of 0.82 (95% confidence interval = 0.74-0.89). In a hypothetical triage model of an urban setting, one secondary transportation would be avoided with every fifth patient screened.ConclusionA smartphone app-based stroke triage completed by emergency medical service personnel showed adequate quality for the Field Assessment Stroke Triage for Emergency Destination to identify large vessel occlusion-associated acute ischemic stroke. We demonstrate feasibility of the use of a medical messaging service in prehospital stroke care. Based on these first results, a randomized trial evaluating the clinical benefit of such a triage system in an urban setting is currently in preparation.Clinical Trial Registration: https://clinicaltrials.gov Unique identifier: NCT04404504.

Project description:BACKGROUND AND PURPOSE:Prehospital scales have been developed to identify patients with acute cerebral ischemia (ACI) because of large vessel occlusion (LVO) for direct routing to Comprehensive Stroke Centers (CSCs), but few have been validated in the prehospital setting, and their impact on routing of patients with intracranial hemorrhage has not been delineated. The purpose of this study was to validate the Los Angeles Motor Scale (LAMS) for LVO and CSC-appropriate (LVO ACI and intracranial hemorrhage patients) recognition and compare the LAMS to other scales. METHODS:The performance of the LAMS, administered prehospital by paramedics to consecutive ambulance trial patients, was assessed in identifying (1) LVOs among all patients with ACI and (2) CSC-appropriate patients among all suspected strokes. Additionally, the LAMS administered postarrival was compared concurrently with 6 other scales proposed for paramedic use and the full National Institutes of Health Stroke Scale. RESULTS:Among 94 patients, age was 70 (±13) and 49% female. Final diagnoses were ACI in 76% (because of LVO in 48% and non-LVO in 28%), intracranial hemorrhage in 19%, and neurovascular mimic in 5%. The LAMS administered by paramedics in the field performed moderately well in identifying LVO among patients with ACI (C statistic, 0.79; accuracy, 0.72) and CSC-appropriate among all suspected stroke transports (C statistic, 0.80; accuracy, 0.72). When concurrently performed in the emergency department postarrival, the LAMS showed comparable or better accuracy versus the 7 comparator scales, for LVO among ACI (accuracies LAMS, 0.70; other scales, 0.62-0.68) and CSC-appropriate (accuracies LAMS, 0.73; other scales, 0.56-0.73). CONCLUSIONS:The LAMS performed in the field by paramedics identifies LVO and CSC-appropriate patients with good accuracy. The LAMS performs comparably or better than more extended prehospital scales and the full National Institutes of Health Stroke Scale.

Dataset Information

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.

Publications

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.

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