9 research outputs found

    A topical review of the feasibility and reliability of ambulance-based telestroke

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    BackgroundAmbulance-based telemedicine is an innovative strategy through which transport time can be used to rapidly and accurately triage stroke patients (i.e., mobile telestroke). The acute phase of stroke is a time-sensitive emergency, and delays in care during this phase worsen outcomes. In this literature review, we analyzed studies that investigated the feasibility and reliability of ambulance based telestroke.MethodsWe followed PRISMA guidelines to perform a keyword-based search of PubMed, Web of Science, CINHAL, and Academic Search Complete databases. We reviewed references of search-identified articles to screen for additional articles. Articles for inclusion were selected according to author consensus in consideration of the studies' investigation of feasibility, reliability, or validity of ambulance-based telestroke.ResultsWe identified 67 articles for secondary screening from which 19 articles were selected for full text review. The selected studies reported diverse methods of development, implementation, and assessment of ambulance-based telestroke systems. Although the methods and results varied among these studies, most concluded that the implementation of ambulance based telestroke is feasible.ConclusionThis topical review suggests that ambulance based telestroke is a feasible method for enhanced prehospital stroke care in a variety of settings. Further prospective research is needed to assess the real-world challenges and to identify additional strategies that bolster rapid and accurate prehospital assessment of acute stroke patients

    Prehospital Stroke Care Part 2: On-Scene Evaluation and Management by Emergency Medical Services Practitioners

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    The prehospital phase is a critical component of delivering high-quality acute stroke care. This topical review discusses the current state of prehospital acute stroke screening and transport, as well as new and emerging advances in prehospital diagnosis and treatment of acute stroke. Topics include prehospital stroke screening, stroke severity screening, emerging technologies to aid in the identification and diagnosis of acute stroke in the prehospital setting, prenotification of receiving emergency departments, decision support for destination determination, and the capabilities and opportunities for prehospital stroke treatment in mobile stroke units. Further evidence-based guideline development and implementation of new technologies are critical for ongoing improvements in prehospital stroke care

    A Rare Case of Immune Reconstitution Inflammatory Syndrome Development in an Immunocompromised Patient with Progressive Multifocal Leukoencephalopathy and Multicentric Castleman’s Disease

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    Immune reconstitution inflammatory syndrome (IRIS) development in HIV with preexistent progressive multifocal leukoencephalopathy (PML) has been extensively studied. PML-IRIS typically manifests clinically as new or worsening neurologic symptoms in conjunction with enlarging CNS lesions and occurs in approximately 10–20 percent of HIV-infected patients with PML who begin HAART. Likewise, Multicentric Castleman’s Disease (MCD), a rare malignant lymphoproliferative disorder, has a strong and well-known association with HIV. Our case provides a rare instance of PML-IRIS in combination with MCD in an HIV-positive individual. The combination of all three diseases has never been reported in the literature. Both MCD and PML were present during initial determination of HIV infection in our patient and their disease courses were altered during the subsequent development of IRIS

    Human vs. Machine Learning Based Detection of Facial Weakness Using Video Analysis.

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    BACKGROUND: Current EMS stroke screening tools facilitate early detection and triage, but the tools\u27 accuracy and reliability are limited and highly variable. An automated stroke screening tool could improve stroke outcomes by facilitating more accurate prehospital diagnosis and delivery. We hypothesize that a machine learning algorithm using video analysis can detect common signs of stroke. As a proof-of-concept study, we trained a computer algorithm to detect presence and laterality of facial weakness in publically available videos with comparable accuracy, sensitivity, and specificity to paramedics. METHODS AND RESULTS: We curated videos of people with unilateral facial weakness ( CONCLUSIONS: These preliminary results suggest that a machine learning algorithm using computer vision analysis can detect unilateral facial weakness in pre-recorded videos with an accuracy and sensitivity comparable to trained paramedics. Further research is warranted to pursue the concept of augmented facial weakness detection and external validation of this algorithm in independent data sets and prospective patient encounters

    A low-cost, tablet-based option for prehospital neurologic assessment

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    ObjectivesIn this 2-center study, we assessed the technical feasibility and reliability of a low cost, tablet-based mobile telestroke option for ambulance transport and hypothesized that the NIH Stroke Scale (NIHSS) could be performed with similar reliability between remote and bedside examinations.MethodsWe piloted our mobile telemedicine system in 2 geographic regions, central Virginia and the San Francisco Bay Area, utilizing commercial cellular networks for videoconferencing transmission. Standardized patients portrayed scripted stroke scenarios during ambulance transport and were evaluated by independent raters comparing bedside to remote mobile telestroke assessments. We used a mixed-effects regression model to determine intraclass correlation of the NIHSS between bedside and remote examinations (95% confidence interval).ResultsWe conducted 27 ambulance runs at both sites and successfully completed the NIHSS for all prehospital assessments without prohibitive technical interruption. The mean difference between bedside (face-to-face) and remote (video) NIHSS scores was 0.25 (1.00 to -0.50). Overall, correlation of the NIHSS between bedside and mobile telestroke assessments was 0.96 (0.92-0.98). In the mixed-effects regression model, there were no statistically significant differences accounting for method of evaluation or differences between sites.ConclusionsUtilizing a low-cost, tablet-based platform and commercial cellular networks, we can reliably perform prehospital neurologic assessments in both rural and urban settings. Further research is needed to establish the reliability and validity of prehospital mobile telestroke assessment in live patients presenting with acute neurologic symptoms

    Pathogenic ischemic stroke phenotypes in the NINDS-Stroke Genetics Network

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    BACKGROUND AND PURPOSE: NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium. METHODS: Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases. RESULTS: The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (κ 0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (κ 0.73; 95% confidence interval, 0.70-0.75). CONCLUSIONS: This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke

    Loci associated with ischaemic stroke and its subtypes (SiGN): a genome-wide association study

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    BACKGROUND: The discovery of disease-associated loci through genome-wide association studies (GWAS) is the leading genetic approach to the identification of novel biological pathways underlying diseases in humans. Until recently, GWAS in ischaemic stroke have been limited by small sample sizes and have yielded few loci associated with ischaemic stroke. We did a large-scale GWAS to identify additional susceptibility genes for stroke and its subtypes. METHODS: To identify genetic loci associated with ischaemic stroke, we did a two-stage GWAS. In the first stage, we included 16 851 cases with state-of-the-art phenotyping data and 32 473 stroke-free controls. Cases were aged 16 to 104 years, recruited between 1989 and 2012, and subtypes of ischaemic stroke were recorded by centrally trained and certified investigators who used the web-based protocol, Causative Classification of Stroke (CCS). We constructed case-control strata by identifying samples that were genotyped on nearly identical arrays and were of similar genetic ancestral background. We cleaned and imputed data by use of dense imputation reference panels generated from whole-genome sequence data. We did genome-wide testing to identify stroke-associated loci within each stratum for each available phenotype, and we combined summary-level results using inverse variance-weighted fixed-effects meta-analysis. In the second stage, we did in-silico lookups of 1372 single nucleotide polymorphisms identified from the first stage GWAS in 20 941 cases and 364 736 unique stroke-free controls. The ischaemic stroke subtypes of these cases had previously been established with the Trial of Org 10 172 in Acute Stroke Treatment (TOAST) classification system, in accordance with local standards. Results from the two stages were then jointly analysed in a final meta-analysis. FINDINGS: We identified a novel locus (G allele at rs12122341) at 1p13.2 near TSPAN2 that was associated with large artery atherosclerosis-related stroke (first stage odds ratio [OR] 1·21, 95% CI 1·13-1·30, p=4·50 × 10-8; joint OR 1·19, 1·12-1·26, p=1·30 × 10-9). Our results also supported robust associations with ischaemic stroke for four other loci that have been reported in previous studies, including PITX2 (first stage OR 1·39, 1·29-1·49, p=3·26 × 10-19; joint OR 1·37, 1·30-1·45, p=2·79 × 10-32) and ZFHX3 (first stage OR 1·19, 1·11-1·27, p=2·93 × 10-7; joint OR 1·17, 1·11-1·23, p=2·29 × 10-10) for cardioembolic stroke, and HDAC9 (first stage OR 1·29, 1·18-1·42, p=3·50 × 10-8; joint OR 1·24, 1·15-1·33, p=4·52 × 10-9) for large artery atherosclerosis stroke. The 12q24 locus near ALDH2, which has previously been associated with all ischaemic stroke but not with any specific subtype, exceeded genome-wide significance in the meta-analysis of small artery stroke (first stage OR 1·20, 1·12-1·28, p=6·82 × 10-8; joint OR 1·17, 1·11-1·23, p=2·92 × 10-9). Other loci associated with stroke in previous studies, including NINJ2, were not confirmed. INTERPRETATION: Our results suggest that all ischaemic stroke-related loci previously implicated by GWAS are subtype specific. We identified a novel gene associated with large artery atherosclerosis stroke susceptibility. Follow-up studies will be necessary to establish whether the locus near TSPAN2 can be a target for a novel therapeutic approach to stroke prevention. In view of the subtype-specificity of the associations detected, the rich phenotyping data available in the Stroke Genetics Network (SiGN) are likely to be crucial for further genetic discoveries related to ischaemic stroke
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