28 research outputs found

    Prevalence and Risk Factors of Neurologic Manifestations in Hospitalized Children Diagnosed with Acute SARS-CoV-2 or MIS-C

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    Background: Our objective was to characterize the frequency, early impact, and risk factors for neurological manifestations in hospitalized children with acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or multisystem inflammatory syndrome in children (MIS-C). Methods: Multicenter, cross-sectional study of neurological manifestations in children aged <18 years hospitalized with positive SARS-CoV-2 test or clinical diagnosis of a SARS-CoV-2-related condition between January 2020 and April 2021. Multivariable logistic regression to identify risk factors for neurological manifestations was performed. Results: Of 1493 children, 1278 (86%) were diagnosed with acute SARS-CoV-2 and 215 (14%) with MIS-C. Overall, 44% of the cohort (40% acute SARS-CoV-2 and 66% MIS-C) had at least one neurological manifestation. The most common neurological findings in children with acute SARS-CoV-2 and MIS-C diagnosis were headache (16% and 47%) and acute encephalopathy (15% and 22%), both P < 0.05. Children with neurological manifestations were more likely to require intensive care unit (ICU) care (51% vs 22%), P < 0.001. In multivariable logistic regression, children with neurological manifestations were older (odds ratio [OR] 1.1 and 95% confidence interval [CI] 1.07 to 1.13) and more likely to have MIS-C versus acute SARS-CoV-2 (OR 2.16, 95% CI 1.45 to 3.24), pre-existing neurological and metabolic conditions (OR 3.48, 95% CI 2.37 to 5.15; and OR 1.65, 95% CI 1.04 to 2.66, respectively), and pharyngeal (OR 1.74, 95% CI 1.16 to 2.64) or abdominal pain (OR 1.43, 95% CI 1.03 to 2.00); all P < 0.05. Conclusions: In this multicenter study, 44% of children hospitalized with SARS-CoV-2-related conditions experienced neurological manifestations, which were associated with ICU admission and pre-existing neurological condition. Posthospital assessment for, and support of, functional impairment and neuroprotective strategies are vitally needed

    REVIEW ON FEATURE SELECTION TECHNIQUES AND ITS IMPACT FOR EFFECTIVE DATA CLASSIFICATION USING UCI MACHINE LEARNING REPOSITORY DATASET

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    Feature selection goal is to get rid of redundant and irrelevant features. The problem of feature subset selection is that of finding a subset of the original features of a dataset, such that an induction algorithm run on data containing only selected features makes a classifier to generate with the highest possible accuracy. High dimensional data can contain a high degree of irrelevant and redundant features which may greatly degrade the performance of learning algorithms. The performance of different feature selectors such as CFS, Chi-Square, Information Gain, Gain Ratio, One R and Symmetrical Uncertainty were evaluated on two different popular classification algorithms namely Decision Tree and Naive Bayesian method. A significant improvement in the performance of DT and NB classifier was shown after reducing the number of both irrelevant and redundant features by the use of different feature ranking methods

    Pediatric Acute Stroke Protocols in the United States and Canada

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    OBJECTIVE: To describe existing pediatric acute stroke protocols to better understand how pediatric centers might implement such pathways within the context of institution-specific structures. STUDY DESIGN: We administered an Internet-based survey of pediatric stroke specialists. The survey included questions about hospital demographics, child neurology and pediatric stroke demographics, acute stroke response, imaging, and hyperacute treatment. RESULTS: Forty-seven surveys were analyzed. Most respondents practiced at a large, freestanding children\u27s hospital with a moderate-sized neurology department and at least 1 neurologist with expertise in pediatric stroke. Although there was variability in how the hospitals deployed stroke protocols, particularly in regard to staffing, the majority of institutions had an acute stroke pathway, and almost all included activation of a stroke alert page. Most institutions preferred magnetic resonance imaging (MRI) over computed tomography (CT) and used abbreviated MRI protocols for acute stroke imaging. Most institutions also had either CT-based or magnetic resonance-based perfusion imaging available. At least 1 patient was treated with intravenous tissue plasminogen activator (IV-tPA) or mechanical thrombectomy at the majority of institutions during the year before our survey. CONCLUSIONS: An acute stroke protocol is utilized in at least 41 pediatric centers in the US and Canada. Most acute stroke response teams are multidisciplinary, prefer abbreviated MRI over CT for diagnosis, and have experience providing IV-tPA and mechanical thrombectomy. Further studies are needed to standardize practices of pediatric acute stroke diagnosis and hyperacute management
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