33 research outputs found

    A synthesis of the ecological processes influencing variation in life history and movement patterns of American eel: towards a global assessment

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    Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

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    Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

    The MSOAC approach to developing performance outcomes to measure and monitor multiple sclerosis disability

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    BACKGROUND: The Multiple Sclerosis Outcome Assessments Consortium (MSOAC) was formed by the National MS Society to develop improved measures of multiple sclerosis (MS)-related disability. OBJECTIVES: (1) To assess the current literature and available data on functional performance outcome measures (PerfOs) and (2) to determine suitability of using PerfOs to quantify MS disability in MS clinical trials. METHODS: (1) Identify disability dimensions common in MS; (2) conduct a comprehensive literature review of measures for those dimensions; (3) develop an MS Clinical Data Interchange Standards Consortium (CDISC) data standard; (4) create a database of standardized, pooled clinical trial data; (5) analyze the pooled data to assess psychometric properties of candidate measures; and (6) work with regulatory agencies to use the measures as primary or secondary outcomes in MS clinical trials. CONCLUSION: Considerable data exist supporting measures of the functional domains ambulation, manual dexterity, vision, and cognition. A CDISC standard for MS ( http://www.cdisc.org/therapeutic#MS ) was published, allowing pooling of clinical trial data. MSOAC member organizations contributed clinical data from 16 trials, including 14,370 subjects. Data from placebo-arm subjects are available to qualified researchers. This integrated, standardized dataset is being analyzed to support qualification of disability endpoints by regulatory agencies

    High-Resolution Diffusion Tensor Spinal Cord MRI Measures as Biomarkers of Disability Progression in a Rodent Model of Progressive Multiple Sclerosis

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    <div><p>Disease in the spinal cord is a major component of disability in multiple sclerosis, yet current techniques of imaging spinal cord injury are insensitive and nonspecific. This study seeks to remove this major impediment to research in multiple sclerosis and other spinal cord diseases by identifying reliable biomarkers of disability progression using diffusion tensor imaging (DTI), a magnetic resonance imaging technique, to evaluate the spinal cord in a model of multiple sclerosis, i.e. the Theiler’s Murine Encephalitis Virus-Induced Demyelinating Disease (TMEV-IDD). Mice with TMEV-IDD with varying levels of clinical disease were imaged using a 9.4T small animal MRI scanner. Axial diffusivity, radial diffusivity, and fractional anisotropy were calculated. Disability was assessed periodically using Rotarod assay and data were expressed as a neurological function index. Correlation was performed between DTI measurements and disability scores. TMEV-IDD mice displayed significant increased neurological deficits over time when compared with controls (<i>p</i><0.0001). Concurrently, the values of fractional anisotropy and axial diffusivity were both decreased compared to controls (both <i>p</i><0.0001), while radial diffusivity was increased (<i>p</i><0.0001). Overall, fractional anisotropy changes were larger in white matter than in grey matter and differences were more pronounced in the ventral region. Lower disability scores were associated with decreased fractional anisotropy values measured in the ventral (r = 0.68; <i>p</i><0.0001) and ventral-lateral (r = 0.70; <i>p</i><0.0001) regions of the white matter. These data demonstrate that DTI measures of the spinal cord contribute to strengthening the association between neuroradiological markers and clinical disability, and support the use of DTI measures in spinal cord imaging in MS patients.</p></div
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