Showing 1 - 20 results of 33 for search '"South London"', query time: 0.06s Refine Results
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    Typological and cumulative approaches to risk and adversity in Child and Adolescent Mental Health Services (CAMHS): Retrospective cohort analysis in South London by Barry Coughlan, Nicole Marshall, Matt Woolgar, Julia Mannes, Paige Erkiert, Ayla Humphrey, Jack Smith, Taliah Drayak, Francesca Crozier-Roche, Tessa Morgan, Dustin Hutchinson, David Graham, Rick Hood, Robbie Duschinsky

    Published 2025-02-01
    “…Methods: We analysed risk assessment data from 21,072 young people attending mental health services in South London. These assessments include items relating to maltreatment, parental mental health difficulties, substance misuse, self-harm, and violent behaviour. …”
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    Diabetes Complications at Presentation and One Year by Glycated Haemoglobin at Diagnosis in a Multiethnic and Diverse Socioeconomic Population: Results from the South London Diabetes Study by Mohsin Azam, Lindsey Marwood, Khalida Ismail, Tyrrell Evans, Sobha Sivaprasad, Kirsty Winkley, Stephanie Anne Amiel

    Published 2015-01-01
    “…WHO’s recommendation of HbA1c≥48 mmol/mol (6.5%) as diagnostic for type 2 diabetes mellitus (T2DM) was adopted by three UK London boroughs in May 2012. The South London Diabetes (SOUL-D) study has recruited people with newly diagnosed T2DM since 2008. …”
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    Investigating the relationship between thought interference, somatic passivity and outcomes in patients with psychosis: a natural language processing approach using a clinical records search platform in south London by Robert Stewart, Anna Kolliakou, Jyoti Sanyal, Rashmi Patel, Thibault Thierry Magrangeas

    Published 2022-08-01
    “…Objectives We aimed to apply natural language processing algorithms in routine healthcare records to identify reported somatic passivity (external control of sensations, actions and impulses) and thought interference symptoms (thought broadcasting, insertion, withdrawal), first-rank symptoms traditionally central to diagnosing schizophrenia, and determine associations with prognosis by analysing routine outcomes.Design Four algorithms were developed on deidentified mental healthcare data and applied to ascertain recorded symptoms over the 3 months following first presentation to a mental healthcare provider in a cohort of patients with a primary schizophreniform disorder (ICD-10 F20-F29) diagnosis.Setting and participants From the electronic health records of a large secondary mental healthcare provider in south London, 9323 patients were ascertained from 2007 to the data extraction date (25 February 2020).Outcomes The primary binary dependent variable for logistic regression analyses was any negative outcome (Mental Health Act section, >2 antipsychotics prescribed, >22 days spent in crisis care) over the subsequent 2 years.Results Final adjusted models indicated significant associations of this composite outcome with baseline somatic passivity (prevalence 4.9%; adjusted OR 1.61, 95% CI 1.37 to 1.88), thought insertion (10.7%; 1.24, 95% CI 1.15 to 1.55) and thought withdrawal (4.9%; 1.36, 95% CI 1.10 to 1.69), but not independently with thought broadcast (10.3%; 1.05, 95% CI 0.91 to 1.22).Conclusions Symptoms traditionally central to the diagnosis of schizophrenia, but under-represented in current diagnostic frameworks, were thus identified as important predictors of short-term to medium-term prognosis in schizophreniform disorders.…”
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    Negative symptoms in schizophrenia: a study in a large clinical sample of patients using a novel automated method by Robert Stewart, Hitesh Shetty, Matthew Broadbent, Angus Roberts, Rashmi Patel, Philip McGuire, Richard D Hayes, Nishamali Jayatilleke, Genevieve Gorrell, Chin-Kuo Chang, Richard Jackson, Nadia Foskett, Caroline Johnston

    Published 2015-09-01
    “…Objectives To identify negative symptoms in the clinical records of a large sample of patients with schizophrenia using natural language processing and assess their relationship with clinical outcomes.Design Observational study using an anonymised electronic health record case register.Setting South London and Maudsley NHS Trust (SLaM), a large provider of inpatient and community mental healthcare in the UK.Participants 7678 patients with schizophrenia receiving care during 2011.Main outcome measures Hospital admission, readmission and duration of admission.Results 10 different negative symptoms were ascertained with precision statistics above 0.80. 41% of patients had 2 or more negative symptoms. …”
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    A proof-of-concept analysis of data from the first NHS clinic for young adults with comorbid cannabis use and psychotic disorders by Marta Di Forti, Benjamin W. Bond, Edoardo Spinazzola, Giulia Trotta, Jodie Lynn, Richard Malkin, Naba Kamran Siddiqui, Sultan Demir, Titilayomi Opadokun, Perry B.M. Leung, Zhikun Li, Andrea Quattrone, Gabriella Baxter, Elizabeth Appiah-Kusi, Tom P. Freeman, Hannah Walsh, Tommaso Squeri, Daria Semikina, Felicity Amberson-Jones, Isabelle Austin-Zimmerman, Tim Meynen, Diego Quattrone, Robin M. Murray

    Published 2025-01-01
    “…Method The sample (N = 46) consisted of adults (aged ≥ 18) with psychosis under the care of the South London and Maudsley NHS Foundation Trust, referred to the CCP between January 2020 and February 2023, who completed their intervention by September 2023. …”
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    To Exist is a Form of Resistance by Sarah Allen, Aina Landsverk Hagen

    Published 2025-01-01
    “…In this interview, Sarah Allen, Head of Programme and co-curator of the exhibition Acts of Resistance: Photography, Feminisms and the Art of Protest at the South London Gallery, elaborates on the reasoning behind the show. …”
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    Assessing machine learning for fair prediction of ADHD in school pupils using a retrospective cohort study of linked education and healthcare data by Johnny Downs, Robert Stewart, Alice Wickersham, Sumithra Velupillai, Lucile Ter-Minassian, Natalia Viani, Lauren Cross

    Published 2022-12-01
    “…Using a unique linked health and education data resource, we examined how machine learning (ML) approaches can predict risk of ADHD.Design Retrospective population cohort study.Setting South London (2007–2013).Participants n=56 258 pupils with linked education and health data.Primary outcome measures Using area under the curve (AUC), we compared the predictive accuracy of four ML models and one neural network for ADHD diagnosis. …”
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    Trans-architecture by Tim Gough

    Published 2017-12-01
    “…The paper concludes by showing how this ontology relates to a specific instance of transing architecture in the gay and SM clubs of Vauxhall, South London.…”
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    On Resisting Global Disposability, Regimes of Death-Making and Accumulation by Rupinder Parhar

    Published 2025-02-01
    “…Acts of Resistance: Photography, Feminisms and the Art of Protest, 2024. South London Gallery. …”
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