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Biomarker identification using dynamic time warping analysis: a longitudinal cohort study of patients with COVID-19 in a UK tertiary hospital.
Burke, Hannah; Freeman, Anna; O'Regan, Paul; Wysocki, Oskar; Freitas, Andre; Dushianthan, Ahilanandan; Celinski, Michael; Batchelor, James; Phan, Hang; Borca, Florina; Sheard, Natasha; Williams, Sarah; Watson, Alastair; Fitzpatrick, Paul; Landers, Dónal; Wilkinson, Tom.
Afiliação
  • Burke H; Faculty of Medicine, University of Southampton, Southampton, UK.
  • Freeman A; Faculty of Medicine, University of Southampton, Southampton, UK a.freeman@soton.ac.uk.
  • O'Regan P; Digital Experimental Cancer Medicine Team, Cancer Biomarker Centre, Cancer Research UK Manchester Institute, The University of Manchester, Manchester, UK.
  • Wysocki O; Digital Experimental Cancer Medicine Team, Cancer Biomarker Centre, Cancer Research UK Manchester Institute, The University of Manchester, Manchester, UK.
  • Freitas A; Digital Experimental Cancer Medicine Team, Cancer Biomarker Centre, Cancer Research UK Manchester Institute, The University of Manchester, Manchester, UK.
  • Dushianthan A; Faculty of Medicine, University of Southampton, Southampton, UK.
  • Celinski M; Faculty of Medicine, University of Southampton, Southampton, UK.
  • Batchelor J; Faculty of Medicine, University of Southampton, Southampton, UK.
  • Phan H; Clinical Informatics Research Unit, University of Southampton Faculty of Medicine, Southampton, UK.
  • Borca F; University of Southampton, Southampton, UK.
  • Sheard N; Institute for Life Sciences, University of Southampton, Southampton, UK.
  • Williams S; University Hospital Southampton NHS Foundation Trust, Southampton, UK.
  • Watson A; University Hospital Southampton NHS Foundation Trust, Southampton, UK.
  • Fitzpatrick P; Faculty of Medicine, University of Southampton, Southampton, UK.
  • Landers D; University of Manchester, Cancer Biomarker Centre, Cancer Research UK Manchester Institute, Manchester, UK.
  • Wilkinson T; Digital Experimental Cancer Medicine Team, University of Manchester, Cancer Biomarker Centre, Cancer Research UK Manchester Institute, Alderley Edge, Cheshire, UK.
BMJ Open ; 12(2): e050331, 2022 02 15.
Article em En | MEDLINE | ID: mdl-35168965
OBJECTIVES: COVID-19 is a heterogeneous disease, and many reports have described variations in demographic, biochemical and clinical features at presentation influencing overall hospital mortality. However, there is little information regarding longitudinal changes in laboratory prognostic variables in relation to disease progression in hospitalised patients with COVID-19. DESIGN AND SETTING: This retrospective observational report describes disease progression from symptom onset, to admission to hospital, clinical response and discharge/death among patients with COVID-19 at a tertiary centre in South East England. PARTICIPANTS: Six hundred and fifty-one patients treated for SARS-CoV-2 between March and September 2020 were included in this analysis. Ethical approval was obtained from the HRA Specific Review Board (REC 20/HRA/2986) for waiver of informed consent. RESULTS: The majority of patients presented within 1 week of symptom onset. The lowest risk patients had low mortality (1/45, 2%), and most were discharged within 1 week after admission (30/45, 67%). The highest risk patients, as determined by the 4C mortality score predictor, had high mortality (27/29, 93%), with most dying within 1 week after admission (22/29, 76%). Consistent with previous reports, most patients presented with high levels of C reactive protein (CRP) (67% of patients >50 mg/L), D-dimer (98%>upper limit of normal (ULN)), ferritin (65%>ULN), lactate dehydrogenase (90%>ULN) and low lymphocyte counts (81%
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans País/Região como assunto: Europa Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans País/Região como assunto: Europa Idioma: En Ano de publicação: 2022 Tipo de documento: Article