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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

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    Authors
    Burke, H.
    Freeman, A.
    O'Regan, P.
    Wysocki, Oskar
    Freitas, Andre
    Dushianthan, A.
    Celinski, M.
    Batchelor, J.
    Phan, H.
    Borca, F.
    Sheard, N.
    Williams, S.
    Watson, A.
    Fitzpatrick, Paul
    Landers, Donal
    Wilkinson, T.
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    Affiliation
    Faculty of Medicine, University of Southampton, Southampton, UK. Faculty of Medicine, University of Southampton, Southampton, UK a.freeman@soton.ac.uk. Digital Experimental Cancer Medicine Team, Cancer Biomarker Centre, Cancer Research UK Manchester Institute, The University of Manchester, Manchester, UK. Clinical Informatics Research Unit, University of Southampton Faculty of Medicine, Southampton, UK. University of Southampton, Southampton, UK. Institute for Life Sciences, University of Southampton, Southampton, UK. University Hospital Southampton NHS Foundation Trust, Southampton, UK. University of Manchester, Cancer Biomarker Centre, Cancer Research UK Manchester Institute, Manchester, UK. Digital Experimental Cancer Medicine Team, University of Manchester, Cancer Biomarker Centre, Cancer Research UK Manchester Institute, Alderley Edge, Cheshire, UK.
    Issue Date
    2022
    
    Metadata
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    Abstract
    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%<lower limit of normal (LLN)). Increases in platelet counts and decreases in CRP, neutrophil:lymphocyte ratio (p<0.001), lactate dehydrogenase, neutrophil counts, urea and white cell counts (all p<0.01) were each associated with discharge. Conclusions Serial measurement of routine blood tests may be a useful prognostic tool for monitoring treatment response in hospitalised patients with COVID-19. Changes in other biochemical parameters often included in a ‘COVID-19 bundle’ did not show significant association with outcome, suggesting there may be limited clinical benefit of serial sampling. This may have direct clinical utility in the context of escalating healthcare costs of the pandemic.
    Citation
    Burke H, Freeman A, O’Regan P, Wysocki O, Freitas A, Dushianthan A, et al. Biomarker identification using dynamic time warping analysis: a longitudinal cohort study of patients with COVID-19 in a UK tertiary hospital [Internet]. Vol. 12, BMJ Open. BMJ; 2022. p. e050331.
    Journal
    BMJ Open
    URI
    http://hdl.handle.net/10541/625135
    DOI
    10.1136/bmjopen-2021-050331
    PubMed ID
    35168965
    Additional Links
    https://dx.doi.org/10.1136/bmjopen-2021-050331
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1136/bmjopen-2021-050331
    Scopus Count
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