Risk factors for severe disease in patients admitted with COVID-19 to a hospital in London, England: a retrospective cohort study

  1. J. W. Goodall
  2. T. A. N. Reed
  3. M. Ardissino
  4. P. Bassett
  5. A. M. Whittington
  6. D. L. Cohen
  7. N. Vaid

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Abstract

COVID-19 has caused a major global pandemic and necessitated unprecedented public health restrictions in almost every country. Understanding risk factors for severe disease in hospitalized patients is critical as the pandemic progresses.

This observational cohort study aimed to characterize the independent associations between the clinical outcomes of hospitalized patients and their demographics, comorbidities, blood tests and bedside observations. All patients admitted to Northwick Park Hospital, London, United Kingdom between 12 March and 15 April 2020 with COVID-19 were retrospectively identified. The primary outcome was death. Associations were explored using Cox proportional hazards modelling.

The study included 981 patients. The mortality rate was 36.0%. Age (adjusted hazard ratio (aHR) 1.53), respiratory disease (aHR 1.37), immunosuppression (aHR 2.23), respiratory rate (aHR 1.28), hypoxia (aHR 1.36), Glasgow Coma Score <15 (aHR 1.92), urea (aHR 2.67), alkaline phosphatase (aHR 2.53), C-reactive protein (aHR 1.15), lactate (aHR 2.67), platelet count (aHR 0.77) and infiltrates on chest radiograph (aHR 1.89) were all associated with mortality.

These important data will aid clinical risk stratification and provide direction for further research.

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  1. ScreenIT

    SciScore for 10.1101/2020.09.24.20200337: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study had National Research Ethics approval (REC 20/NW/0218, IRAS 282630) and was carried out in accordance with the Declaration of Helsinki and the principles of Good Clinical Practice. Variables: Data were collected from electronic patient records and entered into a securely stored database.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    STATA codes can be obtained from the authors.
    STATA
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    A limitation of this study is that for the purpose of the time to event analyses, it had to be assumed that those who had clinically improved and were discharged prior to censoring remained alive until the censoring date. Although it is possible that some of these patients died post-discharge, this risk was minimized by ensuring that patients were screened for readmission and by ensuring that none of the cohort were discharged for community end-of-life care. A second limitation is that a significant minority of patients (157/981) did not have an ethnicity documented. The majority of these patients had opted not to have their ethnicity recorded. In conclusion, this large cohort study included all patients who were hospitalized with COVID-19 during the study period. It was conducted in an area of London with high levels of ethnic diversity [15]. When considering the high mortality among those hospitalized with COVID-19, early identification of those most susceptible to a severe disease is of paramount importance. This study found that predominantly respiratory features such as respiratory rate, oxygen saturations, infiltrates on chest radiograph and a history of respiratory disease were associated with severe disease. Comparatively few non-respiratory features were also identified as being associated with severe disease (age, reduced GCS and immunosuppression) along with a number of biochemical markers. For this new disease, understanding at the point of admission which patient...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  2. Version published to 10.1101/2020.09.24.20200337v1 on medRxiv
  3. Version published to 10.1017/s0950268820002472