Cohort profile: Preliminary experience of 500 COVID-19 postive cases at a South West London District General Hospital

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

This retrospective cohort analysis, reports the demographic data and early outcome of the first 500 patients who were admitted to a District General Hospital in South West London, UK and tested positive to COVID-19. The patients were admitted between 10 January and 10 April 2020; with the first COVID-19 positive diagnosis on 6 March. A surge in admissions started around the 15 March and peaked at the beginning of April.

56.8% of the admissions were male and 43.2% were female. The average age of the 500 admissions was 69.32 years (SD 19.23 years, range 1 week to 99.21 years). By the morning of 14 April 2020, 199 patients had been discharged (Female 89, Male 111), 163 patients had died (female 61, male 102) and 131 remained as in-patients (female 66, male 71).

Fewer than one in twenty deaths occurred in patients below the age of 50 years, in either gender. Mortality rose dramatically, for both genders, after the age of sixty with males being almost twice as vulnerable to dying, as females, during the 7 th decade. Males older than their mid-fifties were more likely to die than leave hospital. The same applied to females beyond their mid seventies. We did not see any evidence of a poorer outcome associated with a lower decile for Index of Multiple Deprivation or convincing evidence that any Ethnic minority groups were more likely to die than the White subgroups. When compared to the equivalent medical conditions, normally treated in the early spring, COVID-19 has an increased mortality, adversely affecting more men and an older population.

The mean duration from admission to discharge was 11.29 days (SD 11.50 days). For admission to death, the mean interval was 11.72 days (SD 11.05 days). 62 of the 500 admissions required ventilator support. Of this subgroup, 71% were male and 29% were female. By the morning of the 14 April, no female over the age of 60 had left the intensive care unit alive and no male over the age of 50 had left the intensive care unit alive. At this time-point, 1.2% of the 500 admitted patients had returned alive from the intensive care units, following a period of ventilator support. This figure will rise if prolonged ventilator and renal support proves effective.

While only providing a snapshot of a relatively small number of patients, reviewed over a short time period, from a small geographic area, the data supports the view that the younger members of society are less vulnerable to the adverse sequelae of COVID-19 infection and that any return to normal work and social activities should be considered initially for the individuals who are less than 40-50 years of age. There is an ongoing need for analyses on larger patient cohorts using both demographic and detailed clinical data.

Article activity feed

  1. SciScore for 10.1101/2020.04.28.20075119: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: Thank you for sharing your data.


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.
    • Thank you for including a protocol registration statement.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.