Clinical characteristics of children and young people admitted to hospital with covid-19 in United Kingdom: prospective multicentre observational cohort study

  1. Olivia V Swann
  2. Karl A Holden
  3. Lance Turtle
  4. Louisa Pollock
  5. Cameron J Fairfield
  6. Thomas M Drake
  7. Sohan Seth
  8. Conor Egan
  9. Hayley E Hardwick
  10. Sophie Halpin
  11. Michelle Girvan
  12. Chloe Donohue
  13. Mark Pritchard
  14. Latifa B Patel
  15. Shamez Ladhani
  16. Louise Sigfrid
  17. Ian P Sinha
  18. Piero L Olliaro
  19. Jonathan S Nguyen-Van-Tam
  20. Peter W Horby
  21. Laura Merson
  22. Gail Carson
  23. Jake Dunning
  24. Peter J M Openshaw
  25. J Kenneth Baillie
  26. Ewen M Harrison
  27. Annemarie B Docherty
  28. Malcolm G Semple

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Abstract

Objective

To characterise the clinical features of children and young people admitted to hospital with laboratory confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the UK and explore factors associated with admission to critical care, mortality, and development of multisystem inflammatory syndrome in children and adolescents temporarily related to coronavirus disease 2019 (covid-19) (MIS-C).

Design

Prospective observational cohort study with rapid data gathering and near real time analysis.

Setting

260 hospitals in England, Wales, and Scotland between 17 January and 3 July 2020, with a minimum follow-up time of two weeks (to 17 July 2020).

Participants

651 children and young people aged less than 19 years admitted to 138 hospitals and enrolled into the International Severe Acute Respiratory and emergency Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK study with laboratory confirmed SARS-CoV-2.

Main outcome measures

Admission to critical care (high dependency or intensive care), in-hospital mortality, or meeting the WHO preliminary case definition for MIS-C.

Results

Median age was 4.6 (interquartile range 0.3-13.7) years, 35% (225/651) were under 12 months old, and 56% (367/650) were male. 57% (330/576) were white, 12% (67/576) South Asian, and 10% (56/576) black. 42% (276/651) had at least one recorded comorbidity. A systemic mucocutaneous-enteric cluster of symptoms was identified, which encompassed the symptoms for the WHO MIS-C criteria. 18% (116/632) of children were admitted to critical care. On multivariable analysis, this was associated with age under 1 month (odds ratio 3.21, 95% confidence interval 1.36 to 7.66; P=0.008), age 10-14 years (3.23, 1.55 to 6.99; P=0.002), and black ethnicity (2.82, 1.41 to 5.57; P=0.003). Six (1%) of 627 patients died in hospital, all of whom had profound comorbidity. 11% (52/456) met the WHO MIS-C criteria, with the first patient developing symptoms in mid-March. Children meeting MIS-C criteria were older (median age 10.7 (8.3-14.1) v 1.6 (0.2-12.9) years; P<0.001) and more likely to be of non-white ethnicity (64% (29/45) v 42% (148/355); P=0.004). Children with MIS-C were five times more likely to be admitted to critical care (73% (38/52) v 15% (62/404); P<0.001). In addition to the WHO criteria, children with MIS-C were more likely to present with fatigue (51% (24/47) v 28% (86/302); P=0.004), headache (34% (16/47) v 10% (26/263); P<0.001), myalgia (34% (15/44) v 8% (21/270); P<0.001), sore throat (30% (14/47) v (12% (34/284); P=0.003), and lymphadenopathy (20% (9/46) v 3% (10/318); P<0.001) and to have a platelet count of less than 150 × 10 9 /L (32% (16/50) v 11% (38/348); P<0.001) than children who did not have MIS-C. No deaths occurred in the MIS-C group.

Conclusions

Children and young people have less severe acute covid-19 than adults. A systemic mucocutaneous-enteric symptom cluster was also identified in acute cases that shares features with MIS-C. This study provides additional evidence for refining the WHO MIS-C preliminary case definition. Children meeting the MIS-C criteria have different demographic and clinical features depending on whether they have acute SARS-CoV-2 infection (polymerase chain reaction positive) or are post-acute (antibody positive).

Study registration

ISRCTN66726260.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.07.14.20153320: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Collection of this routine anonymised demographic and clinical data from medical records did not require consent in England and Wales. In Scotland, a waiver for consent was obtained from the Public Benefit and Privacy Panel.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data were collected from healthcare records onto the case report forms through a secure online database, REDCap (Research Electronic Data Capture, Vanderbilt University, hosted by the University of Oxford (UK)).
    REDCap
    suggested: (REDCap, RRID:SCR_003445)
    Statistical analyses were performed using R (R Core Team version 3.6.3, Vienna, Austria) with packages including tidyverse, finalfit lubridate, ggplot2, gplot, dendextend and UpSetR.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    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:
    Strengths and limitations of this study: This study is unique in that data for patients with laboratory-confirmed covid-19 were collected prospectively and throughout the admission. The ISARIC WHO CCP-UK study had previously been activated in 2016 and 2018 for cases of Middle East Respiratory Syndrome (MERS) and monkeypox so was prepared for the SARS-CoV-2 pandemic, allowing swift activation. Consequently, in addition to reporting the clinical characteristics, risk factors and outcomes of covid-19 in children, this dataset provided a unique opportunity to objectively monitor the emergence and progression of a novel multisystem inflammatory syndrome in the UK, whilst minimising recall bias. The first patient meeting the criteria for MIS-C was identified on 19 March 2020, whilst the first published cases were reported on 6 May 2020 [8]. Comparison with overall covid-19 cases confirms the sporadic occurrence of the MIS-C throughout the first peak of the covid-19 pandemic in the UK. In contrast to previous reports, our analysis was limited only to children admitted with laboratory confirmed SARS-CoV-2 which allowed us to clearly define the picture of covid-19 in children and reduce confounding with other potential causes. The ISARIC WHO CCP-UK database is estimated to represent 53% of covid-19 hospitalisations across England, Wales and Scotland. It is therefore susceptible to selection bias, particularly as tertiary centres with critical care units and specialist children’s hospi...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    ISRCTN66726260NANA

    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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    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.

  2. Version published to 10.1136/bmj.m3249
  3. ScreenIT

    SciScore for 10.1101/2020.07.14.20153320: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementCollection of this routine anonymised demographic and clinical data from medical records did not require consent in England and Wales. In Scotland, a waiver for consent was obtained from the Public Benefit and Privacy Panel.Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variableThe cohort was predominantly male (57%) and of White ethnicity (56%) with most (57%) children having no known comorbidities.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data were collected from healthcare records onto the case report forms through a secure online database, REDCap (Research Electronic Data Capture, Vanderbilt University, hosted by the University of Oxford (UK)).
    REDCap
    suggested: (REDCap, SCR_003445)
    Statistical analyses were performed using R (R Core Team version 3.6.3, Vienna, Austria) with packages including tidyverse, finalfit lubridate, ggplot2, gplot, dendextend and UpSetR.
    ggplot2
    suggested: (ggplot2, SCR_014601)
    Consequently, there is a less information regarding ethnicity, comorbidities, clinical and laboratory findings in children with SARS-CoV-2. A Multisystem Inflammatory Syndrome in Children and Adolescents (MIS-C) temporally associated with SARS-CoV-2 has been widely reported, however all reports to date arise from retrospective cases series which are vulnerable to recall bias.
    SARS-CoV-2
    suggested: (Sino Biological Cat# 40143-R019, AB_2827973)

    Data from additional tools added to each annotation on a weekly basis.

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2020.07.14.20153320v1 on medRxiv