Clinical manifestations of children with COVID‐19: A systematic review

  1. Tiago H. de Souza
  2. José A. Nadal
  3. Roberto J. N. Nogueira
  4. Ricardo M. Pereira
  5. Marcelo B. Brandão

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Abstract

Background

The coronavirus disease 2019 (COVID‐19) outbreak is an unprecedented global public health challenge, leading to thousands of deaths every day worldwide. Despite the epidemiological importance, clinical patterns of children with COVID‐19 remain unclear. The aim of this study was to describe the clinical, laboratorial, and radiological characteristics of children with COVID‐19.

Methods

The Medline database was searched between December 1st 2019 and April 6th 2020. No language restrictions were applied. Inclusion criteria were (a) studied patients younger than 18 years old; (b) presented original data from cases of COVID‐19 confirmed by reverse‐transcription polymerase chain reaction; and (c) contained descriptions of clinical manifestations, laboratory tests, or radiological examinations.

Results

A total of 38 studies (1124 cases) were included. From all the cases, 1117 had their severity classified: 14.2% were asymptomatic, 36.3% were mild, 46.0% were moderate, 2.1% were severe, and 1.2% were critical. The most prevalent symptom was fever (47.5%), followed by cough (41.5%), nasal symptoms (11.2%), diarrhea (8.1%), and nausea/vomiting (7.1%). One hundred forty‐five (36.9%) children were diagnosed with pneumonia and 43 (10.9%) upper airway infections were reported. Reduced lymphocyte count was reported in 12.9% of cases. Abnormalities in computed tomography were reported in 63.0% of cases. The most prevalent abnormalities reported were ground‐glass opacities, patchy shadows, and consolidations. Only one death was reported.

Conclusions

Clinical manifestations of children with COVID‐19 differ widely from adult cases. Fever and respiratory symptoms should not be considered a hallmark of COVID‐19 in children.

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  1. Version published to 10.1002/ppul.24885
  2. ScreenIT

    SciScore for 10.1101/2020.04.01.20049833: (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

    Software and Algorithms
    SentencesResources
    This review was performed in accordance with the Preferred Reporting Items for Systematic and Meta-Analysis (PRISMA) statement.7,8 The Medline database was searched using the following search strategy: ((((covid-19) OR coronavirus) OR SARS-CoV-2)) AND (((((((pediatrics) OR children) OR neonates) OR child) OR neonate) OR infant) OR infants).
    Medline
    suggested: (MEDLINE, RRID:SCR_002185)

    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:
    Our study has some limitations. Firstly, data from the same patient may have been presented in more than one included study. Secondly, the majority of data are from China, and may not be generalized for other populations.

    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

    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.

  3. Version published to 10.1101/2020.04.01.20049833v2 on medRxiv
  4. Version published to 10.1101/2020.04.01.20049833v1 on medRxiv