Clinical Determinants and Predictors for Prognosis of SARS-CoV-2 Infected Pediatric Patients in Saudi Arabia

  1. Khalid Mohamed Adam
  2. Bahaeldin K. Elamin
  3. Jaber A. Alfaifi
  4. Mohammed Abbas

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Abstract

Background

The significant variations in clinical characteristics and outcomes of COVID-19 that range from asymptomatic to severe fatal illness entail searching for potential prognostic determinants to help predict the disease course and early detection of patients at risk of developing life-threatening complications. Although children are less commonly infected by SARS-CoV-2 than their adult counterparts, and their symptoms are generally milder, a severe type of COVID-19 cannot be precluded.

Methods

At first, demographic, clinical, laboratory measurement data, and outcomes for 26 COVID-19 infected children of less than 12 years of age, admitted to King Abdallah Hospital, Bisha, Saudi Arabia, were retrieved from the electronic medical records for the observational retrospective study.

Later, electronic and manual database searches were carried out for pediatric severe COVID-19-related articles. The relevant data from 20 eligible studies and the present retrospective study were analyzed to assess the association of demographic characteristics and comorbidities with COVID-19 severity.

Results

In the retrospective study, 5 (19%) of the children presented with severe symptoms admitted to PICU, 18 (69%) presented with cough, 5 (19%) with diarrhea, 7 (27%) with underlying comorbidities, 4 (15%) with respiratory illnesses, 3 (12%) with cardiovascular diseases and 2 (8%) were obese. None of the patient characteristics showed any significant association with COVID-19 severity.

Of the 21 studies selected for meta-analyses, 14 studies were included in the analysis of the association between any comorbidity and disease severity, resulting in OR: 2.69, 95%CI: 1.38 – 5.26, P < 0.05, for analysis of the association between cardiovascular comorbidities and disease severity 14 studies were included giving OR: 4.06, 95%CI: 1.86 – 8.87, P < 0.05, for analysis of the association between respiratory comorbidity and disease severity 15 studies were included giving OR: 2.05, 95%CI: 1.54 – 2.74, P < 0.05, for analysis of the association between obesity and disease severity 10 studies were included, giving OR: 2.48, 95%CI: 1.16 – 5.32, P < 0.05, for analysis of the association between age <10 years old and diseases severity, 16 studies were included, giving OR: 0.80, 95%CI: 0.65 – 0.97, P < 0.05, and for analysis of the association between female gender and disease severity, 19 studies were included, giving OR: 0.83, 95%CI: 0.59 – 1.18, P > 0.05.

Conclusion

It can be concluded that COVID-19 pediatric patients with underlying comorbidities, being cardiovascular, respiratory, or obesity, are at high risk of developing severe illness, and young age has a protective role against the disease severity.

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  1. ScreenIT

    SciScore for 10.1101/2021.07.28.21261284: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Study design and setting: In this retrospective, observational study, that ethically and technically approved by the institutional review board of deanship of scientific research, University of Bisha, the clinical, demographic, and comorbidity data on presentation, treatment, and outcomes of all children aged less than 12 years admitted to King Abdalla Hospital, Bisha, Saudi Arabia, between March 1, 2020, and April 28, 2021, with a laboratory-confirmed SARS-CoV-2 infection, retrieved from the electronic medical record (EMR).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Medline, Embase, Web of Science, and ProQuest databases were queried for records published from January 1, 2020, until May 1, 2021, using the combination of the following terms: “COVID-19”, “SARS-CoV-2”, “novel
    Medline
    suggested: (MEDLINE, RRID:SCR_002185)
    Embase
    suggested: (EMBASE, RRID:SCR_001650)
    ProQuest
    suggested: (ProQuest, RRID:SCR_006093)
    BioRxiv, MedRxi, Open Grey, and Open Science Framework (
    BioRxiv
    suggested: (bioRxiv, RRID:SCR_003933)
    Results were considered statistically significant at P < 0.05 using SPSS software (IBM SPSS Statistics for Windows, Version 25.0.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    The meta-analysis was performed using Prometa3 software.
    Prometa3
    suggested: None

    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:
    Although we rigorously analyzed data from many relevant COVID-19 studies, our study suffered some limitations, including heterogeneity across studies included for exploring the association of disease severity with any comorbidity, cardiovascular disease, and female gender but not age and respiratory tract diseases. This heterogeneity is believed to have affected the plausibility of some of our results. This study also focused retrospectively on specific comorbidities only, which entails more extensive prospective studies to establish the causality between severe COVID-19 and other comorbidities such as gastrointestinal, renal, genetic, and neurological diseases.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.07.28.21261284 on medRxiv