ANTIBODY RESPONSE TO COVID-19 INFECTION- CLINICAL VARIABLES AT PLAY

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

Background

The current COVID19 pandemic began in December 2019 and rapidly expanded to become a global pandemic. The COVID 19 presents multitude of clinical disorders, ranges from asymptomatic infection to severe disease, which can accompanied by multisystem failure leading to death. The immune response to SARS CoV 2 is understood to involve all the components of the system that together causes viral elimination and recovery from the infection. However, such immune responses implicated in the disease has varied presentation ranging from mild to a severe form, which appears to hinge on the loss of the immune regulation between protective and altered responses. In this study, we want to unravel this association of immune responses to various clinical variables, which might have a major role to play, while generating the immune response. The objective was to test this hypothesis in our settings and comparing the results of serologic tests from a group of COVID 19 patients and will analyzed the disease severity in comparison.

Methods

Testing for SARS COV2 IgG Antibody was done with chemiluminescent assay on the Ortho Clinical Diagnostic’s (OCD) Vitros 5600 platform.

Results

A total of 106 COVID 19 patients were included in this study, of whom 61 were male and 45 were female. Their mean age was 43.7 years (range 17–83) and the median interval between initial symptom onset and sample collection was 12.33 days. Eighty patients (82%) had mild or moderate symptoms and twenty-six patients (18%) had severe symptoms. The antibody titers were positive in 99 patients (93%) and were found negative in 7 patients (7%). When comparing patients with mild/moderate symptoms and patients with severe/critical diseases, no statistically significant difference was observed between their gender ratios (P = 0.373) and age composition (P = 0.224).

Conclusions

The data presented in this research study did not find any statistical significance between SARS CoV 2 IgG antibody levels with COVID 19 disease severity, duration of symptoms, age, gender, and length of convalescence.

Article activity feed

  1. SciScore for 10.1101/2020.11.20.20234500: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethical approval: The study was approved by the Institution Review Board (IRB) (ref. no. 2020003).
    Consent: The written informed consent was waived by the IRB, since the study was retrospective in nature.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.


    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: 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.