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ORIGINAL RESEARCH article

Front. Cell. Infect. Microbiol.
Sec. Clinical Microbiology
Volume 14 - 2024 | doi: 10.3389/fcimb.2024.1477585

Development of a prediction nomogram for IgG levels among asymptomatic or mild patients with COVID-19

Provisionally accepted
Jianying Yi Jianying Yi 1Zhili Liu Zhili Liu 2Xi Cao Xi Cao 1Lili Pi Lili Pi 1Chunlei Zhou Chunlei Zhou 1Hong Mu Hong Mu 1*
  • 1 Tianjin First Central Hospital, Tianjin, China
  • 2 Tianjin Third Central Hospital, Tianjin, China

The final, formatted version of the article will be published soon.

    Objective: COVID-19 has evolved into a seasonal coronavirus disease, characterized by prolonged infection duration and repeated infections, significantly increasing the risk of patients developing long COVID. Our research focused on the immune responses in asymptomatic and mild cases, particularly the critical factors influencing serum immunoglobulin G (IgG) levels and their predictive value. Methods: We conducted a retrospective analysis on data from 1939 asymptomatic or mildly symptomatic COVID-19 patients hospitalized between September 2022 and June 2023. Spearman methods were used to test the correlation between serum IgG and age, immunoglobulin M (IgM), procalcitonin (PCT), interleukin-6 (IL-6), nucleic acid conversion time, and BMI. Univariate and multivariate logistic regression analyses identified independent key factors influencing serum IgG levels, which were integrated and visualized in a nomogram. Finally, receiver operating characteristic (ROC) curves were plotted to predict the model's diagnostic performance by calculating the AUC. Results: Mild patients showed higher levels of IgG, IgM, and longer nucleic acid conversion times than asymptomatic patients, and a lower proportion of them had received ≥ 3 COVID-19 vaccine doses. Serum IgG was positively correlated with serum IgM and negatively correlated with age, PCT, IL-6, and BMI. Notably, it showed a moderate negative correlation with nucleic acid conversion time (r = -0.578, P < 0.001). Logistic regression resultsshowed that younger age, lower IL-6 levels, ≥ 3 doses of vaccine, and no comorbidities were independent predictors of serum IgG levels ≥ 21.08 g/L. We used age, IL-6 levels, vaccine doses, and comorbidities to create a nomogram for predicting serum IgG levels, with the area under the ROC curve reaching 0.772. Conclusion: Age, IL-6 levels, vaccination status, and comorbidities were independent predictors of serum IgG levels in asymptomatic or mild COVID-19 patients, facilitating risk stratification and clinical decision-making. Notably, receiving ≥3 doses of the COVID-19 vaccine was the most beneficial factor for elevated serum IgG levels.

    Keywords: SARS-CoV-2, Long Covid, IgG, IL-6, Vaccine, Comorbidity

    Received: 08 Aug 2024; Accepted: 21 Nov 2024.

    Copyright: © 2024 Yi, Liu, Cao, Pi, Zhou and Mu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Hong Mu, Tianjin First Central Hospital, Tianjin, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.