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Decline of SARS-CoV-2 specific IgG, IgM and IgA in convalescent COVID-19 patients within 100 days after hospital discharge
Preprint
in English
| medRxiv
| ID: ppmedrxiv-20175950
Journal article
A scientific journal published article is available and is probably based on this preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
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A scientific journal published article is available and is probably based on this preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
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ABSTRACT
Monitoring the levels of SARS-CoV-2 specific antibodies such as IgG, M and A in COVID-19 patient is an alternative method for diagnosing SARS-CoV-2 infection and an simple way to monitor immune responses in convalescent patients and after vaccination. Here, we assessed the levels of SARS-CoV-2 RBD specific antibodies in twenty-seven COVID-19 convalescent patients over 28-99 days after hospital discharge. Almost all patient who had severe or moderate COVID-19 symptoms and a high-level of IgG during the hospitalization showed a significant reduction at revisit. The remaining patients who had a low-level IgG during hospitalization stayed low at revisit. As expected, IgM levels in almost all convalescent patients reduced significantly or stayed low at revisit. The RBD-specific IgA levels were also reduced significantly at revisit. We also attempted to estimate decline rates of virus-specific antibodies using a previously established exponential decay model of antibody kinetics after infection. The predicted days when convalescent patients RBD-specific IgG reaches to an undetectable level are approximately 273 days after hospital discharge, while the predicted decay times are 150 days and 108 days for IgM and IgA, respectively. This investigation and report will aid current and future studies to develope SARS-CoV-2 vaccines that are potent and long-lasting.
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Full text:
Available
Collection:
Preprints
Database:
medRxiv
Type of study:
Prognostic study
Language:
English
Year:
2020
Document type:
Preprint