Insights from an N3C RECOVER EHR-based cohort study characterizing SARS-CoV-2 reinfections and Long COVID.


Journal

Communications medicine
ISSN: 2730-664X
Titre abrégé: Commun Med (Lond)
Pays: England
ID NLM: 9918250414506676

Informations de publication

Date de publication:
11 Jul 2024
Historique:
received: 09 01 2023
accepted: 31 05 2024
medline: 12 7 2024
pubmed: 12 7 2024
entrez: 11 7 2024
Statut: epublish

Résumé

Although the COVID-19 pandemic has persisted for over 3 years, reinfections with SARS-CoV-2 are not well understood. We aim to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection. We use an electronic health record study cohort of over 3 million patients from the National COVID Cohort Collaborative as part of the NIH Researching COVID to Enhance Recovery Initiative. We calculate summary statistics, effect sizes, and Kaplan-Meier curves to better understand COVID-19 reinfections. Here we validate previous findings of reinfection incidence (6.9%), the occurrence of most reinfections during the Omicron epoch, and evidence of multiple reinfections. We present findings that the proportion of Long COVID diagnoses is higher following initial infection than reinfection for infections in the same epoch. We report lower albumin levels leading up to reinfection and a statistically significant association of severity between initial infection and reinfection (chi-squared value: 25,697, p-value: <0.0001) with a medium effect size (Cramer's V: 0.20, DoF = 3). Individuals who experienced severe initial and first reinfection were older in age and at a higher mortality risk than those who had mild initial infection and reinfection. In a large patient cohort, we find that the severity of reinfection appears to be associated with the severity of initial infection and that Long COVID diagnoses appear to occur more often following initial infection than reinfection in the same epoch. Future research may build on these findings to better understand COVID-19 reinfections. More than three years after the start of the COVID-19 pandemic, individuals are frequently reporting multiple COVID-19 infections. However, these reinfections remain poorly understood. Here, we investigate COVID-19 reinfections in a large electronic health record cohort of over 3 million patients. We use data summary techniques and statistical tests to characterize reinfections and their relationships with disease severity, biomarkers, and Long COVID. We find that individuals with severe initial infection are more likely to experience severe reinfection, that some protein levels are lower, leading to reinfection, and that a lower proportion of individuals are diagnosed with Long COVID following reinfection than initial infection. Our work highlights the prevalence and impact of reinfections and suggests the need for further research.

Sections du résumé

BACKGROUND BACKGROUND
Although the COVID-19 pandemic has persisted for over 3 years, reinfections with SARS-CoV-2 are not well understood. We aim to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection.
METHODS METHODS
We use an electronic health record study cohort of over 3 million patients from the National COVID Cohort Collaborative as part of the NIH Researching COVID to Enhance Recovery Initiative. We calculate summary statistics, effect sizes, and Kaplan-Meier curves to better understand COVID-19 reinfections.
RESULTS RESULTS
Here we validate previous findings of reinfection incidence (6.9%), the occurrence of most reinfections during the Omicron epoch, and evidence of multiple reinfections. We present findings that the proportion of Long COVID diagnoses is higher following initial infection than reinfection for infections in the same epoch. We report lower albumin levels leading up to reinfection and a statistically significant association of severity between initial infection and reinfection (chi-squared value: 25,697, p-value: <0.0001) with a medium effect size (Cramer's V: 0.20, DoF = 3). Individuals who experienced severe initial and first reinfection were older in age and at a higher mortality risk than those who had mild initial infection and reinfection.
CONCLUSIONS CONCLUSIONS
In a large patient cohort, we find that the severity of reinfection appears to be associated with the severity of initial infection and that Long COVID diagnoses appear to occur more often following initial infection than reinfection in the same epoch. Future research may build on these findings to better understand COVID-19 reinfections.
More than three years after the start of the COVID-19 pandemic, individuals are frequently reporting multiple COVID-19 infections. However, these reinfections remain poorly understood. Here, we investigate COVID-19 reinfections in a large electronic health record cohort of over 3 million patients. We use data summary techniques and statistical tests to characterize reinfections and their relationships with disease severity, biomarkers, and Long COVID. We find that individuals with severe initial infection are more likely to experience severe reinfection, that some protein levels are lower, leading to reinfection, and that a lower proportion of individuals are diagnosed with Long COVID following reinfection than initial infection. Our work highlights the prevalence and impact of reinfections and suggests the need for further research.

Autres résumés

Type: plain-language-summary (eng)
More than three years after the start of the COVID-19 pandemic, individuals are frequently reporting multiple COVID-19 infections. However, these reinfections remain poorly understood. Here, we investigate COVID-19 reinfections in a large electronic health record cohort of over 3 million patients. We use data summary techniques and statistical tests to characterize reinfections and their relationships with disease severity, biomarkers, and Long COVID. We find that individuals with severe initial infection are more likely to experience severe reinfection, that some protein levels are lower, leading to reinfection, and that a lower proportion of individuals are diagnosed with Long COVID following reinfection than initial infection. Our work highlights the prevalence and impact of reinfections and suggests the need for further research.

Identifiants

pubmed: 38992084
doi: 10.1038/s43856-024-00539-2
pii: 10.1038/s43856-024-00539-2
doi:

Types de publication

Journal Article

Langues

eng

Pagination

129

Subventions

Organisme : U.S. Department of Health & Human Services | National Institutes of Health (NIH)
ID : OTA OT2HL161847

Informations de copyright

© 2024. The Author(s).

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Auteurs

Emily Hadley (E)

RTI International, Durham, NC, USA. ehadley@rti.org.

Yun Jae Yoo (YJ)

Emory University, Atlanta, GA, USA.

Saaya Patel (S)

Stony Brook University, Stony Brook, NY, USA.

Andrea Zhou (A)

University of Virginia, Charlottesville, VA, USA.

Bryan Laraway (B)

University of North Carolina, Chapel Hill, NC, USA.

Rachel Wong (R)

Stony Brook University, Stony Brook, NY, USA.

Alexander Preiss (A)

RTI International, Durham, NC, USA.

Rob Chew (R)

RTI International, Durham, NC, USA.

Hannah Davis (H)

Patient Led Research Collaborative (PLRC), Calabasas, CA, USA.

M Daniel Brannock (MD)

RTI International, Durham, NC, USA.

Christopher G Chute (CG)

Johns Hopkins University, Baltimore, MD, USA.

Emily R Pfaff (ER)

University of North Carolina, Chapel Hill, NC, USA.

Johanna Loomba (J)

University of Virginia, Charlottesville, VA, USA.

Melissa Haendel (M)

University of North Carolina, Chapel Hill, NC, USA.

Elaine Hill (E)

University of Rochester Medical Center, Rochester, NY, USA.

Richard Moffitt (R)

Emory University, Atlanta, GA, USA.

Classifications MeSH