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437. Does “Long COVID” Resolve by One Year in U.S. Military Health System Beneficiaries?
BACKGROUND: The long-term duration of post COVID condition (PCC, “Long COVID”) remains unclear. In this study, we estimated the risk of healthcare encounters in Military Health System (MHS) beneficiaries for the 12 months post SARS-CoV-2 diagnosis, adjusting for prior healthcare use, and compared to...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10679074/ http://dx.doi.org/10.1093/ofid/ofad500.507 |
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author | Richard, Stephanie A Byrne, Celia Rusiecki, Jennifer Berjohn, Catherine Lalani, Tahaniyat Smith, Alfred Mody, Rupal Ganesan, Anuradha Colombo, Rhonda Lindholm, David Morris, Michael Huprikar, Nikhil Colombo, Christopher Schofield, Christina Jones, Milissa U Mende, Katrin Saunders, David Livezey, Jeffrey Chang, David Ewers, Evan Maldonado, Carlos Scher, Ann Fries, Anthony C Maves, Ryan C Epsi, Nusrat J Schmidt, Kat Edwards, Margaret Sanchez Simons, Mark Tribble, David R Tribble, David R O’Connell, Robert Agan, Brian Burgess, Timothy Pollett, Simon |
author_facet | Richard, Stephanie A Byrne, Celia Rusiecki, Jennifer Berjohn, Catherine Lalani, Tahaniyat Smith, Alfred Mody, Rupal Ganesan, Anuradha Colombo, Rhonda Lindholm, David Morris, Michael Huprikar, Nikhil Colombo, Christopher Schofield, Christina Jones, Milissa U Mende, Katrin Saunders, David Livezey, Jeffrey Chang, David Ewers, Evan Maldonado, Carlos Scher, Ann Fries, Anthony C Maves, Ryan C Epsi, Nusrat J Schmidt, Kat Edwards, Margaret Sanchez Simons, Mark Tribble, David R Tribble, David R O’Connell, Robert Agan, Brian Burgess, Timothy Pollett, Simon |
author_sort | Richard, Stephanie A |
collection | PubMed |
description | BACKGROUND: The long-term duration of post COVID condition (PCC, “Long COVID”) remains unclear. In this study, we estimated the risk of healthcare encounters in Military Health System (MHS) beneficiaries for the 12 months post SARS-CoV-2 diagnosis, adjusting for prior healthcare use, and compared to those without known prior SARS-COV-2 diagnosis. METHODS: Follow up continues for the Epidemiology, Immunology and Clinical Characteristics of Emerging Infectious Diseases of Pandemic Potential (EPICC) COVID-19 cohort study MHS beneficiaries who were tested for SARS-COV-2 or vaccinated from March 2020 to April 2022. Participants with SARS-COV-2 diagnosis from 3/1/20 through 12/31/21 were matched 1:1 with participants in the same age group with no record of SARS-COV-2 diagnosis. We identified categories of ICD-10 diagnoses occurring from 3 months before through 12 months after first SARS-COV-2 diagnosis (or matched time point) from electronic medical records. Multivariable Poisson regression models were used to estimate the risk of ICD-10 diagnosis categories for those with past SARS-COV-2 diagnosis, compared to those with no SARS-COV-2 diagnosis, adjusting for age, sex, BMI, variant era, and prior healthcare use. [Figure: see text] RESULTS: Analyses included 1,819 matched pairs with a median age of 35 years. Participants were primarily male (63.0%) or white (57.3%) (Table 1) and severe acute COVID-19 was infrequent (9.6% hospitalized). Compared to those without a history of SARS-COV-2 diagnosis, medical encounters for all diagnosis groups (pulmonary, cardiovascular, diabetes, anxiety/depression, and neurology) were elevated in the first month after SARS-COV-2 diagnosis (Figures 1 and 2). Among the different diagnosis categories, only pulmonary diagnoses remained elevated at 9 months post-infection compared to those without a history of SARS-COV-2 diagnosis (risk ratio: 1.95 (95% CI 1.34, 2.83)). Percent of EPICC participants with medical encounters / diagnoses (by organ system or other domain) in health records. Participants without a history of SARS-CoV-2 infection were assigned the infection date of their matched case. [Figure: see text] Poisson regression analysis run using each category of healthcare encounters (pulmonary, cardiovascular, diabetes, neurology, and anxiety/depression) as the outcome. The models included time in 30-day periods around SARS-CoV-2 diagnosis date (or matched time point), SARS-CoV-2 diagnosis status, age, sex, BMI category, and variant/calendar period (calendar times with predominant Ancestral, Alpha, or Delta circulation), as well as a random effect for participant. [Figure: see text] CONCLUSION: MHS beneficiaries with prior SARS-COV-2 diagnosis were at higher risk of pulmonary-associated healthcare encounters through 9 months post-infection compared to those without prior SARS-COV-2 diagnosis, even after adjusting for baseline characteristics and calendar time. Future work will assess the effect of vaccination and boosting on this relationship. DISCLOSURES: Michael Morris, MD, Janssen Pharmaceuticals: Paid speaker (unrelated to this project and COVID-19 in general) Ryan C. Maves, MD, Sound Pharmaceuticals: Grant/Research Support Mark Simons, PhD, AstraZeneca: TBD Timothy Burgess, MD, AstraZeneca: TBD Simon Pollett, MBBS, AstraZeneca: The IDCRP and the Henry M. Jackson Foundation (HJF) were funded to conduct an unrelated phase III COVID-19 monoclonal antibody immunoprophylaxis trial |
format | Online Article Text |
id | pubmed-10679074 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-106790742023-11-27 437. Does “Long COVID” Resolve by One Year in U.S. Military Health System Beneficiaries? Richard, Stephanie A Byrne, Celia Rusiecki, Jennifer Berjohn, Catherine Lalani, Tahaniyat Smith, Alfred Mody, Rupal Ganesan, Anuradha Colombo, Rhonda Lindholm, David Morris, Michael Huprikar, Nikhil Colombo, Christopher Schofield, Christina Jones, Milissa U Mende, Katrin Saunders, David Livezey, Jeffrey Chang, David Ewers, Evan Maldonado, Carlos Scher, Ann Fries, Anthony C Maves, Ryan C Epsi, Nusrat J Schmidt, Kat Edwards, Margaret Sanchez Simons, Mark Tribble, David R Tribble, David R O’Connell, Robert Agan, Brian Burgess, Timothy Pollett, Simon Open Forum Infect Dis Abstract BACKGROUND: The long-term duration of post COVID condition (PCC, “Long COVID”) remains unclear. In this study, we estimated the risk of healthcare encounters in Military Health System (MHS) beneficiaries for the 12 months post SARS-CoV-2 diagnosis, adjusting for prior healthcare use, and compared to those without known prior SARS-COV-2 diagnosis. METHODS: Follow up continues for the Epidemiology, Immunology and Clinical Characteristics of Emerging Infectious Diseases of Pandemic Potential (EPICC) COVID-19 cohort study MHS beneficiaries who were tested for SARS-COV-2 or vaccinated from March 2020 to April 2022. Participants with SARS-COV-2 diagnosis from 3/1/20 through 12/31/21 were matched 1:1 with participants in the same age group with no record of SARS-COV-2 diagnosis. We identified categories of ICD-10 diagnoses occurring from 3 months before through 12 months after first SARS-COV-2 diagnosis (or matched time point) from electronic medical records. Multivariable Poisson regression models were used to estimate the risk of ICD-10 diagnosis categories for those with past SARS-COV-2 diagnosis, compared to those with no SARS-COV-2 diagnosis, adjusting for age, sex, BMI, variant era, and prior healthcare use. [Figure: see text] RESULTS: Analyses included 1,819 matched pairs with a median age of 35 years. Participants were primarily male (63.0%) or white (57.3%) (Table 1) and severe acute COVID-19 was infrequent (9.6% hospitalized). Compared to those without a history of SARS-COV-2 diagnosis, medical encounters for all diagnosis groups (pulmonary, cardiovascular, diabetes, anxiety/depression, and neurology) were elevated in the first month after SARS-COV-2 diagnosis (Figures 1 and 2). Among the different diagnosis categories, only pulmonary diagnoses remained elevated at 9 months post-infection compared to those without a history of SARS-COV-2 diagnosis (risk ratio: 1.95 (95% CI 1.34, 2.83)). Percent of EPICC participants with medical encounters / diagnoses (by organ system or other domain) in health records. Participants without a history of SARS-CoV-2 infection were assigned the infection date of their matched case. [Figure: see text] Poisson regression analysis run using each category of healthcare encounters (pulmonary, cardiovascular, diabetes, neurology, and anxiety/depression) as the outcome. The models included time in 30-day periods around SARS-CoV-2 diagnosis date (or matched time point), SARS-CoV-2 diagnosis status, age, sex, BMI category, and variant/calendar period (calendar times with predominant Ancestral, Alpha, or Delta circulation), as well as a random effect for participant. [Figure: see text] CONCLUSION: MHS beneficiaries with prior SARS-COV-2 diagnosis were at higher risk of pulmonary-associated healthcare encounters through 9 months post-infection compared to those without prior SARS-COV-2 diagnosis, even after adjusting for baseline characteristics and calendar time. Future work will assess the effect of vaccination and boosting on this relationship. DISCLOSURES: Michael Morris, MD, Janssen Pharmaceuticals: Paid speaker (unrelated to this project and COVID-19 in general) Ryan C. Maves, MD, Sound Pharmaceuticals: Grant/Research Support Mark Simons, PhD, AstraZeneca: TBD Timothy Burgess, MD, AstraZeneca: TBD Simon Pollett, MBBS, AstraZeneca: The IDCRP and the Henry M. Jackson Foundation (HJF) were funded to conduct an unrelated phase III COVID-19 monoclonal antibody immunoprophylaxis trial Oxford University Press 2023-11-27 /pmc/articles/PMC10679074/ http://dx.doi.org/10.1093/ofid/ofad500.507 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Abstract Richard, Stephanie A Byrne, Celia Rusiecki, Jennifer Berjohn, Catherine Lalani, Tahaniyat Smith, Alfred Mody, Rupal Ganesan, Anuradha Colombo, Rhonda Lindholm, David Morris, Michael Huprikar, Nikhil Colombo, Christopher Schofield, Christina Jones, Milissa U Mende, Katrin Saunders, David Livezey, Jeffrey Chang, David Ewers, Evan Maldonado, Carlos Scher, Ann Fries, Anthony C Maves, Ryan C Epsi, Nusrat J Schmidt, Kat Edwards, Margaret Sanchez Simons, Mark Tribble, David R Tribble, David R O’Connell, Robert Agan, Brian Burgess, Timothy Pollett, Simon 437. Does “Long COVID” Resolve by One Year in U.S. Military Health System Beneficiaries? |
title | 437. Does “Long COVID” Resolve by One Year in U.S. Military Health System Beneficiaries? |
title_full | 437. Does “Long COVID” Resolve by One Year in U.S. Military Health System Beneficiaries? |
title_fullStr | 437. Does “Long COVID” Resolve by One Year in U.S. Military Health System Beneficiaries? |
title_full_unstemmed | 437. Does “Long COVID” Resolve by One Year in U.S. Military Health System Beneficiaries? |
title_short | 437. Does “Long COVID” Resolve by One Year in U.S. Military Health System Beneficiaries? |
title_sort | 437. does “long covid” resolve by one year in u.s. military health system beneficiaries? |
topic | Abstract |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10679074/ http://dx.doi.org/10.1093/ofid/ofad500.507 |
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