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Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study

OBJECTIVES: We sought to 1) identify long COVID phenotypes based on patient reported outcome measures (PROMs) and 2) determine whether the phenotypes were associated with quality of life (QoL) and/or lung function. METHODS: This was a longitudinal cohort study of hospitalized and non-hospitalized pa...

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Autores principales: Wong, Alyson W., Tran, Karen C., Binka, Mawuena, Janjua, Naveed Z., Sbihi, Hind, Russell, James A., Carlsten, Christopher, Levin, Adeera, Ryerson, Christopher J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10237387/
https://www.ncbi.nlm.nih.gov/pubmed/37267379
http://dx.doi.org/10.1371/journal.pone.0286588
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author Wong, Alyson W.
Tran, Karen C.
Binka, Mawuena
Janjua, Naveed Z.
Sbihi, Hind
Russell, James A.
Carlsten, Christopher
Levin, Adeera
Ryerson, Christopher J.
author_facet Wong, Alyson W.
Tran, Karen C.
Binka, Mawuena
Janjua, Naveed Z.
Sbihi, Hind
Russell, James A.
Carlsten, Christopher
Levin, Adeera
Ryerson, Christopher J.
author_sort Wong, Alyson W.
collection PubMed
description OBJECTIVES: We sought to 1) identify long COVID phenotypes based on patient reported outcome measures (PROMs) and 2) determine whether the phenotypes were associated with quality of life (QoL) and/or lung function. METHODS: This was a longitudinal cohort study of hospitalized and non-hospitalized patients from March 2020 to January 2022 that was conducted across 4 Post-COVID Recovery Clinics in British Columbia, Canada. Latent class analysis was used to identify long COVID phenotypes using baseline PROMs (fatigue, dyspnea, cough, anxiety, depression, and post-traumatic stress disorder). We then explored the association between the phenotypes and QoL (using the EuroQoL 5 dimensions visual analogue scale [EQ5D VAS]) and lung function (using the diffusing capacity of the lung for carbon monoxide [DLCO]). RESULTS: There were 1,344 patients enrolled in the study (mean age 51 ±15 years; 780 [58%] were females; 769 (57%) were of a non-White race). Three distinct long COVID phenotypes were identified: Class 1) fatigue and dyspnea, Class 2) anxiety and depression, and Class 3) fatigue, dyspnea, anxiety, and depression. Class 3 had a significantly lower EQ5D VAS at 3 (50±19) and 6 months (54 ± 22) compared to Classes 1 and 2 (p<0.001). The EQ5D VAS significantly improved between 3 and 6 months for Class 1 (median difference of 6.0 [95% CI, 4.0 to 8.0]) and Class 3 (median difference of 5.0 [95% CI, 0 to 8.5]). There were no differences in DLCO between the classes. CONCLUSIONS: There were 3 distinct long COVID phenotypes with different outcomes in QoL between 3 and 6 months after symptom onset. These phenotypes suggest that long COVID is a heterogeneous condition with distinct subpopulations who may have different outcomes and warrant tailored therapeutic approaches.
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spelling pubmed-102373872023-06-03 Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study Wong, Alyson W. Tran, Karen C. Binka, Mawuena Janjua, Naveed Z. Sbihi, Hind Russell, James A. Carlsten, Christopher Levin, Adeera Ryerson, Christopher J. PLoS One Research Article OBJECTIVES: We sought to 1) identify long COVID phenotypes based on patient reported outcome measures (PROMs) and 2) determine whether the phenotypes were associated with quality of life (QoL) and/or lung function. METHODS: This was a longitudinal cohort study of hospitalized and non-hospitalized patients from March 2020 to January 2022 that was conducted across 4 Post-COVID Recovery Clinics in British Columbia, Canada. Latent class analysis was used to identify long COVID phenotypes using baseline PROMs (fatigue, dyspnea, cough, anxiety, depression, and post-traumatic stress disorder). We then explored the association between the phenotypes and QoL (using the EuroQoL 5 dimensions visual analogue scale [EQ5D VAS]) and lung function (using the diffusing capacity of the lung for carbon monoxide [DLCO]). RESULTS: There were 1,344 patients enrolled in the study (mean age 51 ±15 years; 780 [58%] were females; 769 (57%) were of a non-White race). Three distinct long COVID phenotypes were identified: Class 1) fatigue and dyspnea, Class 2) anxiety and depression, and Class 3) fatigue, dyspnea, anxiety, and depression. Class 3 had a significantly lower EQ5D VAS at 3 (50±19) and 6 months (54 ± 22) compared to Classes 1 and 2 (p<0.001). The EQ5D VAS significantly improved between 3 and 6 months for Class 1 (median difference of 6.0 [95% CI, 4.0 to 8.0]) and Class 3 (median difference of 5.0 [95% CI, 0 to 8.5]). There were no differences in DLCO between the classes. CONCLUSIONS: There were 3 distinct long COVID phenotypes with different outcomes in QoL between 3 and 6 months after symptom onset. These phenotypes suggest that long COVID is a heterogeneous condition with distinct subpopulations who may have different outcomes and warrant tailored therapeutic approaches. Public Library of Science 2023-06-02 /pmc/articles/PMC10237387/ /pubmed/37267379 http://dx.doi.org/10.1371/journal.pone.0286588 Text en © 2023 Wong et al 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 use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Wong, Alyson W.
Tran, Karen C.
Binka, Mawuena
Janjua, Naveed Z.
Sbihi, Hind
Russell, James A.
Carlsten, Christopher
Levin, Adeera
Ryerson, Christopher J.
Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study
title Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study
title_full Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study
title_fullStr Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study
title_full_unstemmed Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study
title_short Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study
title_sort use of latent class analysis and patient reported outcome measures to identify distinct long covid phenotypes: a longitudinal cohort study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10237387/
https://www.ncbi.nlm.nih.gov/pubmed/37267379
http://dx.doi.org/10.1371/journal.pone.0286588
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