{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T11:51:27Z","timestamp":1791805887562,"version":"4.3.4"},"reference-count":29,"publisher":"Public Library of Science (PLoS)","issue":"6","license":[{"start":{"date-parts":[[2023,6,2]],"date-time":"2023-06-02T00:00:00Z","timestamp":1685664000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Canadian Lung Association & Canadian Institutes of Health Research","award":["HEC 181075"],"award-info":[{"award-number":["HEC 181075"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Objectives<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Methods<\/jats:title>\n<jats:p>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]).<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>There were 1,344 patients enrolled in the study (mean age 51 \u00b115 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\u00b119) and 6 months (54 \u00b1 22) compared to Classes 1 and 2 (p&lt;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.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Conclusions<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0286588","type":"journal-article","created":{"date-parts":[[2023,6,2]],"date-time":"2023-06-02T18:10:14Z","timestamp":1685729414000},"page":"e0286588","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":26,"title":["Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study"],"prefix":"10.1371","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4910-1948","authenticated-orcid":true,"given":"Alyson W.","family":"Wong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karen C.","family":"Tran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mawuena","family":"Binka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Naveed Z.","family":"Janjua","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hind","family":"Sbihi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James A.","family":"Russell","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Carlsten","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adeera","family":"Levin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher J.","family":"Ryerson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2023,6,2]]},"reference":[{"issue":"5","key":"pone.0286588.ref001","doi-asserted-by":"crossref","first-page":"e2111417","DOI":"10.1001\/jamanetworkopen.2021.11417","article-title":"Assessment of the Frequency and Variety of Persistent Symptoms Among Patients With COVID-19: A Systematic Review","volume":"4","author":"T Nasserie","year":"2021","journal-title":"JAMA Netw Open"},{"issue":"1","key":"pone.0286588.ref002","doi-asserted-by":"crossref","first-page":"e1002033","DOI":"10.1371\/journal.pbio.1002033","article-title":"Finding our way through phenotypes","volume":"13","author":"AR Deans","year":"2015","journal-title":"PLoS Biol"},{"issue":"9","key":"pone.0286588.ref003","doi-asserted-by":"crossref","first-page":"e0275274","DOI":"10.1371\/journal.pone.0275274","article-title":"Post-acute sequelae of COVID-19 symptom phenotypes and therapeutic strategies: A prospective, observational study","volume":"17","author":"JA Frontera","year":"2022","journal-title":"PLoS One"},{"issue":"4","key":"pone.0286588.ref004","doi-asserted-by":"crossref","first-page":"ofac060","DOI":"10.1093\/ofid\/ofac060","article-title":"Identification of Distinct Long COVID Clinical Phenotypes Through Cluster Analysis of Self-Reported Symptoms","volume":"9","author":"G Kenny","year":"2022","journal-title":"Open Forum Infect Dis"},{"key":"pone.0286588.ref005","doi-asserted-by":"crossref","first-page":"104413","DOI":"10.1016\/j.ebiom.2022.104413","article-title":"Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes","volume":"87","author":"JT Reese","year":"2023","journal-title":"EBioMedicine"},{"key":"pone.0286588.ref006","unstructured":"Canadian Institute for Health Information. 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