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Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study
by
Sbihi, Hind
, Wong, Alyson W.
, Russell, James A.
, Binka, Mawuena
, Carlsten, Christopher
, Tran, Karen C.
, Janjua, Naveed Z.
, Levin, Adeera
, Ryerson, Christopher J.
in
Analysis
/ Anxiety
/ Biology and Life Sciences
/ Carbon monoxide
/ Clinical outcomes
/ Cohort analysis
/ Cough
/ COVID-19
/ Dyspnea
/ Fatigue
/ Illnesses
/ Latent class analysis
/ Long COVID
/ Lungs
/ Medicine and Health Sciences
/ Mental depression
/ Mental disorders
/ Patients
/ Phenotype
/ Phenotypes
/ Post traumatic stress disorder
/ Posttraumatic stress disorder
/ Psychological stress
/ Quality of life
/ Questionnaires
/ Respiration
/ Respiratory function
/ Severe acute respiratory syndrome coronavirus 2
/ Social Sciences
/ Statistical analysis
/ Subpopulations
2023
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Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study
by
Sbihi, Hind
, Wong, Alyson W.
, Russell, James A.
, Binka, Mawuena
, Carlsten, Christopher
, Tran, Karen C.
, Janjua, Naveed Z.
, Levin, Adeera
, Ryerson, Christopher J.
in
Analysis
/ Anxiety
/ Biology and Life Sciences
/ Carbon monoxide
/ Clinical outcomes
/ Cohort analysis
/ Cough
/ COVID-19
/ Dyspnea
/ Fatigue
/ Illnesses
/ Latent class analysis
/ Long COVID
/ Lungs
/ Medicine and Health Sciences
/ Mental depression
/ Mental disorders
/ Patients
/ Phenotype
/ Phenotypes
/ Post traumatic stress disorder
/ Posttraumatic stress disorder
/ Psychological stress
/ Quality of life
/ Questionnaires
/ Respiration
/ Respiratory function
/ Severe acute respiratory syndrome coronavirus 2
/ Social Sciences
/ Statistical analysis
/ Subpopulations
2023
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Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study
by
Sbihi, Hind
, Wong, Alyson W.
, Russell, James A.
, Binka, Mawuena
, Carlsten, Christopher
, Tran, Karen C.
, Janjua, Naveed Z.
, Levin, Adeera
, Ryerson, Christopher J.
in
Analysis
/ Anxiety
/ Biology and Life Sciences
/ Carbon monoxide
/ Clinical outcomes
/ Cohort analysis
/ Cough
/ COVID-19
/ Dyspnea
/ Fatigue
/ Illnesses
/ Latent class analysis
/ Long COVID
/ Lungs
/ Medicine and Health Sciences
/ Mental depression
/ Mental disorders
/ Patients
/ Phenotype
/ Phenotypes
/ Post traumatic stress disorder
/ Posttraumatic stress disorder
/ Psychological stress
/ Quality of life
/ Questionnaires
/ Respiration
/ Respiratory function
/ Severe acute respiratory syndrome coronavirus 2
/ Social Sciences
/ Statistical analysis
/ Subpopulations
2023
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Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study
Journal Article
Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study
2023
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Overview
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.
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]).
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.
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.
Publisher
Public Library of Science,Public Library of Science (PLoS)
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