TY - JOUR
T1 - Who develops long COVID?
T2 - Longitudinal pre-pandemic predictors of long COVID and symptom clusters in a representative Dutch population
AU - Slurink, I.A.L.
AU - van den Houdt, S.C.M.
AU - Mertens, G.
PY - 2024
Y1 - 2024
N2 - ObjectivesPrior studies show that long COVID has a heterogeneous presentation. Whether specific risk factors are related to subclusters of long COVID remains unknown. This study aimed to determine pre-pandemic predictors of long COVID and symptom clustering. MethodsA total of 3,022 participants of a panel representative of the Dutch population completed an online survey about long COVID symptoms. Data was merged into 2018/2019 panel data covering sociodemographic, medical, and psychosocial predictors. A total of 415 participants were classified as having long COVID. K-means clustering was used to identify patient clusters. Multivariate and lasso regression was used to identify relevant predictors compared to a COVID-19 positive control group. ResultsPredictors of long-term COVID included older age, Western ethnicity, BMI, chronic disease, COVID-19 reinfections, severity, and symptoms, lower self-esteem, and higher positive affect (AUC = 0.79, 95%CI 0.73-0.86). Four clusters were identified: a low and a high symptom severity cluster, a smell-taste and respiratory symptoms cluster, and a neuro-cognitive, psychosocial, and inflammatory symptom cluster. Predictors for the different clusters included regular health complaints, healthcare use, fear of COVID-19, anxiety, depressive symptoms, and neuroticism. ConclusionsA combination of sociodemographic, medical, and psychosocial factors predicted long COVID. Heterogenous symptom clusters suggest that there are different phenotypes of long COVID-19 presentation.
AB - ObjectivesPrior studies show that long COVID has a heterogeneous presentation. Whether specific risk factors are related to subclusters of long COVID remains unknown. This study aimed to determine pre-pandemic predictors of long COVID and symptom clustering. MethodsA total of 3,022 participants of a panel representative of the Dutch population completed an online survey about long COVID symptoms. Data was merged into 2018/2019 panel data covering sociodemographic, medical, and psychosocial predictors. A total of 415 participants were classified as having long COVID. K-means clustering was used to identify patient clusters. Multivariate and lasso regression was used to identify relevant predictors compared to a COVID-19 positive control group. ResultsPredictors of long-term COVID included older age, Western ethnicity, BMI, chronic disease, COVID-19 reinfections, severity, and symptoms, lower self-esteem, and higher positive affect (AUC = 0.79, 95%CI 0.73-0.86). Four clusters were identified: a low and a high symptom severity cluster, a smell-taste and respiratory symptoms cluster, and a neuro-cognitive, psychosocial, and inflammatory symptom cluster. Predictors for the different clusters included regular health complaints, healthcare use, fear of COVID-19, anxiety, depressive symptoms, and neuroticism. ConclusionsA combination of sociodemographic, medical, and psychosocial factors predicted long COVID. Heterogenous symptom clusters suggest that there are different phenotypes of long COVID-19 presentation.
KW - COVID-19
KW - Clustering
KW - Long COVID
KW - Prediction model
KW - Symptoms
KW - post-COVID-19
UR - http://www.scopus.com/inward/record.url?scp=85192156550&partnerID=8YFLogxK
U2 - 10.1016/j.ijid.2024.107048
DO - 10.1016/j.ijid.2024.107048
M3 - Article
C2 - 38609036
SN - 1201-9712
VL - 144
JO - International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
JF - International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
M1 - 107048
ER -