BibTex format
@article{Sangkaew:2024:10.1186/s12879-024-10055-2,
author = {Sangkaew, S and Tumviriyakul, H and Cheranakhorn, C and Songumpai, N and Pinpathomrat, N and Seeyankem, B and Yasharad, K and Loomcharoen, P and Pakdee, W and Changawej, C and Dumrongkullachart, D and Limheng, A and Dorigatti, I},
doi = {10.1186/s12879-024-10055-2},
journal = {BMC Infectious Diseases},
title = {Unveiling post-COVID-19 syndrome: incidence, biomarkers, and clinical phenotypes in a Thai population},
url = {http://dx.doi.org/10.1186/s12879-024-10055-2},
volume = {24},
year = {2024}
}
RIS format (EndNote, RefMan)
TY - JOUR
AB - BackgroundPost-COVID- 19 syndrome (PCS) significantly impacts the quality of life of survivors. There is, however, a lack of a standardized approach to PCS diagnosis and management. Our bidirectional cohort study aimed to estimate PCS incidence, identify risk factors and biomarkers, and classify clinical phenotypes for enhanced management to improve patient outcomes.MethodsA bidirectional prospective cohort study was conducted at five medical sites in Hatyai district in Songkhla Province, Thailand. Participants were randomly selected from among the survivors of COVID-19 aged≥18 years between May 15, 2022, and January 31, 2023. The selected participants underwent a scheduled outpatient visit for symptom and health assessments 12 to 16 weeks after the acute onset of infection, during which PCS was diagnosed and blood samples were collected for hematological, inflammatory, and serological tests. PCS was defined according to the World Health Organization criteria. Univariate and multiple logistic regression analyses were used to identify biomarkers associated with PCS. Moreover, three clustering methods (agglomerative hierarchical, divisive hierarchical, and K-means clustering) were applied, and internal validation metrics were used to determine clustering and similarities in phenotypes.FindingsA total of 300 survivors were enrolled in the study, 47% of whom developed PCS according to the World Health Organization (WHO) definition. In the sampled cohort, 66.3% were females, and 79.4% of them developed PCS (as compared to 54.7% of males, p-value <0.001). Comorbidities were present in 19% (57/300) of all patients, with 11% (18/159) in the group without PCS and 27.7% (39/141) in the group with PCS. The incidence of PCS varied depending on the criteria used and reached 13% when a quality of life indicator was added to the WHO definition. Common PCS symptoms were hair loss (22%) and fatigue (21%), while mental health symptoms were less frequent (insomnia 3%, dep
AU - Sangkaew,S
AU - Tumviriyakul,H
AU - Cheranakhorn,C
AU - Songumpai,N
AU - Pinpathomrat,N
AU - Seeyankem,B
AU - Yasharad,K
AU - Loomcharoen,P
AU - Pakdee,W
AU - Changawej,C
AU - Dumrongkullachart,D
AU - Limheng,A
AU - Dorigatti,I
DO - 10.1186/s12879-024-10055-2
PY - 2024///
SN - 1471-2334
TI - Unveiling post-COVID-19 syndrome: incidence, biomarkers, and clinical phenotypes in a Thai population
T2 - BMC Infectious Diseases
UR - http://dx.doi.org/10.1186/s12879-024-10055-2
UR - https://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-024-10055-2
UR - http://hdl.handle.net/10044/1/115029
VL - 24
ER -