Unveiling long COVID symptomatology, co-occurrence trends, and symptom distress post SARS-CoV-2 infection.
J Infect Public Health
; 17(7): 102464, 2024 Jul.
Article
em En
| MEDLINE
| ID: mdl-38865773
ABSTRACT
BACKGROUND:
Long COVID, an emerging public health issue, is characterized by persistent symptoms following SARS-CoV-2 infection. This study aims to explore the relationship between post-COVID-19 symptomatology and patient distress employing Latent Class Analysis to uncover symptom co-occurrence patterns and their association with distress.METHODS:
A cross-sectional study was conducted using an online survey among 240 participants from a university and affiliated hospital of southern Taiwan. The survey quantified distress due to persistent symptoms and assessed the prevalence of Long COVID, symptom co-occurrence, and latent symptom classes. Latent Class Analysis (LCA) identified distinct symptom patterns, and multiple regression models evaluated associations between symptom patterns, distress, and demographic factors.RESULTS:
The study found that 80 % of participants experienced Long COVID, with symptoms persisting for over three months. Individuals with multiple COVID-19 infections showed a significant increase in general (ß = 1.79), cardiovascular (ß = 0.61), and neuropsychological symptoms (ß = 2.18), and higher total distress scores (ß = 6.35). Three distinct symptomatology classes were identified "Diverse", "Mild", and "Severe" symptomatology. The "Mild Symptomatology" class was associated with lower distress (-10.61), while the "Severe Symptomatology" class showed a significantly higher distress due to symptoms (13.32).CONCLUSION:
The study highlights the significant impact of Long COVID on individuals, with distinct patterns of symptomatology and associated distress. It emphasizes the cumulative effect of multiple COVID-19 infections on symptom severity and the importance of tailored care strategies.Palavras-chave
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Base de dados:
MEDLINE
Assunto principal:
SARS-CoV-2
/
COVID-19
/
Síndrome de COVID-19 Pós-Aguda
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article