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Unveiling long COVID symptomatology, co-occurrence trends, and symptom distress post SARS-CoV-2 infection.
Kukreti, Shikha; Yeh, Chun-Yin; Chen, Yi-Jhen; Lu, Meng-Ting; Li, Ming-Chi; Lai, Yi-Yin; Li, Chung-Yi; Ko, Nai-Ying.
Afiliação
  • Kukreti S; Department of Nursing, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Public Health, College of Medicine, National Cheng Kung University, Taiwan.
  • Yeh CY; Department of Computer Science and Information Engineering, National Cheng Kung University, Taiwan.
  • Chen YJ; Department of Public Health, College of Medicine, National Cheng Kung University, Taiwan.
  • Lu MT; Department of Nursing, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Public Health, College of Medicine, National Cheng Kung University, Taiwan.
  • Li MC; Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine National Cheng Kung University, Tainan, Taiwan.
  • Lai YY; Centre of Infection Control, College of Medicine, National Cheng Kung University and Hospital, Tainan, Taiwan.
  • Li CY; Department of Public Health, College of Medicine, National Cheng Kung University, Taiwan; Department of Public Health, College of Public Health, China Medical University, Taichung; Department of Healthcare Administration, College of Medical and Health Science, Asia University, Taichung, Taiwan.
  • Ko NY; Department of Nursing, College of Medicine, National Cheng Kung University, Tainan, Taiwan; International Doctoral Program in Nursing, Department of Nursing, College of Medicine, National Cheng Kung University, Tainan, Taiwan. Electronic address: nyko@mail.ncku.edu.tw.
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.
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Texto completo: 1 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

Texto completo: 1 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