Abstract
Purpose: We aimed to assess symptoms in patients after SARS-CoV-2 infection and to identify factors predicting prolonged time to symptom-free.
Methods: COVIDOM/NAPKON-POP is a population-based prospective cohort of adults whose first on-site visits were scheduled ≥ 6 months after a positive SARS-CoV-2 PCR test. Retrospective data including self-reported symptoms and time to symptom-free were collected during the survey before a site visit. In the survival analyses, being symptom-free served as the event and time to be symptom-free as the time variable. Data were visualized with Kaplan–Meier curves, differences were tested with log-rank tests. A stratified Cox proportional hazard model was used to estimate adjusted hazard ratios (aHRs) of predictors, with aHR < 1 indicating a longer time to symptom-free.
Results: Of 1175 symptomatic participants included in the present analysis, 636 (54.1%) reported persistent symptoms after 280 days (SD 68) post infection. 25% of participants were free from symptoms after 18 days [quartiles: 14, 21]. Factors associated with prolonged time to symptom-free were age 49–59 years compared to < 49 years (aHR 0.70, 95% CI 0.56–0.87), female sex (aHR 0.78, 95% CI 0.65–0.93), lower educational level (aHR 0.77, 95% CI 0.64–0.93), living with a partner (aHR 0.81, 95% CI 0.66–0.99), low resilience (aHR 0.65, 95% CI 0.47–0.90), steroid treatment (aHR 0.22, 95% CI 0.05–0.90) and no medication (aHR 0.74, 95% CI 0.62–0.89) during acute infection.
Conclusion: In the studied population, COVID-19 symptoms had resolved in one-quarter of participants within 18 days, and in 34.5% within 28 days. Over half of the participants reported COVID-19-related symptoms 9 months after infection. Symptom persistence was predominantly determined by participant’s characteristics that are difficult to modify.
Item Type: | Journal article |
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Keywords: | COVID-19; Long COVID; Post-COVID syndrome; Time to symptom-free; Risk factors |
Faculties: | Medicine > Institute for Medical Information Processing, Biometry and Epidemiology |
Subjects: | 600 Technology > 610 Medicine and health |
URN: | urn:nbn:de:bvb:19-epub-96462-0 |
ISSN: | 0300-8126 |
Language: | English |
Item ID: | 96462 |
Date Deposited: | 02. Jun 2023, 12:01 |
Last Modified: | 22. Nov 2023, 16:14 |