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Semergen ; 50(5): 102208, 2024.
Article in English | MEDLINE | ID: mdl-38471366

ABSTRACT

OBJECTIVE: This study aimed to characterize the prevalence as well as clinical and epidemiological features of persistent symptoms after acute COVID-19, focusing on gender-specific differences in a primary care setting. METHODS: A total of 1542 individuals with confirmed SARS-CoV-2 infection were enrolled. The study population comprised 55.77% females (mean age: 45.04 years). Risk factors for persistent COVID-19 were analyzed, revealing disparities between men and women. Symptom clusters and their prevalence were assessed over time, along with functional status using the post-COVID-19 functional status scale. RESULTS: The prevalence of persistent COVID-19 was 12.38%, with females exhibiting a 1.5 times higher risk. Females displayed a higher number of visits and persistent symptoms at 90 days, decreasing after one year. Symptom clusters varied between genders, with females experiencing more dermatological issues. Functional status analysis revealed that females had a better pre-infection status, similar status to males at 90 days, and improved status at 180-, 270-, and 365-days post-infection. Logistic regression analysis showed significant associations between persistence, gender, hospitalization, radiological abnormalities, age, and immunosuppression. CONCLUSION: This study provides insights into the prevalence and clinical characteristics of persistent COVID-19 in a primary care population. Females exhibited a higher risk of persistent symptoms and displayed distinct patterns in symptom clusters and functional status compared to males. These findings contribute to a better understanding of the long-term effects of COVID-19 and highlight the importance of gender-specific considerations in post-acute care.


Subject(s)
COVID-19 , Post-Acute COVID-19 Syndrome , Primary Health Care , Humans , Female , Male , COVID-19/epidemiology , COVID-19/complications , Middle Aged , Sex Factors , Risk Factors , Adult , Prevalence , Primary Health Care/statistics & numerical data , Aged , Hospitalization/statistics & numerical data , Time Factors , Young Adult
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