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Nirmatrelvir/ritonavir and risk of long COVID symptoms: a retrospective cohort study

We conducted a retrospective cohort study to assess whether treatment with nirmatrelvir/ritonavir was associated with a reduced risk of long COVID. We enrolled 500 adults with confirmed SARS-CoV-2 who were eligible for nirmatrelvir/ritonavir; 250 who took nirmatrelvir/ritonavir and 250 who did not....

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Detalles Bibliográficos
Autores principales: Congdon, Seth, Narrowe, Zev, Yone, Nang, Gunn, Jacob, Deng, Yuting, Nori, Priya, Cowman, Kelsie, Islam, Marjan, Rikin, Sharon, Starrels, Joanna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10640584/
https://www.ncbi.nlm.nih.gov/pubmed/37951998
http://dx.doi.org/10.1038/s41598-023-46912-4
Descripción
Sumario:We conducted a retrospective cohort study to assess whether treatment with nirmatrelvir/ritonavir was associated with a reduced risk of long COVID. We enrolled 500 adults with confirmed SARS-CoV-2 who were eligible for nirmatrelvir/ritonavir; 250 who took nirmatrelvir/ritonavir and 250 who did not. The primary outcome was the development of one or more of eleven prespecified long COVID symptoms, assessed through a structured telephone interview four months after the positive SARS-CoV-2 test. Multivariable logistic regression models controlled for age, sex, race/ethnicity, chronic conditions, and COVID-19 vaccination status. We found that participants who took nirmatrelvir/ritonavir were no less likely to develop long COVID symptoms, compared to those who did not take the medication (44% vs. 49.6%, p = 0.21). Taking nirmatrelvir/ritonavir was associated with a lower odds of two of the eleven long COVID symptoms, brain fog (OR 0.58, 95% CI 0.38–0.88) and chest pain/tightness (OR 0.51, 95% CI 0.28–0.91). Our finding that treatment with nirmatrelvir/ritonavir was not associated with a lower risk of developing long COVID is different from prior studies that obtained data only from electronic medical records.