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EFFECT OF PAXLOVID TREATMENT ON LONG COVID ONSET: AN EHR-BASED TARGET TRIAL EMULATION FROM N3C.

Alexander J PreissAbhishek BhatiaChengxi ZangLeyna V AragonJohn M BarattaMonika BaskaranFrank BlanceroM Daniel BrannockRobert F ChewIvan DiazMegan L FitzgeraldElizabeth P KellyAndrea G ZhouMark G WeinerThomas W CartonFei WangRainu KaushalChristopher G ChuteMelissa A HaendelRichard A MoffittEmily Rose Pfaff
Published in: medRxiv : the preprint server for health sciences (2024)
Preventing and treating post-acute sequelae of SARS-CoV-2 infection (PASC), commonly known as Long COVID, has become a public health priority. In this study, we examined whether treatment with Paxlovid in the acute phase of COVID-19 helps prevent the onset of PASC. We used electronic health records from the National Covid Cohort Collaborative (N3C) to define a cohort of 426,461 patients who had COVID-19 since April 1, 2022, and were eligible for Paxlovid treatment due to risk for progression to severe COVID-19. We used the target trial emulation (TTE) framework to estimate the effect of Paxlovid treatment on PASC incidence. Our primary outcome measure was a PASC computable phenotype. Secondary outcomes were the onset of novel cognitive, fatigue, and respiratory symptoms in the post-acute period. Paxlovid treatment did not have a significant effect on overall PASC incidence (relative risk [RR] = 0.99, 95% confidence interval [CI] 0.96-1.01). However, its effect varied across the cognitive (RR = 0.85, 95% CI 0.79-0.90), fatigue (RR = 0.93, 95% CI 0.89-0.96), and respiratory (RR = 0.99, 95% CI 0.95-1.02) symptom clusters, suggesting that Paxlovid treatment may help prevent post-acute cognitive and fatigue symptoms more than others.
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