Effect of Paxlovid Treatment on Long COVID Onset: An EHR-Based Target Trial Emulation from N3C


Alexander Preiss Chengxi Zang Leyna V. Aragon John M. Baratta Monika Baskaran Frank Blancero M. Daniel Brannock Robert F. Chew Ivan Diaz Megan Fitzgerald Elizabeth P. Kelly Andrea Zhou Mark G. Weiner Thomas W. Carton Fei Wang Rainu Kaushal Christopher G. Chute Melissa Haendel Richard Moffitt Emily Pfaff N3C Consortium the RECOVER EHR Cohort


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.