National Clinical Cohort Collaborative (formerly National COVID Cohort Collaborative) (N3C) and NIH RECOVER
Long COVID research in the National Clinical Cohort Collaborative (formerly National COVID Cohort Collaborative) (N3C) and NIH RECOVER, using harmonized multi-site electronic health record (EHR) data. Contributions include machine-learning phenotyping, ICD-10-based characterization, and target trial emulations of antiviral treatment.
Project details
outputs
publications
- Effect of Paxlovid Treatment during Acute COVID-19 on Long COVID Onset: An EHR-Based Target Trial Emulation from the N3C and RECOVER Consortia
- Re-engineering a Machine Learning Phenotype to Adapt to the Changing COVID-19 Landscape: A Machine Learning Modelling Study from the N3C and RECOVER Consortia
- Identifying commonalities and differences between EHR representations of PASC and ME/CFS in the RECOVER EHR cohort
- Effect of Nirmatrelvir/Ritonavir (Paxlovid) on Hospitalization among Adults with COVID-19: An EHR-Based Target Trial Emulation from N3C
- Coding Long COVID: Characterizing a New Disease through an ICD-10 Lens
- Identifying Who Has Long COVID in the USA: A Machine Learning Approach Using N3C Data