Finding Long-COVID: Temporal Topic Modeling of Electronic Health Records from the N3C and RECOVER Programs
September 2023
in “
medRxiv (Cold Spring Harbor Laboratory)
”
TLDR Long-COVID has diverse, long-term health impacts, especially in young people.
The study utilized electronic health records from the N3C and RECOVER programs to identify and analyze conditions associated with Long-COVID (PASC) using temporal topic modeling. By examining data from over 14 million patients, the researchers identified 213 significant conditions, including non-scarring alopecia and telogen effluvium, particularly in pediatric and adolescent PASC patients. The study highlighted the diverse and long-term health impacts of COVID-19, emphasizing the importance of comprehensive data analysis and improved diagnostics for understanding and treating Long-COVID.