Essential Site Maintenance: Authorea-powered sites will be updated circa 15:00-17:00 Eastern on Tuesday 5 November.
There should be no interruption to normal services, but please contact us at [email protected] in case you face any issues.

loading page

Using machine learning to characterize the impact of oseltamivir on clinical failure in hospitalized patients with lower respiratory tract infection
  • +4
  • Timothy Wiemken,
  • Stephen Furmanek,
  • Ruth Carrico,
  • Paula Peyrani,
  • Daniel Hoft,
  • Alicia Fry,
  • Julio Ramirez
Timothy Wiemken
Saint Louis University

Corresponding Author:[email protected]

Author Profile
Stephen Furmanek
University of Louisville
Author Profile
Ruth Carrico
University of Louisville
Author Profile
Paula Peyrani
University of Louisville
Author Profile
Daniel Hoft
Saint Louis University
Author Profile
Alicia Fry
Centers for Disease Control and Prevention
Author Profile
Julio Ramirez
University of Louisville Medical School
Author Profile

Abstract

We used causal forest machine learning to re-analyze data from a randomized study evaluating oseltamivir in hospitalized patients with lower respiratory tract infection. Influenza virus infected patients had 26% lower risk of clinical failure when treated with oseltamivir (95% CI 3.2% - 48.0%), suggesting it may be a useful intervention.