Published on in Vol 10, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35190, first published .
Mining Electronic Health Records for Drugs Associated With 28-day Mortality in COVID-19: Pharmacopoeia-wide Association Study (PharmWAS)

Mining Electronic Health Records for Drugs Associated With 28-day Mortality in COVID-19: Pharmacopoeia-wide Association Study (PharmWAS)

Mining Electronic Health Records for Drugs Associated With 28-day Mortality in COVID-19: Pharmacopoeia-wide Association Study (PharmWAS)

Ivan Lerner   1, 2, 3 , MD ;   Arnaud Serret-Larmande   1, 2 , MD ;   Bastien Rance   1, 3 , PhD ;   Nicolas Garcelon   3, 4 , PhD ;   Anita Burgun   1, 2, 3 , MD, PhD ;   Laurent Chouchana   5 , PhD, PharmD ;   Antoine Neuraz   1, 2, 3 , MD, PhD

1 Inserm, Centre de Recherche des Cordeliers, Sorbonne Université, Paris, France

2 Informatique biomédicale, Hôpital Necker-Enfants Malades, Assistance Publique - Hôpitaux de Paris, Paris, France

3 HeKA Team, Inria, Paris, France

4 Inserm UMR 1163, Data Science Platform, Université de Paris, Imagine Institute, Paris, France

5 Centre Régional de Pharmacovigilance, Service de Pharmacologie, Hôpital Cochin, Assistance Publique - Hôpitaux de Paris, Centre - Université de Paris, Paris, France

Corresponding Author:

  • Antoine Neuraz, MD, PhD
  • Inserm
  • Centre de Recherche des Cordeliers
  • Sorbonne Université
  • Université de Paris
  • 15 Rue de l'École de Médecine
  • Paris, 75006
  • France
  • Phone: 33 01 44 27 64 82
  • Email: antoine.neuraz@aphp.fr