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A pragmatic approach to estimating average treatment effects from EHR data: the effect of prone positioning on mechanically ventilated COVID-19 patients

Authors :
Izdebski, Adam
Thoral, Patrick J.
Lalisang, Robbert C. A.
McHugh, Dean M.
Gommers, Diederik
Cremer, Olaf L.
Bosman, Rob J.
Rigter, Sander
Wils, Evert-Jan
Frenzel, Tim
Dongelmans, Dave A.
de Jong, Remko
Peters, Marco A. A.
Kamps, Marlijn J. A
Ramnarain, Dharmanand
Nowitzky, Ralph
Nooteboom, Fleur G. C. A.
de Ruijter, Wouter
Urlings-Strop, Louise C.
Smit, Ellen G. M.
Mehagnoul-Schipper, D. Jannet
Dormans, Tom
de Jager, Cornelis P. C.
Hendriks, Stefaan H. A.
Achterberg, Sefanja
Oostdijk, Evelien
Reidinga, Auke C.
Festen-Spanjer, Barbara
Brunnekreef, Gert B.
Cornet, Alexander D.
Tempel, Walter van den
Boelens, Age D.
Koetsier, Peter
Lens, Judith
Faber, Harald J.
Karakus, A.
Entjes, Robert
de Jong, Paul
Rettig, Thijs C. D.
Arbous, Sesmu
Fleuren, Lucas M.
Dam, Tariq A.
Tonutti, Michele
de Bruin, Daan P.
Elbers, Paul W. G.
CinĂ , Giovanni
Publication Year :
2021

Abstract

Despite the recent progress in the field of causal inference, to date there is no agreed upon methodology to glean treatment effect estimation from observational data. The consequence on clinical practice is that, when lacking results from a randomized trial, medical personnel is left without guidance on what seems to be effective in a real-world scenario. This article proposes a pragmatic methodology to obtain preliminary but robust estimation of treatment effect from observational studies, to provide front-line clinicians with a degree of confidence in their treatment strategy. Our study design is applied to an open problem, the estimation of treatment effect of the proning maneuver on COVID-19 Intensive Care patients.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2109.06707
Document Type :
Working Paper