English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

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

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