Using Machine Learning to Identify Patients at High Risk of Inappropriate Drug Dosing in Periods with Renal Dysfunction.

Benjamin Skov Kaas-Hansen Cristina Leal Rodríguez Davide Placido Hans-Christian Thorsen-Meyer Anna Pors NielsenNicolas DérianSøren BrunakStig Ejdrup Andersen

Published in: Clinical epidemiology (2022)

Our models can flag patients at high risk of receiving at least one inappropriate dose daily in a controlled in-silico setting. A prospective clinical study may confirm that this holds in real-life settings and translates into benefits in hard endpoints.

Keyphrases

end stage renal disease
newly diagnosed
prognostic factors
physical activity
peritoneal dialysis
oxidative stress
emergency department
clinical trial
molecular docking
patient reported outcomes
adverse drug
patient reported