Probabilistic analysis of COVID-19 patients' individual length of stay in Swiss intensive care units.

Alexander HenziGian-Reto KlegerMatthias Peter HiltyPedro D Wendel GarciaJohanna F Ziegelnull null

Published in: PloS one (2021)

A new probabilistic model permits calibrated and informative probabilistic prediction of LoS of individual patients with COVID-19. Long staying patients could be discovered early. The model may be the basis to simulate stochastic models for bed occupation in intensive care units under different casemix scenarios.

Keyphrases

intensive care unit
end stage renal disease
ejection fraction
newly diagnosed
chronic kidney disease
sars cov
climate change
prognostic factors
peritoneal dialysis
patient reported outcomes
acute respiratory distress syndrome