Evolution of Clinical Phenotypes of COVID-19 Patients During Intensive Care Treatment: An Unsupervised Machine Learning Analysis.

Sander SiepelTariq A DamLucas M FleurenArmand R J GirbesMark HoogendoornPatrick J ThoralPaul W G ElbersFrank C Bennisnull null

Published in: Journal of intensive care medicine (2023)

Patients typically do not remain in the same cluster throughout intensive care treatment. This may have important implications for prognostic or predictive enrichment. Prominent dissimilarities between clinical phenotypes are predominantly driven by inflammation and dead space ventilation.

Keyphrases

machine learning
end stage renal disease
oxidative stress
ejection fraction
newly diagnosed
chronic kidney disease
prognostic factors
artificial intelligence
patient reported outcomes