Kaplan-Meier curves and logistic models are widely used to describe and explain the variability of survival in intensive care unit (ICU) patients. The Kaplan-Meier approach considers that patients discharged alive from hospital are 'non-informatively' censored (for instance, representative of all other individuals who have survived to that time but are still in hospital); this is probably wrong. Logistic models are adapted to this so-called 'competing risks' setting but fail to take into account censoring and differences in exposure time. To address these issues, we exemplified the usefulness of standard competing risks methods; namely, cumulative incidence function (CIF) curves and the Fine and Gray model.
Resche-Rigon, M., Azoulay, E., & Chevret, S. (2005). Evaluating mortality in intensive care units: Contribution of competing risks analyses. Critical Care, 10(1). https://doi.org/10.1186/cc3921