Mortality predictions in ICU patients with delirium show strong predictors like frailty and illness severity, suggesting tailored assessments may improve outcomes.
This article presents mortality prediction models for ICU patients with delirium that incorporate pre-admission functional status and apply several modern statistical learning approaches, providing an instructive and transparent example of contemporary prediction modeling. The resulting elastic net regression models showed fair discrimination and good calibration for predicting 90-day and 1-year mortality, with frailty, age, and illness severity emerging as the strongest predictors. However, such models should be interpreted cautiously at the individual patient level and may be most useful for identifying patients at increased risk who may benefit from careful clinical assessment, individualized treatment, and close follow-up.
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Poulsen et al. (2026) studied this question.
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