PTCohortJournal of rehabilitation medicine2026

Prognostic profiles for discharge destination identified during intensive care unit admission: a decision tree analysis.

Sho Otsubo, Daisuke Kawakami, Shota Okuno and 2 others

PMID 42159014

WHAT IT FOUND

Simple ICU variables identified discharge profiles.

APACHE II score under 20 with ICU stay under 8.3 days had 86% probability of home discharge. FSS-ICU below 5 with APACHE II 20 or higher had 18%.

Key findings

01In the 300 analysed ICU patients, the decision tree identified 5 profiles based on APACHE II score, ICU length of stay, FSS-ICU and age.

02The model with APACHE II score, FSS-ICU and age had an AUC of 0.77, sensitivity of 0.85 and specificity of 0.57.

03Patients with APACHE II score under 20 and ICU stay under 8.3 days had an 86% probability of home discharge, while patients with APACHE II score 20 or higher and FSS-ICU under 5 had an 18% probability.

STILL TO COME

How it was doneWhat they foundWhat it means for PTs

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What it does not show

Single centre historical study, so results may not apply to other ICUs or countries. No external validation was performed, so the profiles may be overfitted to this dataset. The decision tree produced 5 terminal nodes but only 3 broad prognostic groups, and cut-offs such as 8.3 days ICU stay should be read as probabilities, not strict thresholds. Missing data were common, including 130 cases for step lifts and 156 for home modifications, which may affect model stability. The study excluded patients who died or had non-independent pre-admission ADLs, so it does not apply to those groups. PT sessions were higher in the non-home discharge group, but this is observational and cannot show whether PT helped or reflected greater need. The model includes only recorded variables, and other social or functional factors may matter.

Declared interests

The authors declared no conflicts of interest. The funding statement does not name a funder.

The easy way to misread this

Do not use these profiles as a deterministic prediction for one patient. The study was single-centre, historical and not externally validated, and the cut-offs are probabilistic.

Summarised by AI from the full paper, without a clinician reviewing it. Check it against the source before it changes what you do. Read it on PubMed →