Utility of Screening for Cognitive Impairment at Hospital Discharge in Adult Survivors of Critical Illness
Bibliographic record
Abstract
BACKGROUND: Few studies have explored the utility of screening for cognitive impairment near hospital discharge in intensive care unit survivors. OBJECTIVES: To explore baseline and hospitalization characteristics associated with cognitive impairment at hospital discharge and the relationship between cognitive impairment and 6-month disability and mortality outcomes. METHODS: Hospital disability status and treatment variables were collected from 2 observational cohort studies. Patients were screened for cognitive impairment at hospital discharge using the Montreal Cognitive Assessment (MoCA)-Blind, and telephone follow-up was conducted 6 months after discharge to assess vital and physical disability status. RESULTS: Of 423 patients enrolled, 320 were alive at hospital discharge. A total of 213 patients (66.6%) were able to complete the MoCA near discharge; 47 patients (14.7%) could not complete it owing to cognitive impairment. In MoCA completers, the median (IQR) score was 17 (14-19). Older age (β per year increase, -0.09 [95% CI, -0.13 to -0.05]) and blood transfusions during hospitalization (β, -1.20 [95% CI, -2.26 to -0.14]) were associated with lower MoCA scores. At 6-month follow-up, 176 of 213 patients (82.6%) were alive, of whom 41 (23.3%) had new severe physical disabilities. Discharge MoCA score was not significantly associated with 6-month mortality (adjusted odds ratio, 1.03 [95% CI, 0.93-1.14]) but was significantly associated with risk of new severe disability at 6 months (adjusted odds ratio, 0.85 [95% CI, 0.76-0.94]). CONCLUSION: Assessing for cognitive impairment at hospital discharge may help identify intensive care unit survivors at higher risk of severe physical disabilities after critical illness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".