Delirium and long term cognition in critically ill patients
Bibliographic record
Abstract
Delirium, a form of acute brain dysfunction, is very common in the critically ill adult patient population. Although its pathophysiology is poorly understood, multiple factors associated with delirium have been identified, many of which are coincident with critical illness. To date, no drug or non-drug treatments have been shown to improve outcomes in patients with delirium. Clinical trials have provided a limited understanding of the contributions of multiple triggers and processes of intensive care unit (ICU) acquired delirium, making identification of therapies difficult. Delirium is independently associated with poor long term outcomes, including persistent cognitive impairment. A longer duration of delirium is associated with worse long term cognition after adjustment for age, education, pre-existing cognitive function, severity of illness, and exposure to sedatives. Interestingly, differences in prevalence are seen between ICU survivor populations, with survivors of acute respiratory distress syndrome experiencing higher rates of cognitive impairment at early follow-up compared with mixed ICU survivor populations. Although cognitive performance improves over time for some ICU survivors, impairment is persistent in others. Studies have so far been unable to identify patients at higher risk of long term cognitive impairment; this is an active area of scientific investigation.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.002 | 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".