Clinical Assessment and Management of Delirium in the Palliative Care Setting
Bibliographic record
Abstract
Delirium is a neurocognitive syndrome arising from acute global brain dysfunction, and is prevalent in up to 42% of patients admitted to palliative care inpatient units. The symptoms of delirium and its associated communicative impediment invariably generate high levels of patient and family distress. Furthermore, delirium is associated with significant patient morbidity and increased mortality in many patient populations, especially palliative care where refractory delirium is common in the dying phase. As the clinical diagnosis of delirium is frequently missed by the healthcare team, the case for regular screening is arguably very compelling. Depending on its precipitating factors, a delirium episode is often reversible, especially in the earlier stages of a life-threatening illness. Until recently, antipsychotics have played a pivotal role in delirium management, but this role now requires critical re-evaluation in light of recent research that failed to demonstrate their efficacy in mild- to moderate-severity delirium occurring in palliative care patients. Non-pharmacological strategies for the management of delirium play a fundamental role and should be optimized through the collective efforts of the whole interprofessional team. Refractory agitated delirium in the last days or weeks of life may require the use of pharmacological sedation to ameliorate the distress of patients, which is invariably juxtaposed with increasing distress of family members. Further evaluation of multicomponent strategies for delirium prevention and treatment in the palliative care patient population is urgently required.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.001 |
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".