Delirium prevention in terminal cancer: assessment of a multicomponent intervention
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Delirium is a highly prevalent and deleterious disorder in terminally ill cancer patients. We assessed whether a multicomponent preventive intervention was effective in decreasing delirium incidence and severity among cancer patients receiving end-of-life care. METHODS: A cohort of 1516 patients was followed from admission to death at seven Canadian palliative care centers. In two of these centers, routine care included a delirium preventive intervention targeting physicians (written notice on selective delirium risk factors and inquest on intended medication changes), patients, and their family (orientation to time and place, information about early delirium symptoms). Delirium frequency and severity were compared between patients at the intervention (N = 674) and usual-care (N = 842) centers based on thrice-daily symptom assessments with the Confusion Rating Scale. RESULTS: The overall rate of adherence to the intervention was 89.7%. The incidence of delirium was 49.1% in the intervention group, compared with 43.9% in the usual-care group (odds ratio [OR] 1.23, P = 0.045). When confounding variables were controlled for, no difference was observed between the intervention and the usual-care groups in delirium incidence (OR 0.94, P = 0.66), delirium severity (1.83 vs. 1.92; P = 0.07), total days in delirium (4.57 vs. 3.57 days; P = 0.63), or duration of first delirium episode (2.9 vs. 2.1 days; P = 0.96). Delirium-free survival was similar in the two groups. CONCLUSION: A simple multicomponent preventive intervention was ineffective in reducing delirium incidence or severity among cancer patients receiving end-of-life care. Delirium prevention remains a difficult challenge in terminally ill cancer patients.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it