A Core Outcome Set for Interventions to Prevent and/or Treat Delirium in Palliative Care
Bibliographic record
Abstract
CONTEXT: Delirium is a serious neurocognitive syndrome which is highly prevalent in people approaching the end of life. Existing trials of interventions to prevent or treat delirium in adults receiving palliative care report heterogeneous outcomes. OBJECTIVES: To undertake an international consensus process to develop a core outcome set for trials of interventions, designed to prevent and/or treat delirium, for adults receiving palliative care. METHODS: The core outcome set development process included a systematic review, qualitative interviews, modified Delphi method and virtual consensus meetings using nominal group technique (Registration http://www.comet-initiative.org/studies/details/796). Participants included family members, clinicians, and researchers with experience of delirium in palliative care. RESULTS: Forty outcomes were generated from the systematic review and interviews informing the Delphi Round one survey. The international Delphi panel comprised 92 participants including clinicians (n = 71, 77%), researchers (n = 13, 14%), and family members (n = 8, 9%). Delphi Round two was completed by 77 (84%) participants from Round one. Following the consensus meetings, four outcomes were selected for the core outcome set: 1) delirium occurrence (incidence and prevalence); 2) duration of delirium until resolution defined as either no further delirium in this episode of care or death; 3) overall delirium symptom profile (agitation, delusions or hallucinations, delirium symptoms and delirium severity); 4) distress due to delirium (person with delirium, and/or family and/or carers [including healthcare professionals]). CONCLUSION: Using a rigorous consensus process, we developed a core outcome set comprising four delirium-specific outcomes for inclusion in future trials of interventions to prevent and/or treat delirium in palliative care.
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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 | 0.240 | 0.332 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.016 |
| Bibliometrics | 0.014 | 0.009 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".