Outcomes and measures of delirium interventional studies in palliative care to inform a core outcome set: A systematic review
Bibliographic record
Abstract
Background: Trials of interventions for delirium in various patient populations report disparate outcomes and measures but little is known about those used in palliative care trials. A core outcome set promotes consistency of outcome selection and measurement. Aim: To inform core outcome set development by examining outcomes, their definitions, measures and time-points in published palliative care studies of delirium prevention or treatment delirium interventions. Design: Prospectively registered systematic review adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Data sources: We searched six electronic databases (1980–November 2020) for original studies, three for relevant reviews and the International Clinical Trials Registry Platform for unpublished studies and ongoing trials. We included randomised, quasi-randomised and non-randomised intervention studies of pharmacological and non-pharmacological delirium prevention and/or treatment interventions. Results: From 13/3244 studies (2863 adult participants), we identified 9 delirium-specific and 13 non-delirium specific outcome domains within eight Core Outcome Measures in Effectiveness Trials (COMET) taxonomy categories. There were multiple and varied outcomes and time points in each domain. The commonest delirium specific outcome was delirium severity ( n = 7), commonly using the Memorial Delirium Assessment Scale (6/8 studies, 75%). Four studies reported delirium incidence. Non-delirium specific outcomes included mortality, agitation, adverse events, other symptoms and quality of life. Conclusion: The review identified few delirium interventions with heterogeneity in outcomes, their definition and measurement, highlighting the need for a uniform approach. Findings will inform the next stage to develop consensus for a core outcome set to inform delirium interventional palliative care research.
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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 | 0.049 | 0.194 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.017 |
| Bibliometrics | 0.022 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".