Reporting of outcomes and measures in studies of interventions to prevent and/or treat delirium in older adults resident in long-term care: a systematic review
Bibliographic record
Abstract
OBJECTIVES: to inform development of a core outcome set, we evaluated outcomes, definitions, measures and measurement time points in clinical trials of interventions to prevent and/or treat delirium in older adults resident in long-term care (LTC). DATA SOURCES: we searched electronic databases, systematic review repositories and trial registries (1980 to 10 December 2021). STUDY SELECTION AND DATA EXTRACTION: we included randomised, quasi-randomised and non-randomised intervention studies. We extracted data on study characteristics, outcomes and measurement features. We assessed outcome reporting quality using the MOMENT study scoring system. We categorised outcomes using the Core Outcome Measures in Effectiveness Trials taxonomy. DATA SYNTHESIS: we identified 18 studies recruiting 5,639 participants. All evaluated non-pharmacological interventions; most (16 studies, 89%) addressed delirium prevention. We identified 12 delirium-specific outcomes (mean [SD] 2.4 [1.5] per study), of which delirium incidence (14 studies, 78%) and severity (6 studies, 33%) were most common. We found heterogeneity in description of outcomes and measurement time points. The Confusion Assessment Method (three versions) was the most common measure used to ascertain delirium incidence (7 of 14 studies, 50%). We identified 25 non-delirium specific outcomes (mean [SD] 4.0 [2.3] per study), with hospital admission the most commonly reported (9 studies, 50%). CONCLUSIONS: we identified few studies of interventions for the prevention or treatment of delirium in older adults resident in LTC. These studies were heterogeneous in the outcomes reported and measures used. These data inform the consensus-building stage of a core outcome set.
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How this classification was reachedexpand
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 | 0.001 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".