Development of a core outcome set for clinical trials of interventions to improve sleep in people with cognitive impairment
Bibliographic record
Abstract
Abstract Background Although sleep disturbance is common among people with cognitive impairment, leading to negative outcomes, there is a paucity of evidence to inform management in this cohort. Existing clinical trials are marked by wide heterogeneity, both in the methods used to measure sleep and in the outcome measures reported, limiting data synthesis. A core outcome set (COS) would improve the coherence and reliability of data in future clinical trials. Methods A multi-stage mixed-methods approach was adopted in accordance with The Core Outcome Set-STAndards for Development: the COS-STAD recommendations. Results A systematic review identified 287 sleep outcome measures from previous clinical trials. Qualitative interviews revealed that people living with cognitive impairment and their caregivers are most concerned with improving overall sleep quality, reducing the time taken to fall asleep and night-time awakenings, and avoiding daytime sleepiness. Ultimately, a modified Delphi process, involving 41 experts in sleep and cognition from six different continents, selected nine outcome measures for the COS: total sleep time, sleep onset latency, wakefulness after sleep onset, number of night-time awakenings, sleep efficiency, and measures of subjective sleep quality, daytime sleepiness, cognition, and mood. The Delphi panel recommended that both subjective and objective measures be used to measure sleep outcomes over at least one week. Subjective sleep quality should be measured using a single Likert-type question. Acknowledging limitations, the Epworth Sleepiness Scale was recommended to measure daytime sleepiness, the Montreal Cognitive Assessment to monitor cognition and the Geriatric Depression Scale to assess mood. Conclusion This COS will support the conduct of future clinical trials of interventions to improve sleep in people with cognitive impairment by ensuring more reliable, comparable and coherent data. This will lead to a more robust evidence base to manage sleep disturbance and improve the care of people living with cognitive impairment.
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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 | 0.517 | 0.589 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.025 |
| Bibliometrics | 0.014 | 0.009 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".