Development of a core outcome set for clinical trials of interventions to improve sleep in people with cognitive impairment‐the Sleep in Cognitive Impairment Core Outcome Set (SCICOS)
Bibliographic record
Abstract
INTRODUCTION: Sleep disturbances are common in older people with cognitive impairment, potentially contributing to negative outcomes. A core outcome set (COS) is required to reduce heterogeneity in clinical trials and promote the development of high-quality evidence to support clinical management. METHODS: A multi-stage mixed methods study was conducted in accordance with The Core Outcome Set Standards for Development. RESULTS: A systematic review identified 287 sleep outcomes from previous clinical trials. Qualitative interviews ensured the COS was informed by what matters most to people with cognitive impairment and their caregivers. A modified Delphi process identified nine outcomes for the COS: total sleep time, sleep onset latency, wakefulness after sleep onset, number of night-time awakenings, sleep efficiency, and measures of sleep quality, daytime sleepiness, cognition, and mood. DISCUSSION: This COS will support researchers to produce more reliable and coherent trial data to guide the management of sleep disturbances in people with neurodegenerative cognitive impairment. HIGHLIGHTS: Evidence is lacking regarding the treatment of sleep disturbances in people with cognitive impairment. Heterogeneity of reported outcomes in clinical trials limits data synthesis. A qualitative analysis established what matters most to people with cognitive impairment and their caregivers when determining treatment effectiveness. A Delphi panel of experts agreed upon a core outcome set. This core outcome set will improve the reliability and comparability of data from future trials.
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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 | 0.359 | 0.440 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.017 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".