Evaluating the Effect of a Sleep Prehabilitation Intervention in Patients Awaiting Elective Surgery: Protocol for a Single‐Blind Randomised Trial
Bibliographic record
Abstract
Adequate sleep health is critical for surgical recovery. Disrupted sleep can impede wound healing and cognitive performance and contribute to poor surgical outcomes. Preoperative intervention aimed at improving surgical outcomes is often referred to as prehabilitation and commonly uses exercise, nutrition or psychological intervention. Sleep prehabilitation interventions have not yet been studied. This randomised assessor-blinded trial will measure the effect of a personalised sleep prehabilitation (PSP) intervention in addition to standard of care prehabilitation (PREHAB) on participant sleep health compared to PREHAB alone (Clinicaltrials.gov ID: NCT06762639). One hundred fifty-four English-speaking patients from the University Health Network's Prehabilitation Program with sleep disturbance and a surgery within 4-12 weeks will be recruited. Patients will be excluded if they are participating in PREHAB remotely, have an existing sleep disorder, are a shift worker, have travel plans outside of their usual time zone or have a cognitive disability that precludes participation. Study assessments occur at baseline, 1 week before surgery and 6 weeks after surgery. PREHAB consists of individualised exercise and nutrition support as well as psychological intervention. The PSP consists of a baseline sleep assessment, brief behavioural treatment for insomnia (BBTI), sleep hygiene and behaviour-change support. The primary outcome is the Pittsburgh Sleep Quality Index (PSQI). The primary analysis will be an ANCOVA to detect differences in PSQI between groups 1 week before surgery whilst controlling for baseline scores. The proposed study will be the first to explore the effect of a personalised preoperative sleep intervention.
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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 | 0.035 | 0.066 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads 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".