Relaxation for Critically ill Patient Outcomes and Stress-coping Enhancement (REPOSE): a protocol for a pilot randomised trial of an integrative intervention to improve critically ill patients’ delirium and related outcomes
Bibliographic record
Abstract
Introduction: Delirium is a common complication of critical illness, associated with negative patient outcomes. Preventive or therapeutic interventions are mostly ineffective. Although relaxation-inducing approaches may benefit critically ill patients, no well-designed studies target delirium prevention as a primary outcome. The objective of this study is to assess feasibility and treatment effect estimates of a multimodal integrative intervention incorporating relaxation, guided imagery and moderate pressure touch massage for prevention of critical illness delirium and for related outcomes. Methods and analysis: Randomised, controlled, single-blinded trial with two parallel groups (1:1 allocation: intervention and standard care) and stratified randomisation (age (18–64 years and ≥65 years) and presence of trauma) with blocking, involving 104 patients with Intensive Care Delirium Screening Checklist (ICDSC): 0–3 recruited from two academic intensive care units (ICUs). Intervention group participants receive the intervention in addition to standard care for up to five consecutive days (or until transfer/discharge); control group participants receive standard care and a sham intervention. We will assess predefined feasibility outcomes, that is, recruitment rates and protocol adherence. The primary clinical outcome is incidence of delirium (ICDSC ≥4). Secondary outcomes include pain scores, inflammatory biomarkers, heart rate variability, stress and quality of life (6 weeks and 4 months) post-ICU discharge. Feasibility measures will be analysed descriptively, and outcomes will be analysed longitudinally. Estimates of effects will be calculated. Ethics and dissemination: The study has received approval from the Human Research Ethics Board, University of Alberta. Results will inform the design of a future multicentre trial.
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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 | 0.030 | 0.027 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.044 | 0.008 |
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".