Music Use for Sedation in Critically ill Children (MUSiCC trial): a pilot randomized controlled trial
Bibliographic record
Abstract
OBJECTIVE: To demonstrate feasibility of a music medicine intervention trial in pediatric intensive care and to obtain information on sedation and analgesia dose variation to plan a larger trial. MATERIAL AND METHODS: Pilot randomized controlled trial (RCT) was conducted at the Stollery Children's Hospital general and cardiac intensive care units (PICU/PCICU). The study included children 1 month to 16 years of age on mechanical ventilation and receiving sedation drugs. Patients were randomized in a 1:1:1 ratio to music, noise cancellation or control. The music group received classical music for 30 min three times/day using headphones. The noise cancellation group received the same intervention but with no music. The control group received usual care. RESULTS: A total of 60 patients were included. Average enrollment rate was 4.8 patients/month, with a consent rate of 69%. Protocol adherence was achieved with patients receiving > 80% of the interventions. Overall mean (SD) daily Sedation Intensity Score was 52.4 (30.3) with a mean (SD) sedation frequency of 9.75 (7.21) PRN doses per day. There was a small but statistically significant decrease in heart rate at the beginning of the music intervention. There were no study related adverse events. Eighty-eight percent of the parents thought the headphones were comfortable; 73% described their child more settled during the intervention. CONCLUSIONS: This pilot RCT has demonstrated the feasibility of a music medicine intervention in critically ill children. The study has also provided the necessary information to plan a larger trial.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".