Effect of Music Interventions on Sedation in Children Undergoing Magnetic Resonance Imaging: Clinical Trial
Bibliographic record
Abstract
Background: Although parenteral sedation is often required in MRI studies in children, it is stressful and increases the cost of healthcare. Objectives: We evaluated the impact of music interventions in children receiving parenteral sedation for MRI studies on total number of doses of sedation medications, sedation time, levels of cortisol and cytokines, sedation success, adverse events, parental satisfaction, and cost savings. Methods: We conducted a prospective open unblinded four-arm clinical evaluation of interventions on 471 children 1-12 years of age undergoing MRI and receiving parenteral sedation. Children were assigned to active music therapy (AMT), facilitated music listening (FML), and as comparison another intervention (child life intervention or CLI), or no intervention (NI); measures included number of doses of sedation medications, time of sedation, sedation success, adverse events, parental satisfaction, and salivary levels of the stress hormone cortisol and pro-inflammatory cytokines, before and after intervention. Results: The total number of sedation doses, total sedation time, and levels of salivary cortisol and cytokines did not differ between the four groups. One FMLA choice, Wee Sing Animal Songs, resulted in significant decrease in total sedation time and reduction of associated costs. Conclusions: The use of one type of FML led to decreased total sedation time in children. This is an important finding since FML is an inexpensive non-invasive intervention which could be of significant time and cost saving benefits.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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) | 0.007 | 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; 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".