Music Decreases Sedative Requirements During Spinal Anesthesia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
UNLABELLED: Ambulatory surgery can create significant anxiety. This prospective study measured whether music can influence anxiety and perioperative sedative requirements in outpatients undergoing surgery with spinal anesthesia. We also evaluated the correlation between two anxiety measures, the State-Trait Anxiety Inventory test (STAI) and the 0- to 10-cm visual analog scale (VAS 0-10), with 0 meaning complete relaxation and 10 the worst feeling of anxiety possible. Fifty unpremedicated patients were randomly assigned to listen to music of their choice via headset during the perioperative period (Group I) or to have no music (Group II). All participants used patient-controlled IV midazolam sedation and underwent repeated evaluations of their anxiety level with the STAI and the VAS 0-10. Midazolam requirements during surgery (Group I, 0.6 +/- 0.7 versus Group II, 1.3 +/- 1.1 mg; P < 0.05) and for the whole perioperative period (Group I, 1.2 +/- 1.3 versus Group II, 2.5 +/- 2.0 mg; P < 0.05) were smaller in patients listening to music. Anxiety levels, measured with STAI or VAS 0-10, were similar in both groups. The Spearman's coefficient values between STAI and VAS 0-10 ranged from 0.532 to 0.687. We conclude that patients listening to music require less midazolam to achieve a similar degree of relaxation as controls and that measures of anxiety obtained from the STAI and the VAS 0-10 are positively, but only moderately, correlated. IMPLICATIONS: It is possible to decrease sedative requirements during surgery under spinal anesthesia by allowing patients to listen to music to reduce their anxiety.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 it