Evidence Basis for the Use of Ultrasound for Upper-Extremity Blocks
Bibliographic record
Abstract
This article qualitatively assesses and summarizes randomized, controlled studies regarding benefits of ultrasound (US) for brachial plexus block and also examines those studies that have compared different brachial plexus block techniques using US.Studies were identified by a search of PUBMED and EMBASE databases using the MeSH terms anesthetic techniques, brachial plexus, and ultrasound. Included studies were limited to randomized trials that compared a US technique with another accepted method of performing brachial plexus block or those studies that compared 2 different US-guided techniques. Studies were further classified according to methodological quality using accepted methods. Quality scores were compared using Mann-Whitney U test, and significance assumed at P < 0.05.Twenty-five studies met inclusion criteria, with 19 studies comparing US techniques with other nerve location methods and 6 studies comparing different US techniques. Of the former, there was convincing evidence to support the use of US, with 15 of 19 studies demonstrating improved outcomes compared with existing techniques.Ultrasound provides significant advantages when performing brachial plexus block including faster sensory block onset and greater block success.
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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 | 0.016 | 0.075 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.003 | 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".