Ultrasound-Guided Supraclavicular Brachial Plexus Block
Bibliographic record
Abstract
UNLABELLED: In this study, we evaluated state-of-the-art ultrasound technology for supraclavicular brachial plexus blocks in 40 outpatients. Ultrasound imaging was used to identify the brachial plexus before the block, guide the block needle to reach target nerves, and visualize the pattern of local anesthetic spread. Needle position was further confirmed by nerve stimulation before injection. The block technique we describe aligned the needle path with the ultrasound beam. The block was successful after one attempt in 95% of the cases, with one failure attributable to subcutaneous injection and one to partial intravascular injection. Pneumothorax did not occur. Our preliminary data suggest that a high-resolution ultrasound probe can reliably identify the brachial plexus and its neighboring structures in the supraclavicular region. The technique of real-time guidance during needle advancement can quickly localize nerves. Distinct patterns of local anesthetic spread observed on ultrasound can further confirm accurate needle location. IMPLICATIONS: Real-time ultrasound imaging during supraclavicular brachial plexus blocks can facilitate nerve localization and needle placement and examine the pattern of local anesthetic spread.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".