First Robotic Ultrasound-Guided Nerve Blocks in Humans Using the Magellan System
Bibliographic record
Abstract
BACKGROUND: Ultrasound-guided nerve blocks are becoming a standard of modern anesthesia. We developed a robotic system, Magellan, to perform nerve blocks using a remote control center. METHODS: Thirteen patients were enrolled in this pilot study. The Magellan system consists of 3 main components: a joystick, a robotic arm, and a software control system. The joystick allows simulation of wrist or arm movements of the proceduralist. After localization of the sciatic nerve, 35 mL of bupivacaine 0.25% was injected. The success rate of sciatic nerve blocks and block performance times (performance time=interval of time from the start of the ultrasound search for the nerve to the end of the injection of the drug; robotic time=interval of time from the identification of the nerve to the end of the injection of the drug) were determined. Data are presented as median (25th, 75th; minimal, maximal) and categorical data. RESULTS: Eight men and 5 women aged 34 years were included in this study. Nerve blocks were successful in all patients. A successful attempt was defined as the introduction of the needle into the nerve sheath; motor or sensory block was not used to determine the success rate. The nerve performance time was 189 seconds (150, 233; 90, 305), whereas the robotic time was 164 seconds (121, 210; 73, 271). CONCLUSIONS: We present the first human testing of a robotic ultrasound-guided nerve block system. The success rate was 100%. The total performance time was approximately 3 minutes to 4 minutes.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".