Standardizing nomenclature in regional anesthesia: an ASRA-ESRA Delphi consensus study of upper and lower limb nerve blocks
Bibliographic record
Abstract
BACKGROUND: Inconsistent nomenclature and anatomical descriptions of regional anesthetic techniques hinder scientific communication and engender confusion; this in turn has implications for research, education and clinical implementation of regional anesthesia. Having produced standardized nomenclature for abdominal wall, paraspinal and chest wall regional anesthetic techniques, we aimed to similarly do so for upper and lower limb peripheral nerve blocks. METHODS: We performed a three-round Delphi international consensus study to generate standardized names and anatomical descriptions of upper and lower limb regional anesthetic techniques. A long list of names and anatomical description of blocks of upper and lower extremities was produced by the members of the steering committee. Subsequently, two rounds of anonymized voting and commenting were followed by a third virtual round table to secure consensus for items that remained outstanding after the first and second rounds. As with previous methodology, strong consensus was defined as ≥75% agreement and weak consensus as 50%-74% agreement. RESULTS: A total of 94, 91 and 65 collaborators participated in the first, second and third rounds, respectively. We achieved strong consensus for 38 names and 33 anatomical descriptions, and weak consensus for five anatomical descriptions. We agreed on a template for naming peripheral nerve blocks based on the name of the nerve and the anatomical location of the blockade and identified several areas for future research. CONCLUSIONS: We achieved consensus on nomenclature and anatomical descriptions of regional anesthetic techniques for upper and lower limb nerve blocks, and recommend using this framework in clinical and academic practice. This should improve research, teaching and learning of regional anesthesia to eventually improve patient care.
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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 | 0.444 | 0.321 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.004 |
| 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".