Standardizing nomenclature in regional anesthesia: an ASRA-ESRA Delphi consensus study of abdominal wall, paraspinal, and chest wall blocks
Bibliographic record
Abstract
BACKGROUND: There is heterogeneity in the names and anatomical descriptions of regional anesthetic techniques. This may have adverse consequences on education, research, and implementation into clinical practice. We aimed to produce standardized nomenclature for abdominal wall, paraspinal, and chest wall regional anesthetic techniques. METHODS: We conducted an international consensus study involving experts using a three-round Delphi method to produce a list of names and corresponding descriptions of anatomical targets. After long-list formulation by a Steering Committee, the first and second rounds involved anonymous electronic voting and commenting, with the third round involving a virtual round table discussion aiming to achieve consensus on items that had yet to achieve it. Novel names were presented where required for anatomical clarity and harmonization. Strong consensus was defined as ≥75% agreement and weak consensus as 50% to 74% agreement. RESULTS: Sixty expert Collaborators participated in this study. After three rounds and clarification, harmonization, and introduction of novel nomenclature, strong consensus was achieved for the names of 16 block names and weak consensus for four names. For anatomical descriptions, strong consensus was achieved for 19 blocks and weak consensus was achieved for one approach. Several areas requiring further research were identified. CONCLUSIONS: Harmonization and standardization of nomenclature may improve education, research, and ultimately patient care. We present the first international consensus on nomenclature and anatomical descriptions of blocks of the abdominal wall, chest wall, and paraspinal blocks. We recommend using the consensus results in academic and clinical practice.
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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 | 0.403 | 0.320 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.003 |
| 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".