Baby steps to mastery: building blocks for novices in pediatric regional anesthesia
Bibliographic record
Abstract
Pediatric regional anesthesia offers significant benefits, yet its adoption faces barriers, including perceived overcomplexity. This study aimed to identify and establish a set of core, high-value, low-complexity nerve blocks to improve perioperative pain management in pediatric patients. A four-round modified Delphi consensus study was conducted with an international panel of pediatric and regional anesthesia experts. An initial long list of regional techniques was compiled by the Steering Committee and refined through iterative input. Panelists rated each technique on a 10-point Likert scale for importance. Consensus was defined as ≥75% of panelists assigning a mean importance score of ≥8. Techniques receiving 50%-74% agreement were categorized as having strong agreement and considered for inclusion. The final selection was confirmed through a virtual roundtable discussion. Thirty-three experts representing 12 pediatric and regional societies participated. Consensus was reached on six regional techniques, with strong agreement (*) on two additional techniques, identifying eight core pediatric regional anesthesia blocks: supraclavicular brachial plexus block, rectus sheath block, transverse abdominis plane block*, suprainguinal fascia iliaca block*, femoral nerve block, adductor canal block, popliteal sciatic nerve block, and landmark-based caudal block. This consensus-driven framework defines a core set of pediatric regional anesthesia techniques that balance clinical effectiveness, feasibility, and accessibility. These findings provide a practical entry point for practitioners looking to incorporate pediatric regional anesthesia into their practice, regardless of prior experience. Future efforts should focus on standardized training, implementation research, and policy initiatives to support widespread adoption and improve perioperative pain management in children globally.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.041 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".