Defining the Reliability of Sonoanatomy Identification by Novices in Ultrasound-Guided Pediatric Ilioinguinal and Iliohypogastric Nerve Blockade
Bibliographic record
Abstract
BACKGROUND: The ilioinguinal (II)/iliohypogastric (IH) nerve block is a safe, frequently used block that has been improved in efficacy and safety by the use of ultrasound guidance. We assessed the frequency with which pediatric anesthesiologists with limited experience with ultrasound-guided regional anesthesia could correctly identify anatomical structures within the inguinal region. Our primary outcome was to compare the frequency of correct identification of the transversus abdominis (TA) muscle with the frequency of correct identification of the II/IH nerves. We used 2 ultrasound machines with different capabilities to assess a potential equipment effect on success of structure identification and time taken for structure identification. METHODS: Seven pediatric anesthesiologists with <6 mo experience with ultrasound-guided regional anesthesia performed a total of 127 scans of the II region in anesthetized children. The muscle planes and the II and IH nerves were identified and labeled. The ultrasound images were reviewed by a blinded expert to mark accuracy of structure identification and time taken for identification. Two ultrasound machines (Sonosite C180plus and Micromaxx, both from Sonosite, Bothell, WA) were used. RESULTS: There was no difference in the frequency of correct identification of the TA muscle compared with the II/IH nerves (chi(2) test, TA versus II, P = 0.45; TA versus IH, P = 0.50). Ultrasound machine selection did show a nonsignificant trend in improving correct II/IH nerve identification (II nerve chi(2) test, P = 0.02; IH nerve chi(2) test, P = 0.04; Bonferroni corrected significance 0.17) but not for the muscle planes (chi(2) test, P = 0.83) or time taken (1-way analysis of variance, P = 0.07). A curve of improving accuracy with number of scans was plotted, with reliability of TA recognition occurring after 14-15 scans and II/IH identification after 18 scans. CONCLUSIONS: We have demonstrated that although there is no difference in the overall accuracy of muscle plane versus II/IH nerve identification, the muscle planes are reliably identified after fewer scans of the inguinal region. We suggest that a reliable end point for the inexperienced practitioner of ultrasound-guided II/IH nerve block may be the TA/internal oblique plane where the nerves are reported to be found in 100% of cases.
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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 | 0.006 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".