Ultrasound guidance showing real-time local anesthetic extravasation during injection of two lateral popliteal sciatic nerve blocks
Bibliographic record
Abstract
Objective: The purpose of this case report is to describe an observation of local anesthetic extravasation while performing single-shot lateral sciatic popliteal blocks on two patients using ultrasound guided imaging. This under-reported phenom- enon may have clinical implications and warrants further examination of conventional practice techniques. Case report: We performed lateral sciatic popliteal blocks under ultrasound guidance for post-operative pain in two patients having surgery in the left lower extremity. Both blocks involved sequential, real-time scans during the injection beneath the complex fascial sheath of the sciatic nerve. Observations included extrafascial extravasation of local anesthetic away from the nerve, up the needle path, and also concentrically outside the nerve sheath. Both blocks had 100% sensory block but slower clinical onset than expected. Conclusions: Ultrasound imaging is an evolving technology gaining popularity for performing peripheral nerve blocks. The incidence and volume of local anesthetic extravasation with single shot nerve blocks are unknown. This phenomenon may be common but frequently undetected given the limited resolution and the two-dimensional nature of current ultrasound imaging technology. The clinical consequences of local anesthetic injection into tissues outside of the nerve sheath are unknown, however our observations suggest speed of onset and quality of blocks may be affected. Further investigation evaluating the extravasation of local anesthetics during ultrasound blockade is needed to re-evaluate injection speeds and the use of conventional volumes for injection.
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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 | 0.000 | 0.003 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".