Efficacy of Local Anesthesia in the Face and Scalp: A Prospective Trial
Bibliographic record
Abstract
BACKGROUND: The use of local anesthesia has allowed for the excision and repair of lesions of the head and neck to be done in an office-based setting. There is a gap of knowledge on how surgeons can improve operative flow related to the onset of action. A prospective trial was undertaken to determine the length of time for full anesthesia effect in the head and neck regions. METHODS: Consecutive patients undergoing head and neck cutaneous cancer resection over a 3-month period were enrolled in the study. Local anesthesia injection and lesion excision were all done by a single surgeon. All patients received the standard of care of local anesthesia injection. RESULTS: > 0.05). Using the time to full anesthesia effect for each local injection, a heat map was generated to show the relative times of the face and scalp to achieve full effect. CONCLUSIONS: This prospective trial demonstrated that for the same local anesthetic and concentration, upper forehead and scalp lesions take significantly longer to anesthetize than other lesions in the lower face and ear. This can help surgeons tailor all aspects of their practice, which utilizes local anesthesia to help with patient satisfaction and operative flow.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".