Surgeons Can Decrease the Pain of WALANT Local Anesthesia Injection if They Ask for Patient Feedback
Bibliographic record
Abstract
Introduction: Some patients who are having WALANT (Wide Awake Local Anesthesia No Tourniquet) carpal tunnel surgery are afraid of the pain of local anesthesia injection. Many surgeons do not yet focus on minimally painful injection techniques to avoid unnecessary painful patient experiences. This study measured the number of local anesthetic injection pain events in feedback from patients to the injecting surgeon to decrease the pain of his injections. Methods: A single surgeon asked 250 consecutive carpal tunnel surgery patients to tell him each time they felt a pain event during his local anesthetic injection process for WALANT carpal tunnel surgery. The pain events were counted and provided an objective pain number to score the surgeon’s injection skill over the 35 months of the study. Results: The surgeon's injection pain score improved dramatically over the time of the study. In his last 50 patients, he scored a hole-in-one 37 times, where none of his first 50 patients gave him such a high score. A hole-in-one happens when the only pain the patient feels is the small sting of the first 27 gauge needle insertion. Conclusions: Surgeons who inject local anesthesia for carpal tunnel surgery can ask patients to tell them each time they feel a pain event after the sting of the first needle insertion is numbed. Counting the number of pain events provides a score for each injection process. This score from immediate patient feedback can help the surgeons decrease the pain of their injections.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".