Patients Tracking Pain Episodes Show Wide-awake Local Anesthesia Without Tourniquet Can Be Nearly Painless
Bibliographic record
Abstract
Background: Minimally painful tumescent local anesthesia ensures patients feel only the first needle insertion, with no further pain. This technique includes real-time patient feedback, where they report each pain event during injection. Methods: This prospective study involved 154 consecutive patients undergoing wide-awake local anesthesia no tourniquet surgery at 3 hand surgery centers (January-April 2024). Patients objectively scored pain events during injection and rated pain intensity (0-10 Likert scale), intraoperative pain, anxiety, and overall experience. Results: During local anesthesia injection, 61 (40%) patients reported no pain, 92 (59.7%) reported 1 pain event, and 1 (0.7%) patient reported 2 events. Among the 93 patients who felt pain, 90 reported only mild discomfort (1-2 of 10), whereas 3 reported moderate pain (3-5 of 10). Anxiety levels during anesthesia and surgery were 3 of 10 or less for 147 (95.5%) patients. Conclusions: Real-time patient feedback improved surgeons' ability to administer tumescent local anesthesia with minimal pain. As a result, most patients experienced no pain or only 1 minor event during local anesthesia injection for wide-awake local anesthesia no tourniquet surgery.
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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 | 0.002 |
| 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) | 0.004 | 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".