Efficacy of EMLA for Office-based Andrology Procedures Under Local Anesthesia: A Randomized Control Trial
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effectiveness of Eutectic Mixture of Local Anesthetic (EMLA), a topical anesthetic cream, in office-based invasive andrological procedures such as hydrocelectomy, spermatocelectomy, and others, aimed at minimizing pain perception and enhancing the overall patient experience. METHODS: A double-blinded randomized controlled trial was conducted for patients undergoing scrotal andrology surgeries under LA. Power calculation was performed with an estimated sample size of 72. Participants were randomly assigned in a 1:1 ratio to topical EMLA + LA versus LA alone. In the post-operative recovery area, patient will be asked to complete a VAS questionnaire rating pain with LA administration and pain with procedure. Analysis comparing VAS pain scores of both groups was performed using the independent sample t-test method. RESULTS: Seventy-two patients were included in our analysis, with 36 in the control and 36 in the intervention arm. For patient pain with administration of LA, the control arm reported an average VAS pain score of 4.31, compared to 3.72 in the intervention arm (P = .319). For patient pain with procedure, patients in the control arm reported a median VAS pain score of 3.47 compared to 3.03 (P = .432) in the intervention arm. Overall, 86% (62/72) of patients reported that they would either be "very likely" (4/5) or "highly likely" (5/5) to undergo future procedures under local anesthetic. CONCLUSION: While performing scrotal surgeries under LA appears to be well tolerated and a feasible option, the application of EMLA cream does not appear to significantly alter patient-reported outcomes.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".