Outcomes following inguinal and subinguinal urologic procedures under deep intravenous sedation
Bibliographic record
Abstract
INTRODUCTION: We aimed to investigate the surgical outcomes following inguinal and subinguinal urologic procedures under deep intravenous sedation (DIVS) with multimodal local anesthesia (LA). METHODS: We conducted a retrospective cohort study from September 2022 to December 2023 including adult patients deemed eligible for day surgery (American Society of Anesthesiologist score 1-3) undergoing radical orchiectomy (RO), microscopic varicocelectomy (MV), or microscopic denervation of the spermatic cord (MDSC). All procedures were performed at a single urologic ambulatory surgical center and outpatient clinic, and by a single surgeon (PP). Procedures were performed through a subinguinal or inguinal approach with DIVS and adjunctive multimodal LA. We evaluated intraoperative complications and relevant surgical outcomes and parameters. RESULTS: A total of 103 patients were included in the analysis with a mean age ± standard deviation of 37.3±9.6. This included 25 patients who underwent RO, 54 patients who underwent MV, and 24 patients who underwent MDSC. All procedures were completed successfully without intraoperative complications. Oncologic outcomes were preserved, fertility outcomes improved, and pain scores reduced similarly to the expected rates in the literature. CONCLUSIONS: Our preliminary results demonstrate the safety, effectiveness, and feasibility of performing inguinal and subinguinal urologic procedures under DIVS with LA. These findings suggest that this technique preserves high-quality care while avoiding the unnecessary risks of general or spinal anesthesia, representing an opportunity to transfer these cases outside of hospitals' operating rooms into outpatient ambulatory centers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".