Anesthetic options for Rezūm water vapour therapy
Bibliographic record
Abstract
INTRODUCTION: There has been a rapid expansion of the armamentarium for managing benign prostatic hyperplasia (BPH). Due to the invasiveness and complication risks of traditional surgical management, minimally invasive procedures have emerged. Rezūm water vapor therapy is a safe, effective alternative. Given the minimally invasive nature, there is interest in administering conscious sedation over general anesthesia to decrease procedural times and costs and increase accessibility by completing procedures in an office-based setting. We sought to assess and describe patient-reported tolerability for Rezūm completed under oral and deep intravenous sedation. METHODS: Patients who underwent Rezūm between April and November of 2022 under conscious sedation with oral sedation and local anesthesia (OSLA) or deep intravenous sedation (DIS) were enrolled. Baseline information was collected, and followup interviews were conducted where patient tolerability scores, future anesthetic preferences, and complication data was prospectively obtained. RESULTS: Fourteen patients were enrolled in each group. The OSLA and DIS cohorts had a median tolerability score of 8 (interquartile range [IQR] 3.5) and 9 (IQR 1.75), respectively, indicating highly tolerable experiences. There was no significant difference between groups (p=0.13). On followup, 85.7% of patients in the OSLA and 100% in DIS groups expressed their future preference for conscious sedation over general anesthetic, with no significant difference between the two groups (p=0.46). CONCLUSIONS: Our study demonstrates OSLA and DIS are both viable conscious sedation methods for Rezūm, with patients reporting high tolerability to the procedure regardless of sedation choice. Almost all patients receiving conscious sedation would choose to undergo Rezūm using conscious sedation again and had minimal complications.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".