Benign prostatic hyperplasia surgical re-treatment after prostatic urethral lift
Bibliographic record
Abstract
INTRODUCTION: Prostatic urethral lift (PUL) accounts for approximately one-quarter of all surgical benign prostatic hyperplasia (BPH) procedures performed in the U.S. Within five years of a patient's PUL procedure, approximately 1/7 patients will require surgical BPH retreatment. We aimed to highlight the evidence of surgical BPH retreatment modalities after PUL, with a focus on safety, short-term efficacy, durability, and relative costs. METHODS: A literature review was performed using PubMed, and an exhaustive review of miscellaneous online resources was completed. The search was limited to English, human studies. Citations of relevant studies were reviewed. RESULTS: No study has examined the efficacy, safety, or durability of transurethral resection of the prostate (TURP) or repeat PUL in the post-PUL setting. Recently, groups have examined laser enucleation (n=81), water vapor thermal therapy (WVTT) (n=5), robotic simple prostatectomy (SP) (n=2), and prostatic artery embolization (PAE) (n=1) in the post-PUL setting. Holmium enucleation of the prostate (HoLEP) after PUL appears to be safe and has similar functional outcomes to HoLEP controls. Other treatment modalities examined appear safe but have limited efficacy evidence supporting their use. Photo-selective vaporization of the prostate (PVP) and robotic waterjet treatment (RWT) have no safety or efficacy studies to support their use in the post-PUL setting. CONCLUSIONS: Despite increasing numbers of patients expected to require surgical retreatment after PUL in North America, there is currently limited evidence and a lack of recommendations guiding the evaluation and management of these patients. HoLEP is associated with the strongest evidence to support its use in the post-PUL setting.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".