Next-gen minimally invasive surgical therapies for benign prostatic hyperplasia: innovations, selection, and best practices- a review from European Association of Urology endourology
Bibliographic record
Abstract
PURPOSE OF REVIEW: The expanding range of minimally invasive surgical therapies (MISTs) for benign prostatic hyperplasia (BPH) reflects a growing emphasis on individualized, anatomy-driven treatment that prioritizes symptom relief, reduced morbidity, and preservation of sexual function. This review provides a timely synthesis of MISTs, highlighting innovations in technique, key anatomical considerations, and evolving strategies for patient-centered care in the modern clinical setting. RECENT FINDINGS: Recent studies highlight the expanding role of MISTs, such as UroLift, Rezūm, the temporary implanted nitinol device, Optilume BPH, transperineal laser ablation, and prostatic stents. Each modality shows distinct performance characteristics depending on factors such as prostate volume, intravesical prostatic protrusion, bladder neck configuration, and the presence of a median lobe. Increasing attention has also been given to preserving antegrade ejaculation, which is often a high priority for younger or sexually active patients. Concurrently, new decision aid tools are in development to support shared decision-making in concordance with patient values and treatment preferences. SUMMARY: MISTs represent a diverse and maturing set of therapeutic options. Optimizing their use requires detailed anatomical assessment and thoughtful, individualized decision-making to align treatment with patient goals, preserve function, minimize morbidity, and reflect contemporary evidence-based standards in BPH management.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".