Is it time to offer True Minimally Invasive Treatments (TMIST) for BPH? - A review of office-based therapies and introduction of a new technology category.
Bibliographic record
Abstract
INTRODUCTION The options for treating benign prostatic hyperplasia (BPH) beyond medication and traditional transurethral surgery continue to expand. Undesirable side effects to medication and surgeries have driven interest toward minimally invasive surgical therapies (MISTs), including convective water vapor ablation (Rezum) and prostatic urethral lift (UroLift). While these treatments can be performed outside of the operating room, they do require special equipment and the use of rigid cystoscopy. A new class of treatments, which utilize no special equipment beyond a flexible cystoscope are emerging, the first of which, the temporary implantable nitinol device (iTind) is already FDA approved. MATERIALS AND METHODS: A comprehensive review of the literature using PUBMED, EMBASE, Scopus focused on the two commercially available MISTs, Rezum and UroLift, was performed. Additionally, we evaluated the existing literature for the novel iTind. RESULTS: UroLift and Rezum have demonstrated significant improvements in validated questionnaires such as IPSS and IPSS QoL. They generally maintain erectile function (IIEF) and ejaculatory function (MSHQ). The short term recovery seems to slightly favor UroLift, while re-treatment rates seem to favor Rezum. The iTind also appears to improve subjective and objectives outcomes, though longer term follow up is still maturing. CONCLUSION: The currently available MISTs have changed the way we treat BPH, offering a middle ground for men between oral medial therapy and more invasive transurethral surgery. While these MIST treatments require specialized and costly equipment, the proposed a new category, the True Minimally Invasive Surgical Therapy, or TMIST, offers an off-the-shelf, affordable and comfortable solution for men suffering from LUTS secondary to BPH.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| 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".