Putting Patients Ahead by Leaving Nothing Behind: An Emerging Treatment Paradigm in Minimally Invasive Surgical Therapy for Benign Prostatic Hyperplasia
Bibliographic record
Abstract
Lower urinary tract symptoms (LUTS) secondary to benign prostatic hyperplasia (BPH) are highly prevalent in older men. The long-term clinical utility of lifestyle modification and oral medications for LUTS is limited. There is a great clinical need for safe, effective, and durable BPH therapies for men who unsuccessfully attempt conservative measures. Enthusiasm for transurethral resection of the prostate has declined due to surgical risk, high rates of postoperative sexual dysfunction, and the perceived invasive nature therein. Consequently, interest has grown in developing minimally invasive surgical treatments (MISTs) that are efficacious but with a more favorable risk profile in order to better align with patient preferences. This review evaluates currently available MISTs for BPH. Further, we critically examine a "Leave Nothing Behind" philosophy in MIST for BPH since implantation of permanent metallic devices may be associated with increased long-term failure rates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".