Defining minimal invasive surgical therapy for benign prostatic obstruction surgery: Perspectives from a global knowledge, attitude, and practice survey
Bibliographic record
Abstract
Objective: To scrutinize the definitions of minimal invasive surgical therapy (MIST) and to investigate urologists' knowledge, attitudes, and practices for benign prostatic obstruction surgeries. Methods: A 36-item survey was developed with a Delphi method. Questions on definitions of MIST and attitudes and practices of benign prostatic obstruction surgeries were included. Urologists were invited globally to complete the online survey. Consensus was achieved when more than or equal to 70% responses were "agree or strongly agree" and less than or equal to 15% responses were "disagree or strongly disagree" (consensus agree), or when more than or equal to 70% responses were "disagree or strongly disagree" and less than or equal to 15% responses were "agree or strongly agree" (consensus disagree). Results: =332, 57.2%). Consensus in the knowledge section was achieved for the superiority of Urolift®, Rezum®, and iTIND® over transurethral resection of the prostate with regard to blood loss, recovery, day surgery feasibility, and post-operative continence. Consensus in the attitudes section was achieved for the superiority of Urolift®, Rezum®, and iTIND® over transurethral resection of the prostate with regard to blood loss, recovery, and day surgery feasibility. Consensus on both sections was achieved for EEP as the option with the better symptoms and flow improvement, lower retreatment rate, and better suitable for prostate more than 80 mL. Conclusion: Minimal blood loss, fast post-operative recovery, and short hospital stay were the most important qualities for defining MIST. Urolift®, Rezum®, and EEP were regarded as MIST by most urologists.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".