Waterjet Ablation Therapy for Endoscopic Resection of prostate tissue trial (WATER) vs WATER II: comparing Aquablation therapy for benign prostatic hyperplasia in 30–80 and 80–150 mL prostates
Bibliographic record
Abstract
OBJECTIVE: To compare the outcomes of Aquablation in 30-80 mL prostates with those in 80-150 mL prostates. Surgical options, especially with short learning curves, are limited when treating large prostates for lower urinary tract symptoms (LUTS) due to benign prostatic hyperplasia (BPH). Aquablation (AquaBeam System, PROCEPT BioRobotics Inc., Redwood City, CA, USA) could solve this issue with global reproducibility, independent of prostate volume. PATIENTS AND METHODS: Waterjet Ablation Therapy for Endoscopic Resection of prostate tissue (WATER [W-I]; NCT02505919) is a prospective, double-blind, multicentre, international clinical trial comparing Aquablation and transurethral resection of the prostate (TURP) for the treatment of LUTS/BPH in prostates between 30 and 80 mL. WATER II (W-II; NCT03123250) is a prospective, multicentre, single-arm international clinical trial of Aquablation in prostates between 80 and 150 mL. We compare baseline parameters and 12-month outcomes in 116 W-I and 101 W-II study patients. Students' t-test or Wilcoxon tests were used for continuous variables and Fisher's test for binary variables. RESULTS: The mean (SD) operative time was 33 (17) and 37 (13) min in W-I and W-II, respectively. Actual treatment time was 4 and 8 min in W-I and W-II, respectively. The mean change in the International Prostate Symptom Score was substantial averaging (at 12 months) 15.1 in W-I and 17.1 in W-II (P = 0.605). By 3 months, Clavien-Dindo grade ≥II events occurred in 19.8% of W-I patients and 34.7% of W-II patients (P = 0.468). CONCLUSION: Aquablation clinically normalises outcomes between patients with 30-80 mL prostates and patients with 80-150 mL prostates treated for LUTS/BPH, with an expected increase in the risk of complications in larger prostates. Long-term outcomes of procedure durability are needed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".