Is the Bulbar Urethral Stricture a Single and Uniform Disease?
Bibliographic record
Abstract
Objectives: Proximal and distal bulbar urethral strictures (BUS) have different disease characteristics and require different treatment strategies despite being regarded as a single condition. To clarify the differences, we analyzed our database by distinguishing the two types of BUS. Methods: We retrospectively reviewed the data of 196 patients with BUS who underwent urethroplasty at the National Defense Medical College (Japan) between August 2004 and March 2022. We divided patients into proximal (group 1) or distal (group 2) groups based on the stricture segment and compared patient background and surgical techniques for each group. We assessed whether the stricture segment was an independent predictive factor for substitution urethroplasty selection using multivariate logistic regression analysis. The recurrence rates were calculated and compared using the Kaplan–Meier method and log-rank test, respectively. Results: Patients in group 1 had a less frequent non-obliterated lumen (73% vs. 94%, p = 0.020) and significantly shorter strictures (10 mm vs. 23 mm, p < 0.001) more frequently caused by external traumas (47% vs. 26%, p = 0.010) than those in group 2. Logistic regression analysis revealed that the stricture segment (distal) (p < 0.001), stricture length (≥20 mm) (p < 0.001), ≥2 prior transurethral procedures (p = 0.030), and a non-obliterated lumen (p = 0.020) were independent predictive factors for substitution urethroplasty. However, the recurrence rate (p = 0.18) did not significantly differ between the two groups. Conclusions: Proximal and distal BUS have substantially different anatomical characteristics and etiologies and require different reconstructive techniques.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".