Editorial Comment from Dr Rourke to Risk of urethral stricture recurrence increases over time after urethroplasty
Bibliographic record
Abstract
Although urethroplasty is well established as the most efficacious treatment for urethral stricture, it (like everything else in the world) is not perfect. Stricture recurrence after urethroplasty is a reality, even in the most experienced and capable hands. The present article by Han et al. examines risk factors for stricture recurrence in a cohort of 227 patients undergoing anterior urethroplasty with a mean follow up of 62 months.1 Patients with radiation or pelvic facture-related stenosis as well as panurethral strictures were excluded from the study. In this series, 26% of patients experienced stricture recurrence during follow up. Multivariate analysis identified prior urethroplasty and follow up greater than 48 months as risk factors for stricture recurrence. Strictures associated with lichen sclerosus were additionally very close to achieving significance as a risk factor. The exclusion of “panurethral” strictures involving portions of both the penile and bulbar urethra could have unintentionally contributed to the underestimation of stricture length and lichen sclerosus as a risk factor for stricture recurrence. The underlying basis for stricture recurrence after urethroplasty remains poorly understood. This is in part related to a lack of literature on the subject. However, there has been inconsistency regarding which factors are associated with stricture recurrence after urethroplasty, even in studies carrying out multivariate analysis. The factors most often associated with stricture recurrence (in descending order) are prior procedures (urethroplasty or endoscopic), stricture length, smoking and lichen sclerosus.2-4 These risk factors, however, are found in less than half of the studies on the subject. Other occasionally identified factors include diabetes, the use of penile skin grafts, surgical technique (anastomotic urethroplasty), hypospadias, poor oral hygiene and surgeon experience.5, 6 Some of the inconsistency can be explained by the fact that no studies have examined a comprehensive list of all known potential confounding variables, which increases the risk of underestimating or overestimating the association between a given variable and treatment outcome. Additionally, many studies are simply not statistically powered to examine all potential risk factors, and a significant association with more factors might have been found if studies had greater statistical power. Inconsistencies in the literature could also be related to surgeon preference for variations in urethroplasty technique, discrepancies in stricture etiology related to regional patterns and the duration of follow up preferred by the surgeon. Although many surgeons feel that the majority of stricture recurrences occur within 2 years of surgery, this might be an artifact of limited or inconsistent patient follow up. If patients are followed over a longer time-period, it is likely that more recurrences will be detected. It makes intuitive sense that stricture recurrence can occur at any time-point after urethroplasty. This study by Han et al. further emphasizes this logic. Patients at increased risk for stricture recurrence after urethroplasty should be counseled accordingly and every effort should be made to achieve regular follow up for these patients. None declared.
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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 | 0.000 | 0.004 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 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".