De novo urethral stricture disease in renal transplant recipients
Bibliographic record
Abstract
Introduction: With routine catheterization and low urine output pre-transplant, renal transplant recipients (RTRs) may be at risk of urethral stricture disease post-transplant. The objective of this study was to characterize new urethral stricture disease in males following renal transplant. Methods: Retrospective chart review was carried out on all male RTRs at Vancouver General Hospital who developed urethral strictures from October 2009–2019. Descriptive analyses were conducted on patient characteristics. Comparative analyses against non-stricture RTRs were carried out. Results: Of 636 RTRs, 18 (2.8%) developed a postoperative urethral stricture. Median time from transplant to stricture discovery was 56 days (range 8–618 days). One-third of stricture patients had prior risk factors for stricture formation. Post-transplant, 77.8% presented symptomatically, with 61.1% requiring intervention. Overall graft survival rate was 88.9% among the RTR stricture group; 16.7% experienced acute rejection and 22.2% had delayed graft function (DGF). There was no significant association between developing postoperative urethral stricture and urinary tract infection (Chi-squared [X2]=0.04, p=0.84; odds ratio [OR] 0.81, 95% confidence interval [CI] 0.1–6.21), DGF (X2=0.14, p=0.70; OR 0.8, CI 0.26–2.48), or acute rejection (X2=2.02, p=0.14; OR 2.55, CI 0.71–9.12). Conclusions: De novo post-transplant urethral stricture rates appear to occur at a higher rate than the general population and contribute to patient morbidity. Stricture disease should be considered post-transplantation in patients with voiding dysfunction, even if they don’t have prior risk factors. Multicenter studies should be considered to elucidate any relationship between urethral stricture and graft survival.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".