Triamcinolone acetonide injections for the treatment of recalcitrant post-radical prostatectomy vesicourethral anastomotic stenosis: A retrospective look at efficacy and safety
Bibliographic record
Abstract
INTRODUCTION: We aimed to evaluate the success of bladder neck injections of triamcinolone at the time of transurethral bladder neck incision (BNI) for prevention of recurrent vesicourethral anastomotic stenosis (VUAS) following prostate cancer treatment. METHODS: This is a retrospective cohort study examining patients with recurrent VUAS post-radical prostatectomy (RP) ± radiation treated with triamcinolone injections at the time of BNI. VUAS was diagnosed by symptoms followed by cystoscopy or urethrography. The outpatient procedures were done under general anesthesia. Cold knife incisions were made at the three, nine, and 12 o'clock BN positions, followed by triamcinolone injections (4 mg/mL) into the three and nine o'clock incision sites. Treatment outcomes were determined with cystoscopy. RESULTS: Eighteen men underwent 25 procedures over a four-year period. Median age at diagnosis of VUAS was 65 (interquartile range [IQR] 61-68); median time to VUAS from RP was eight months (IQR 5-12). Fourteen patients (78%) had radiation treatment. The cohort had 128 unsuccessful VUAS treatments, with a median of five failed treatments per patient (IQR 3-10). Failed treatments included BN dilation, BNI, BN injection of mitomycin C, and urethral stent placement. Success rate after a mean of 16.3 months (standard deviation [SD] 8.1) from the time of triamcinolone injection was 83% (15/18). Six patients went on to have successful incontinence surgery. Five patients (28%) had treatment complications (bleeding, urinary tract infection, pain, and urinary extravasation). The three non-responders are stable and awaiting re-treatment with triamcinolone injection. CONCLUSIONS: Triamcinolone bladder neck injections for post-RP VUAS are a useful and safe treatment for recurrent stenosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".