BCG-Related Renal Granulomas Managed Conservatively
Bibliographic record
Abstract
INTRODUCTION: The aim of this case series is to present two cases of renal granulomas discovered incidentally post-intravesical Bacillus Calmette-Guerin (BCG) installations and were managed conservatively. CASE REPORTS: The first case is a 68-year-old man with bladder and right ureteral orifice carcinoma in situ. After transurethral resection of the right ureteral orifice and bladder tumours, he received 6 + 3 weekly intravesical installations of BCG and then 6 + 3 weekly intravesical installations of BCG with interferon alpha (IFN) in the presence of an indwelling ureteral stent since he had refused cystoprostatectomy. At the 18-month follow-up, his computed tomography scan showed two right renal masses. Biopsy demonstrated non-necrotizing granulomatosis. Serial follow-up with imaging studies showed complete resolution of these masses without anti-tuberculous medications. The second case is a 74-year old man with left renal high-grade papillary urothelial carcinoma. After ureteral meatotomy and insertion of indwelling ureteral stents, he received 6 weekly intravesical installations of BCG followed by 3 weekly installations of BCG and IFN prior to the definitive management with laparoscopic left nephroureterectomy. Final pathology showed pT1 urothelial carcinoma and an incidental finding of BCG-related renal granulamotosis. The patient has been asymptomatic and did not require anti-tuberculous medications. CONCLUSIONS: While these two cases demonstrate the ability of intravesical BCG to reach the renal pelvis, patients with a history of intravesical BCG with incidental renal masses may benefit from renal biopsy. These renal granulomas may resolve without anti-tuberculous medications.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".