Ureteroscopy for Transplant Lithiasis
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The optimal management of renal and ureteral calculi in transplanted kidneys is not well defined. Although larger (>1.5 cm) stone burdens are generally treated with percutaneous nephrolithotomy (PCNL), smaller stones may be reasonably approached with retrograde or antegrade ureteroscopy (URS). We report our multicenter experience with URS for transplant lithiasis. PATIENTS AND METHODS: URS performed for stone disease within a transplanted kidney were retrospectively identified at three stone-referral centers between 2006 and 2011. Demographic and disease parameters were recorded, as were perioperative and postoperative details. RESULTS: Twelve patients underwent URS for a calculus in a transplant renal unit and/or ureter. For retrograde procedures (7), access to the ureteral orifice was facilitated by the use of a Kumpe catheter; a two-wire (safety and working guidewire) technique was used. For antegrade procedures (5), the ureteroscope was passed into the kidney using a two-wire technique without tract dilation. All stones but one necessitated holmium:yttrium-aluminum-garnet laser lithotripsy with extraction of stone fragments. All patients were stone free on postoperative imaging except for one patient with a 2-mm fragment that was observed. Stone analysis included calcium oxalate (6), calcium phosphate (4), and struvite (1). CONCLUSION: Antegrade and retrograde URS are safe and effective treatments for patients with simple stone burdens in a transplanted kidney. Although retrograde access to the ureter can be challenging, specialized techniques and modern endoscope technology facilitate this process. Antegrade URS for small stone burdens can be performed safely and effectively without tract dilation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".