Diode Laser for the Management of Upper Tract Urothelial Cancer (UTUC) – Case Series.
Bibliographic record
Abstract
Background and Objective: Upper tract urothelial carcinoma (UTUC) is uncommon; however, at the time of diagnosis, they are usually more invasive than bladder urothelial carcinomas. Although nephroureterectomy (NU) has been the gold-standard treatment, guidelines have been set for kidney-sparing treatment in selected groups of patients. While these guidelines are aimed towards patients fit for salvage radical treatment, little has been published on managing the symptomatic patient not fit for NU. Various modalities of endoscopic ablation in managing UTUC have been described in the literature, but there is currently no reported use of the diode laser. Therefore, we aim to assess its efficacy and safety profile in the ablation of UTUC in patients unfit for major abdominal surgery in radical nephroureterectomy regardless of the tumour grade and size. Patients and method A single centre retrospective review of patients who underwent Diode Laser treatment for UTUC over 4 years was done. Follow up through 6 monthly ureteroscopy alternating with computed tomography (CT) urogram was done to assess the need for further treatment. Results: 30 patients were identified, with mean age 76 years (64-88) and variable tumour locations, including lower and mid ureter and renal pelvis, upper and lower calyces. 76.7% were ASA 3 and 20% ASA 4. The mean tumour size was 3.8 cm (2-7 cm). The mean number of sessions was 2.1 (1-6). 63.3% of the tumours were grade 2, while 30% were grade 3. A case of metastatic renal-cell carcinoma was diagnosed as a 4 cm filling defect in the kidney where the diode laser was used for resection biopsy and ablation. 16.7% experienced Clavien-Dindo grades 1-2 complications. A total of 6.7% of patients were converted to an inpatient stay. None of the patients needed blood transfusion nor did any develop a ureteric stricture on subsequent ureteroscopies. 48.3% of patients experienced clinical recurrences of which 57.1% were at a different site. Two of the patients developed metastatic disease. One patient died 3 years after initial treatment with disease progression. Conclusion: The management of UTUC with diode laser is a safe and efficacious conservative treatment for disease and symptom control in patients unfit for radical treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".