Transurethral resection and degeneration of bladder tumour
Bibliographic record
Abstract
INTRODUCTION: We evaluate the efficacy and safety of transurethral resection and degeneration of bladder tumour (TURD-Bt). METHODS: In total, 56 patients with bladder tumour were treated by TURD-Bt. The results in these patients were compared with 32 patients treated by current transurethral resection of bladder tumour (TUR-Bt). Patients with or without disease progressive factors were respectively compared between the 2 groups. The factors included recurrent tumour, multiple tumours, tumour ≥3 cm in diameter, clinical stage T2, histological grade 3, adenocarcinoma, and ureteral obstruction or hydronephrosis. RESULTS: Follow-up time was 48.55 ± 23.74 months in TURD-Bt group and 56.28 ± 17.61 months in the TUR-Bt group (p > 0.05). In patients without progressive factors, no tumour recurrence was found and overall survival was 14 (100%) in the TURD-Bt group; 3 (37.50%) patients had recurrence and overall survival was 5 (62.5%) in the TUR-Bt group. In patients with progressive factors, 8 (19.05%) patients had tumour recurrence, overall survival was 32 (76.19%) and cancer death was 3 (7.14%) in TURD-Bt group; 18 (75.00%) patients had tumour recurrence (p < 0.05), overall survival was 12 (50.00%) (p < 0.01) and cancer death was 8 (33.33%) (p < 0.05) in TUR-Bt group. No significant complication was found in TURD-Bt group. CONCLUSION: This study suggests that complete resection and degeneration of bladder tumour can be expected by TURD-Bt. The surgical procedure is safe and efficacious, and could be predictable and controllable before and during surgery. We would conclude that for bladder cancers without lymph node metastasis and distal metastasis, TURD-Bt could be performed to replace radical TUR-Bt and preserve the bladder.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".