728 A Systematic Review of The Efficacy and Safety of Outpatient Bladder Tumour Ablation
Bibliographic record
Abstract
Abstract Introduction The management of recurrent non-muscle-invasive bladder cancer (NMIBC) typically requires repeated transurethral resections under general anaesthesia. This is costly and results in poor health-related quality-of-life for patients. Outpatient-based laser ablation and diathermy to recurrent tumours could reduce morbidity and cost of managing NMIBC. This systematic review evaluates the safety and efficacy of outpatient-based diathermy or laser ablation for recurrent NMIBC. Method The EMBASE, MEDLINE and Cochrane Library were searched until June 2020. All studies evaluating the use of outpatient diathermy or laser ablation for NMIBC were included. The quality of evidence and risk of bias were assessed using the GRADE and ROBINS-I tools, respectively. Results From 1328 studies identified, 17 studies (1584 patients) were included. Overall, the majority of tumours (80%) were low-grade (G1 and G2). Laser ablation and diathermy resulted in a mean recurrence rate of 47% and 40% at 20-31 months follow-up, respectively, with a mean progression rate of 3-11%. Both procedures were well-tolerated with low pain scores (mean score of 1) and low periprocedural complication rates. However, the overall quality of evidence of low. Conclusions This review demonstrates that both procedures have good short-term efficacy in patients with low-grade NMIBC. The procedures are well-tolerated with low complication rates and importantly, reduce the need for intervention under general anaesthesia. These findings can aid patient counselling regarding less invasive treatment options, avoiding the morbidity of transurethral resection. Future randomised studies with standardised risk stratification and outcome measures are required to add to the quality of evidence.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".