Impact of a teaching program on outcome quality of white light transurethral resection for bladder tumor: A cohort study
Bibliographic record
Abstract
Objective: To test the hypothesis that a teaching program improves the quality of transurethral resection of bladder tumor (TURBT) and decreases the risk of early recurrence. Material and methods: This is an observational retrospective cohort study of prospectively recorded data of patients with first clinical diagnosis of non-muscle-invasive bladder cancer (NMIBC), scheduled for TURBT. In 2005 a systematic TURBT teaching program was introduced in our Department. We reviewed the charts of patients who underwent TURBT in the years 1998-2004, when no tutoring was applied, and those who underwent TURBT in the years 2005-2010. The outcomes of interest were: presence/absence of detrusor muscle (DM), carcinoma in situ (CIS) detection, complication rate and recurrence rate at the first follow-up cystoscopy (RRFF-C). Results: Complete data from 427 patients were available: 199 before and 228 after the introduction of the teaching program. Multivariable logistic analysis showed that the training program was an independent prognostic factor for DM (presence) rate (OR = 3.92, 95%CI = 2.42-6.33), CIS detection rate (OR = 4.36, 95%CI = 1.92-9.86), and complication rate (OR = 0.28, 95%CI = 0.15-0.55), but not for RRFF-C (OR = 0.79, 95%CI = 0.52-1.20). Between 1998-2004, RRFF-C was correlated with tumor number, pathological stage, DM presence, presence of complication, CIS detection and surgeon experience. After the introduction of the teaching program, only tumor number, DM presence and surgeon experience influenced the RRFF-C. Conclusion: Our findings suggest the hypothesis that the teaching program might have an impact of quality of TURBT, but it failed to improve the RRFF-C.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".