Impact of peri‐operative blood transfusion on the outcomes of patients undergoing radical cystectomy for urothelial carcinoma of the bladder
Bibliographic record
Abstract
OBJECTIVE: To determine the association between peri-operative blood transfusion (PBT) and oncological outcomes in a large multi-institutional cohort of patients undergoing radical cystectomy (RC) for urothelial carcinoma of the bladder (UCB). PATIENTS AND METHODS: We conducted a retrospective analysis of 2895 patients treated with RC for UCB. Univariable and multivariable Cox regression models were used to analyse the effect of PBT administration on disease recurrence, cancer-specific mortality, and any-cause mortality. RESULTS: Patients' median (interquartile range [IQR]) age was 67 (60, 73) years and the median (IQR) follow-up was 36.1 (15, 84) months. Patients who received PBT were more likely to have advanced disease (P < 0.001), high grade tumours (P = 0.047) and nodal metastasis (P = 0.004). PBT was associated with a higher risk of disease recurrence (P = 0.003), cancer-specific mortality (P = 0.017), and any-cause mortality (P = 0.010) in univariable, but not multivariable, analyses (P > 0.05). In multivariable analyses, pathological tumour stage, pathological nodal stage, soft tissue surgical margin, lymphovascular invasion and administration of adjuvant chemotherapy were independent predictors of disease recurrence, cancer-specific mortality and any-cause mortality (all P values <0.002). CONCLUSIONS: Patients with UCB who underwent RC and received PBT had a greater risk of disease recurrence, cancer-specific mortality and any-cause mortality in univariable, but not multivariable, analysis. Although the greater need for PBT with more advanced disease is probably caused by a number of factors, including surgical and cancer-related factors, the present analysis showed that the disease characteristics rather than need for PBT led to worse outcomes.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".