Radical cystectomy in patients over 80 years old in Quebec: A population‐based study of outcomes
Bibliographic record
Abstract
OBJECTIVES: To document radical cystectomy (RC) outcomes in patients over 80 years old across Quebec during the years 2000-2009 and to examine potentially related factors. METHODS: Within Quebec health insurance medical services database, we identified patients over 80 years who underwent RC. The outcomes analyzed were post-operative complications, mortality rates at 30, 60 and 90 days and overall survival. RESULTS: A total of 275 patients over 80 years old had RC performed in 38 hospitals across Quebec. Among them, 33% had major post-operative complications with 16% having more than one complication. Mortality rates at 30, 60 and 90 days were 5.8%, 9.8% and 13% respectively. 44.3% of RCs were performed in seven academic hospitals with mortality rates of 2.5%, 6.5% and 9% respectively. Community hospitals had mortality of 8.5%, 12.4% and 16.3% respectively (P < 0.001). The cohort 5-year overall survival rate was 27%. The presence of post-operative complications and the number of complications negatively affected overall survival (P < 0.001) CONCLUSION: Patients over 80 years of age have high post-RC mortality rates, especially at 90 days. In addition, it appears that they have lower post-operative mortality if their RCs were performed in academic centers. Mortality rates and complications can be used when obtaining informed consent.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".