Radical cystectomy in patients with disseminated disease: An assessment of perioperative outcomes using the National Surgical Quality Improvement Program database
Bibliographic record
Abstract
INTRODUCTION: We sought to determine the effect of the presence of disseminated disease on perioperative outcomes following radical cystectomy for bladder cancer. METHODS: We identified 4108 eligible patients who underwent radical cystectomy for bladder cancer using the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database. We matched patients with disseminated cancer at the time of surgery to those without disseminated cancer using propensity scores. The primary outcome of interest was major complications (death, reoperation, cardiac or neurological event). Secondary outcomes included pulmonary, infectious thromboembolic, and bleeding complications, in addition to prolonged length of stay. Generalized estimating equations were used to examine the association between disseminated cancer and the development of complications. RESULTS: Following propensity score matching and adjusting for the type of urinary diversion, radical cystectomy in patients with disseminated disease was associated with a significant increase in major complications (8.6% vs. 4.0%; odds ratio [OR] 2.50; 95% confidence interval [CI] 1.02-6.11; p=0.045). The presence of disseminated disease was associated with an increase in pulmonary complications (5.8% vs. 1.2%; OR 5.17. 95% CI 1.00-26.66. p=0.049), but not infectious complications, venous thromboembolism, bleeding requiring transfusion, and prolonged length of stay (p values 0.07-0.79). CONCLUSIONS: Patients with disseminated cancer undergoing cystectomy are more likely to experience major and pulmonary complications. The strength of these conclusions is limited by sample size, selection bias inherent in observational data, and a lack of specific oncological detail in the database.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".