Robot‐Assisted Versus Open Radical Cystectomy: Comparison of Adverse In‐Hospital Outcomes
Bibliographic record
Abstract
PURPOSE: To quantify improvements in adverse in-hospital outcomes between historical and contemporary robot-assisted radical cystectomy (RARC) versus historical and contemporary open RC (ORC). MATERIAL AND METHODS: Within the National Inpatient Sample (2010-2019), RARC and ORC ileal conduit diversion patients were identified. Multivariable logistic and Poisson regression models were fitted. RESULTS: Of RARC patients, 1343 (39%) were historical (2010-2014) and 2087 (61%) were contemporary (2015-2019). Of ORC patients, 5812 (54%) were historical and 5019 (46%) were contemporary. Versus historical counterparts, contemporary RARC patients exhibited significantly better adverse in-hospital outcomes in 9 of 13 categories, with improvements ranging from -82% for intraoperative complications to -22% for cumulative postoperative complications. Similarly, versus historical, contemporary ORC patients also exhibited significantly better adverse in-hospital outcomes in 9 of 13 categories, with improvements ranging from -72% for intraoperative complications to -12% for median length of stay (LOS). When contemporary RARC was compared to contemporary ORC, RARC adverse in-hospital outcomes were better in 7 of 13 comparisons, with improvements ranging from -55% for blood transfusions to -18% for median LOS. Similarly, when historical RARC was compared to historical ORC, RARC adverse in-hospital outcomes were better in 6 of 13 comparisons, with improvements ranging from -55% for blood transfusions to -15% for median LOS. CONCLUSION: The magnitude of the improvement in adverse in-hospital outcomes was comparable between contemporary versus historical RARC (nine improved categories) and contemporary versus historical ORC (nine improved categories). However, contemporary RARC outperformed contemporary ORC in 7 of 13 categories of adverse in-hospital outcomes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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".