Comparison of peri- and intraoperative outcomes of open vs robotic-assisted partial nephrectomy for renal cell carcinoma: a propensity-matched analysis
Bibliographic record
Abstract
BACKGROUND: Partial nephrectomy (PN) is the gold standard surgical treatment for resectable renal cell carcinoma (RCC) tumors. However, the decision whether a robotic (RAPN) or open PN (OPN) approach is chosen is often based on the surgeon's individual experience and preference. To overcome the inherent selection bias when comparing peri- and postoperative outcomes of RAPN vs. OPN, a strict statistical methodology is needed. MATERIALS AND METHODS: We relied on an institutional tertiary-care database to identify RCC patients treated with RAPN and OPN between January 2003 and January 2021. Study endpoints were estimated blood loss (EBL), length of stay (LOS), rate of intraoperative and postoperative complications, and trifecta. In the first step of analyses, descriptive statistics and multivariable regression models (MVA) were applied. In the second step of analyses, to validate initial findings, MVA were applied after 2:1 propensity-score matching (PSM). RESULTS: Of 615 RCC patients, 481 (78%) underwent OPN vs 134 (22%) RAPN. RAPN patients were younger and presented with a smaller tumor diameter and lower RENAL-Score sum, respectively. Median EBL was comparable, whereas LOS was shorter in RAPN vs. OPN. Both intraoperative (27 vs 6%) and Clavien-Dindo > 2 complications (11 vs 3%) were higher in OPN (both < 0.05), whereas achievement of trifecta was higher in RAPN (65 vs 54%; p = 0.028). In MVA, RAPN was a significant predictor for shorter LOS, lower rates of intraoperative and postoperative complications as well as higher trifecta rates. After 2:1 PSM with subsequent MVA, RAPN remained a statistical and clinical predictor for lower rates of intraoperative and postoperative complications and higher rates of trifecta achievement but not LOS. CONCLUSIONS: Differences in baseline and outcome characteristics exist between RAPN vs. OPN, probably due to selection bias. However, after applying two sets of statistical analyses, RAPN seems to be associated with more favorable outcomes regarding complications and trifecta rates.
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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) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".