The association between renal tumour scoring system components and complications of partial nephrectomy
Bibliographic record
Abstract
INTRODUCTION: We evaluate the associations between 3 renal tumour scoring systems and their components with perioperative complications of partial nephrectomy. METHODS: A consecutive cohort of partial nephrectomy patients was analyzed. Patient characteristics were abstracted from medical records. PADUA scores (preoperative aspects and dimensions used for anatomic classification), RENAL (radius exophyic/endophytic nearness anterior/posterior location scoring) nephrometry scores, and Centrality index (C-index) were determined from preoperative axial images by 2 independent reviewers. Cases were evaluated for postoperative complications up to 30 days after surgery. Pre-specified complication definitions were used for 33 potential medical and surgical complications. Unadjusted and adjusted associations between overall scores, individual components, and complications were determined using log binomial regression. RESULTS: In total, 118 patients were included in the study. Of these, 36 (30.5%) surgical complications occurred in 27 (22.9%) patients. Fourteen (11.9%) were Clavien grade ≥3. Overall PADUA score was significantly associated with surgical and overall complications after adjusting for potential confounders. Among all components of the 3 scoring systems, only tumour diameter and exophytic/endophytic nature of the tumour were significantly associated with complications after adjusting for the other components of the respective scoring system (p < 0.05). CONCLUSIONS: Renal tumour scoring systems may help predict the risk of complications after partial nephrectomy. Further refinement of current systems is required. A first step would be to include only components that are significantly associated with complications.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".