MP75-10 HILAR LOCATION OF RENAL TUMOR PREDICTS INCIDENCE OF MAJOR COMPLICATIONS AFTER ROBOTIC PARTIAL NEPHRECTOMY: A LARGE, MULTI-INSTITUTIONAL STUDY
Bibliographic record
Abstract
months post-operatively with the mean eGFR at 3 months being 19 ml/ min/1.73m2lower than those undergoing partial nephrectomy (p<0.001).A lower pre-operative eGFR and increasing age were also associated with a lower eGFR post-operatively (p<0.01) in both the entire cohort and among patients undergoing partial nephrectomy.Severe renal failure (Stage 4 or 5) developed post-operatively in 31.0%,5.4%, and 1.1% of patients with pre-operative stage 1, 2, or 3 chronic kidney disease.Among patients undergoing partial nephrectomy, ischemia type and duration were not predictive of post-operative decline in eGFR at all time intervals.CONCLUSIONS: Patients undergoing radical nephrectomy have a greater long-term reduction in renal function compared with those undergoing partial nephrectomy.In this modern series with generally short ischemia durations, ischemia duration and type were not predictive of post-operative renal function.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".