Early clamp release during laparoscopic partial nephrectomy: Implications for preservation of renal function
Bibliographic record
Abstract
INTRODUCTION: Intraoperative warm ischemic time (WIT), associated with hilar clamping during partial nephrectomy (PN), is an established modifiable risk factor for renal dysfunction. We assessed early clamp release (ECR) as a strategy to reduce WIT and assess its impact on renal function and bleeding. METHODS: We retrospectively assessed patients who underwent minimally invasive PN by a single surgeon at our centre since December 2011. Comparing the standard technique to an ECR modification, WIT, complications, change in estimated glomerular filtration rate (eGFR), and change in differential function as demonstrated by MAG-3 nuclear renography were assessed. Followup blood work and renograms were performed at 6-12 weeks postoperatively and compared to baseline in 70 patients (35 ECR: 35 control). RESULTS: The ECR and control groups were similar in age, sex, and tumour size, with only patient weight being higher in the ECR group (91.6 vs. 81.6 kg; p<0.05). WIT was significantly lower in ECR group compared to control (18.8 vs. 31.5 minutes; p<0.05). Although there was no significant difference in change from baseline eGFR in the early postoperative period (Day 3) or in followup (6-12 weeks), the control group had a significantly greater loss of ipsilateral renal function from baseline compared to the ECR group (9 vs. 4% change; p<0.05). Blood loss and complication rate were similar between groups. CONCLUSIONS: The ECR technique offers a safe, reproducible alternative that reduces WIT during laparoscopic PN. ECR demonstrates a reduction in overall ipsilateral renal dysfunction, without increasing complication or intraoperative bleeding risk.
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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 | 0.001 | 0.003 |
| 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 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".