Renal hypothermia during partial nephrectomy for patients with renal tumours: a randomised controlled clinical trial protocol
Bibliographic record
Abstract
INTRODUCTION: Partial nephrectomy is a standard of care for non-metastatic renal tumours when technically feasible. Despite the increased use of partial nephrectomy, intraoperative techniques that lead to optimal renal function after surgery have not been rigorously studied. Clamping of the renal hilum to prevent bleeding during resection causes temporary renal ischaemia. The internal temperature of the kidney may be lowered after the renal hilum is clamped (renal hypothermia) in an attempt to mitigate the effects of ischaemia. Our objective is to determine if renal hypothermia during open partial nephrectomy results in improved postoperative renal function at 12 months following surgery as compared with warm ischaemia (no renal hypothermia). METHODS AND ANALYSES: This is a multicentre, randomised, single-blinded controlled trial comparing renal hypothermia versus no hypothermia during open partial nephrectomy. Due to the nature of the intervention, complete blinding of the surgical team is not possible; however, surgeons will be blinded until the time of hilar clamping. Glomerular filtration will be based on plasma clearance of a radionucleotide, and differential renal function will be based on renal scintigraphy. The primary outcome is overall renal function at 12 months measured by the glomerular filtration rate (GFR). Secondary outcomes include change in GFR, GFR of the affected kidney, change in GFR of the affected kidney, serum creatinine, haemoglobin, spot urine albumin to creatinine ratio, quality of life and postoperative complications. Data will be collected at baseline, immediately postoperatively and at 3, 6, 9 and 12 months postoperatively. ETHICS AND DISSEMINATION: Ethics approval was obtained for all participating study sites. Results of the trial will be submitted for publication in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: NCT01529658; Pre-results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.037 | 0.005 |
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".