Identification of factors predicting loss of renal differential function on the operated kidney after laparoscopic partial nephrectomy
Bibliographic record
Abstract
e16015 Background: Partial nephrectomy (PN) is now the gold standard for small renal mass of less than 4 cm since it prevents renal insufficiency that may occur with radical nephrectomy. The impact of warm ischemis time (WIT) on the operated kidney's renal differential function (RDF) have been poorly studied in the litterature, especially when WIT is less than 30 minutes. We evaluated the effect of WIT and other perioperative factors on RDF function assessed by pre- and post-operative renal scintigraphy. Methods: Between 2003 and 2008, 182 laparoscopic PN were performed by a single surgeon on patients with two kidneys. Among those, 56 had a MAG3-lasix renal scintigraphy pre- and post-operatively between 7 and 14 days. Data were collected prospectively. Loss in RDF is calculated as follow: Loss in RDF=(RDF preoperatively-RDF postoperatively/RDF preoperatively) × 100. Results: Medians for age, pre- op creatinine, pre-op GFR (Cockroft formula) and tumor CT-size were 61 years, 83 μM, 83,2 ml/min and 26 mm, respectively. Median WIT and pre-operative RDF were 30 minutes and 50%. Median loss of RDF after surgery was 24%. In multivariate analysis, low pre-operative RDF, WIT and intrarenal location of the tumor were associated with a statistically significant loss of RDF (p<0.05). Age, pre-op GFR, tumor CT-size, diabetes and HTN did not predict loss in RDF. Fitting the relative RDF loss versus WIT to a polynomial curve suggests that the rate of loss in RDF increase with WIT. The point of inflection of the polynomial curve (reflecting the maximal change in rates of loss in RDF) was estimated to be at 32 minutes. Linear regression curves show that loss in RDF rate is 0.8% per minute when WIT is less than 32 minutes and 1.3 % per minute when WIT is more or equal to 32 minutes. Conclusions: We show that a WIT of less than 32 minutes optimizes the chances of preserving RDF of the operated kidney and that the rate of loss in RDF is higher above 32 minutes. Finally, higher loss in RDF must be expected if the patient has a low pre-operative RDF and intrarenal location of the tumor. No significant financial relationships to disclose.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".