Impact of Blood Loss on Renal Function and Interaction with Ischemia Duration after Nephron-Sparing Surgery
Bibliographic record
Abstract
Objectives: Nephron-sparing surgery (NSS) exposes the kidney to ischemia–reperfusion injury. Blood loss and hypotension are also associated with kidney injury. We aimed to test the hypothesis that, during NSS, both ischemia duration and blood loss significantly affect postoperative renal function and that their effects interact. Methods: Consecutive patients undergoing NSS were enrolled. The primary endpoint was renal function expressed as the absolute delta between preoperative and postoperative peak creatinine. We developed a generalized linear model with the ischemia duration and absolute hemoglobin difference as independent variables, their interaction term, and the RENAL score. The model was than expanded to include a history of hypertension (as a proxy for hypotension susceptibility) and related interaction terms. Further, we described the perioperative and mid-term oncological outcomes. Results: A total of 478 patients underwent NSS, and 209 (43.7%) required ischemia for a mean of 10.9 min (SD 8). Both the ischemia duration (partial eta 0.842, p = 0.006) and hemoglobin difference (partial eta 0.933, p = 0.029) significantly affected postoperative renal function, albeit without evidence of a significant interaction (p = 0.525). The RENAL score also significantly influenced postoperative renal function (p = 0.023). After the addition of a previous history of hypertension, the effects persisted, with a significant interaction between blood loss and a history of hypertension (p = 0.02). Conclusions: Ischemia duration and blood loss had a similar impact on postoperative renal function, albeit without potentiating each other. While the surgical technique and ischemia minimization remain crucial to postoperative kidney function, increased awareness of conscious hemodynamic management appears warranted.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".