Clinical implication of renal allograft volume to recipient body surface area ratio in pediatric renal transplant
Bibliographic record
Abstract
Our study aims to assess the clinical implication of RAV/rBSA ratio in PRT as a predictor for attained renal function at 1 year post-transplantation and its association with surgical complications. A retrospective cohort was performed for PRT cases from January 2000 to December 2015 in our institution. Extracted clinical information includes the recipient's demographics, donor type, renal allograft characteristics, arterial, venous and ureteral anastomoses, vascular anastomosis time while kidney off ice, overall operative time, and estimated blood loss. The RAV/rBSA was extrapolated and assessed for its association with renal graft function attained in 1 year post-transplantation and surgical complications within 30-day post-transplantation. A total of 324 PRTs cases were analyzed. The cohort consisted of 187 (52.4%) male and 137 (42.3%) female recipients, with 152 (46.9%) living donor and 172 (53.1%) deceased donor renal transplants, and an overall median age of 155.26 months (IQR 76.70-186.98) at time of renal transplantation. The receiver operating characteristic identified that a RAV/rBSA ratio of 135 was the optimal cutoff in determining the renal graft function outcome. Univariate and multivariate analyses revealed the relative OR for RAV/rBSA ≥ 135 ratio in predicting an eGFR ≥ 90 attained within 1 year post-transplant was highest among younger pediatric recipients (<142.5 months) of deceased kidney donors (OR = 11.143, 95% CI = 3.156-39.34). Conversely, Kaplan-Meier analysis revealed that RAV/rBSA ratio ≥ 135 is associated with lower odds of having eGFR <60 (OR = 0.417, 95% CI = 0.203-0.856). The RAV/rBSA ratio was not associated nor predictive of transplant-related surgical complications. Our study determined that the RAV/rBSA ratio is predictive of renal graft function at 1-year PRT, but not associated with any increased surgical complications.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".