Preoperative evaluation of laparoscopic living renal donors with computerized tomography and its effect on donor morbidity and graft function.
Bibliographic record
Abstract
OBJECTIVE: To assess the efficacy of CT angiography (CTA) in evaluating the renovascular anatomy in 50 patients who underwent laparoscopic donor nephrectomy, and to correlate results with donor morbidity and recipient outcome. METHODS: Forty-eight patients were evaluated by CTA prior to laparoscopy. Donors with aberrant renovasculature and their respective recipients were divided into: 1) accurate preoperative CTA ("predictive group", PG), 2) inaccurate CTA ("non-predictive group", NPG). Warm ischemia times (WIT), estimated blood loss (EBL), operative time (OT), and the open conversion rate were compared. Recipient creatinine values on post-operative day 1 and 3 months were recorded with the rate of delayed graft function (DGF) and ureteral complication. Statistical significance was calculated using the student's T-test. RESULTS: Among patients with aberrant vasculature (48%, 23/48) at laparoscopy, 14 were accurately predicted by CT angiography (11 arterial, 3 venous). NPG consisted of 5 duplicated arteries, 1 early arterial branching, and 3 anomalous veins. CT accuracy was 85%. The sensitivity and specificity of the arterial imaging were 65% and 100% respectively, while those of venous imaging were 50% and 100%. EBL, WIT, OT, number of open conversions, and ureteral complications were statistically insignificant between groups (p= 0.05, 95% C.I.). The mean decreases in creatinine between NPG and PG on post-operative day 1 and at 3 months were 45.4% and 54.8%, and 71.5% and 79.1% respectively, both statistically insignificant. Two of 8 in the NPG experienced DGF as compared to 1/8 in the PG. CONCLUSIONS: Despite the lower sensitivity of this study, the discordance between imaging and laparoscopy did not augment donor morbidity or increase adverse recipient outcomes. This may indicate that regardless of the shortcomings of 2-D CTA for living donors, it represents a safe and effective imaging modality when coupled with meticulous laparoscopic dissection and central intraoperative involvement of the transplant surgeon.
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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 | 0.006 |
| 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) | 0.001 | 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".