IS ROUTINE URETERIC STENTING NEEDED IN KIDNEY TRANSPLANTATION? A RANDOMIZED TRIAL
Bibliographic record
Abstract
BACKGROUND: Whether routine ureteric stenting in low-urological-risk patients reduces the risk of urological complications in kidney transplantation is not established. METHODS: Eligible patients were recipients of single-organ renal transplants with normal lower urinary tracts. Patients were randomized intraoperatively to receive either routine stenting or stenting only in the event of technical difficulties with the anastomosis. All patients underwent Lich-Gregoire ureteroneocystostomy. RESULTS: Between June 1994 and December 1997, 331 kidney transplants were performed at a single center, 305 patients were eligible, and 280 patients were enrolled and randomized. Donor and recipient age, sex, donor source, whether first or subsequent grafts, ureteric length, native renal disease, and immunosuppression were similar in each group. In the no-routine-stenting group 6 of 137 patients (4.4%) received stents after randomization for intraoperative events that in the surgeon's opinion required use of a stent. In an intention-to-treat analysis there was no difference between groups in the primary outcome cluster of obstruction or leak [routine stenting 5 of 143 (3.5%) vs. no routine stenting 9 of 137 (6.6%); P=0.23], or in either of these complications analyzed separately. All urological complications were successfully managed without major morbidity. Living donor organs and shorter ureteric length (after trimming) were univariate risk factors for leaks, although increasing donor age was associated with obstruction. CONCLUSIONS: Routine ureteric stenting is unnecessary in kidney transplantation in patients at low risk for urological complications. Careful surgical technique with selective stenting of problematic anastomoses yields similar 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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".