Comparison of Complications and Short Term Results of Conventional Technique Versus New Technique During Graft Ureteral Stent Insertion in Bari Technique at Emam Khomeini Hospital, Urmia
Bibliographic record
Abstract
INTRODUCTION: There is debate on renal graft stenting during ureteroneocystostomy, patients with ureteral stents may encounter several complications such as encrustation, stent crustation which can lead to loss of kidney, and complications related to stent extraction: pain and UTI increasing related to cystoscopy for stent extraction accompanying excess expenses. This study designed to reduce complications related to stent extraction. MATERIALS & METHODS: 90 patients prepared for renal transplantation during 1 year randomly classified to groups, study group: patients with attached stent to Foley catheter, control group: patients with conventional technique (stent separated from Foley) then in their follow up; UTI, stent crustation, luts severity compared to each other. RESULTS: Second week and fourth week UTI reported 25.6%, 2.3% in study group versus 34.9%, 4.7% in control group (P.value:0.48 and 0.5). Urinary leakage was 3.3% overall, that all of them occurred in separate stent group, 37.5% vs. 0% in the linked stent group. Stent crustation in separate stent was 25% compared with 0% in the linked stent. CONCLUSION: Low complications rate in linked stent group, despite the lack of significant statistical differences, but indicate the effectiveness and success of the new technique.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".