Comparison of a magnetic retrieval device vs. flexible cystoscopy for removal of ureteral stents in renal transplant patients: A randomized controlled trial
Bibliographic record
Abstract
INTRODUCTION: Placement of a ureteral stent at the time of renal transplantation can reduce complications when compared to non-stented anastomoses. Removal by flexible cystoscopy can be associated with discomfort, risk for infection, and high costs. New magnetic stents offer a means of bypassing cystoscopy by use of a magnetic retrieval device. Our objective was to compare clinical and cost-related outcomes of conventional and magnetic stents in patients undergoing deceased donor renal transplantation. METHODS: magnetic stent. Clinical, procedural, and cost outcomes were assessed, and the Ureteral Stent Symptom Questionnaire (USSQ) was administered with the stent in situ and after stent removal. All variables were compared between groups. RESULTS: Forty-one patients were randomized to conventional (n=19) or Black-Star (n=22) stent. The total time for stent removal under cystoscopy was significantly longer compared to Black-Star removal (6.67±2.47 and 4.80±2.21 minutes, respectively, p=0.019). No differences were found in the USSQ domains between groups. Rates of urinary tract infections and surgical complications between groups were similar. Stent removal was well-tolerated in both groups. Black-Star stent use resulted in a cost savings of $304.02 Canadian dollars (CAD) per case. CONCLUSIONS: USSQ scores suggest that stent removal with the Black-Star magnetic stent is as equally well-tolerated as flexible cystoscopy by renal transplant patients. Black-Star stent removal was significantly faster than conventional stents. No differences in discomfort, infection rate, or complication rate were found. Use of the Black-Star stent resulted in an estimated annual savings of $27 360 CAD at our centre.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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, 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".