Multicentre study comparing outcomes of RIRS using traditional suction ureteral access sheath (SUAS) and flexible and navigable suction UAS (FANS)
Bibliographic record
Abstract
Objective: We aim to compare the stone-free rate (SFR), complications, and re-treatment rates in retrograde intrarenal surgery (RIRS) using a traditional suction ureteral access sheath (SUAS) with the more advanced flexible and navigable suction UAS (FANS). Materials and methods: Retrospective analysis was performed on patients who underwent RIRS using SUAS versus FANS across five institutions internationally as part of an audit. We analysed baseline and pre-operative characteristics such as stone location and density, intra-operative characteristics such as type of ureteroscope and laser, laser, and fluoroscopy time, as well as post-operative complications and residual fragments (RFs). Results: A total of 45 patients were included in each arm, with no significant difference in baseline characteristics. The commonest sheath size in the FANS group was 10–12 Fr (64.4%), while 11–13 Fr was preferred in SUAS (73.3%). Despite similar lasers (thulium fibre laser (TFL) and high-power holmium laser with MOSES), stone dusting (48.9%) and popcorning (95.6%) were carried out in FANS with minimal need for baskets (4.4%), while popcorning (64.4%) and basket extraction (40.0%) were required in SUAS. Although FANS had significantly longer operative times (65 minutes versus 55 minutes), it also had significantly higher rates of 100% SFR (80.0% versus 13.3%), and lower rates of clinically significant residual fragment (CSRF) (8.9% versus 53.3%), clinically insignificant residual fragment (CIRF) (11.1% versus 33.3%), and reintervention for CSRF (4.4% versus 37.8%). In addition, minor complications such as intra-operative oozing from mucosa not requiring intervention (8.9% versus 31.1%) and post-operative fever (11.1% versus 40.0%) were less common in FANS. On additional multivariate analysis, FANS was the only significant factor for higher SFR. Discussion and conclusion: The results of our study demonstrate that with its flexible and navigable tip, FANS proves advantageous over SUAS in terms of improving immediate SFR with negligible complications. By navigating the sheath into targeted individual calyces, fragments and dust are more successfully aspirated. FANS can therefore help to achieve the trifecta of high single-stage SFR, minimal minor and no major complications, and negligible reintervention rates. Level of evidence: Not applicable.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".