RIRS with disposable or reusable scopes: does it make a difference? Results from the multicenter FLEXOR study
Bibliographic record
Abstract
Introduction: With several single-use ureteroscopes now available, our aim was to analyze and compare data obtained globally from high-volume centers using both disposable and reusable flexible ureteroscopes and see if indeed in real-world practice either scope has a distinct advantage. Methods: Retrospective analysis was performed on the FLEXOR registry, which was created as a TOWER group (Team of Worldwide Endourological Researchers, research wing of the Endourological Society) endeavor. Patients who underwent retrograde intrarenal surgery (RIRS) for renal stones from January 2018 to August 2021 were enrolled from 20 centers globally. A total of 6663 patients whose data were available for analysis were divided into Group 1 (Reusable scopes, 4808 patients) versus Group 2 (Disposable scopes, 1855 patients). Results: The age and gender distribution were similar in both groups. The mean stone size was 11.8 mm and 9.6 mm in Groups 2 and 1, respectively ( p < 0.001). Group 2 had more patients with >2 cm stones, lower pole stones and of higher Hounsfield unit. Thulium fiber laser (TFL) was used more in Group 2 ( p < 0.001). Patients in Group 2 had a slightly higher stone-free rate (SFR) (78.22%) and a lower number of residual fragments (RFs) compared with Group 1 ( p < 0.001). The need for further treatments for RF and overall complications was comparable between groups. On multivariate analysis, overall complications were more likely to occur in elderly patients, larger stone size, lower pole stones, and were also more when using disposable scopes with longer operative time. RFs were significantly higher ( p < 0.001) for lower pole, larger, harder, multiple stones and in elderly. Conclusion: Our real-world practice observations suggest that urologists choose disposable scopes for bigger, lower pole, and harder stones, and it does indeed help in improving the single-stage SFR if used correctly, with the appropriate lasers and lasing techniques in expert hands.
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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 | 0.000 | 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".