Dusting versus Basketing during Ureteroscopy–Which Technique is More Efficacious? A Prospective Multicenter Trial from the EDGE Research Consortium
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: There is scant evidence in the literature to support dusting vs active basket extraction during ureteroscopy for kidney stones. We prospectively evaluated and followed patients to determine which modality produced a higher stone-free rate with the fewest complications. MATERIALS AND METHODS: Members of the Endourologic Disease Group for Excellence research consortium prospectively enrolled patients with a renal stone burden ranging from 5 to 20 mm in this study. A holmium laser was used and all patients were stented postoperatively. Ureteral access sheaths were used in 100% of basketing cases while sheaths were optional when dusting. The primary study outcome was the stone-free rate at 6 weeks as determined by x-ray and ultrasound. RESULTS: , p <0.001). The stone-free rate was significantly higher in the basketing group on univariate analysis (74.3% vs 58.2%, p = 0.04) but not on multivariate analysis (1.9 OR, 95% CI 0.9-4.3, p = 0.11). In patients who underwent a basketing procedure operative time was 37.7 minutes longer than in those treated with a dusting procedure (95% CI 23.8-51.7, p <0.001). There was no statistically significant difference in complication rates, hospital readmissions or additional procedures between the groups. CONCLUSIONS: The stone-free rate was higher for active basket retrieval of fragments at short-term followup on univariate analysis but not on multivariate analysis. There was no difference in postoperative complications or procedures. The 2 techniques should be in the armamentarium of the urologist.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it