Effective ureteral access sheath insertion during flexible ueteroscopy: Influence of the ureteral orifice configuration
Bibliographic record
Abstract
Introduction: We sought to determine the possible predictors for effective insertion of the ureteral access sheath (UAS) during flexible ureteroscopy (fURS) in virgin ureters and its impact on postoperative ureteral wall injury and the procedural outcome. Methods: A retrospective review of prospectively collected data was performed for all consecutive patients scheduled for fURS of virgin ureters at two tertiary care centers between 2018 and 2020. Demographics, stone characteristics, and perioperative data, including the configuration of the ureteral orifice (UO) over introductory guidewire insertion, were collected. Multivariate logistic regression was used to detect possible predictors of successful UAS insertion. Results: In total, 128 patients who underwent primary fURS were included, with a mean age of 43.3±12.3 years and a stone burden of 12.3±6.9 mm. One hundred and seven patients (85.9%) achieved successful ureteral access insertion, including 81 (63.3%) without ureteral dilatation and 29 (22.7%) out of the 35 (27.3%) patients who needed ureteral dilation. Patients who underwent successful UAS placement into virgin ureters were significantly older and had a lower body mass index. A tent-shaped UO over the guidewire led to successful UAS insertion. In multivariate regression analysis, cases with body mass index (BMI) <30 kg/m2 (odds ratio [OR] 1.89, 95% confidence interval [CI] 1.28–7.03) and those with a tent-shaped UO over the introductory guidewire (OR 6.60, 95% CI 3.8–7.2) maintained their significance to predict successful UAS insertion into virgin ureters. Nine patients (8.2%) had ureteral mucosal injuries, and the overall stone-free rate was 78.2%. Conclusions: Patients with normal BMIs and tent-shaped UOs over the introductory guidewires are more likely to achieve primary UAS insertion without the need for ureteral dilation.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".