Current use of medical expulsive therapy among endourologists
Bibliographic record
Abstract
INTRODUCTION: We aimed to characterize current practice patterns among endourologists on medical expulsive therapy (MET) for treatment of ureteral calculi. METHODS: An online survey was administered to Endourological Society members. Respondents' MET usage, index case management, and awareness of recent guidelines and literature were compared based on international status, practice setting, interval since training, and endourological fellowship training. RESULTS: Of the 237 complete responses, 65% were international, 61% were academic, 66% had >10 years in practice, and 71% were endourology fellowship-trained. MET was used by 88%, with no differences between international, academic, practice length, and fellowship-trained groups. MET was used more frequently for <8 mm and distal stones and more U.S.-based respondents reported use for proximal/midureteral stones (68% vs 43%; p<0.001). For the index patient, 70% preferred MET as the initial approach and respondents <10 years from training were more likely to choose MET (82% vs. 64%; p=0.006). While 82% of respondents were aware of the SUSPEND trial, 70% reported that it had not altered their use of MET. Current American Urological Association (AUA) guideline awareness was 90%. Mean MET prescription length was 19.9±10.3 days, and was statistically significantly longer for respondents who were U.S.-based, academic and <10 years from training. CONCLUSIONS: MET is the preferred approach for patients with ureteral calculi <10 mm among endourologists despite conflicting data in the literature. While current AUA practice guidelines are followed by the majority of respondents, our survey suggests MET is being used more liberally than the guideline criteria, specifically in proximal and midureteral stones.
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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) | 0.002 | 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".