Under pressure: irrigation practice patterns during flexible ureteroscopy
Bibliographic record
Abstract
Introduction: Irrigation parameters during flexible ureteroscopy (fURS) may impact patient outcomes, yet there are limited data on current practice patterns of irrigation methods and parameter selection. We assessed the common irrigation methods, pressure settings, and situations that present the most problems with irrigation among worldwide endourologists. Methods: A questionnaire on fURS practice patterns was sent to Endourology Society members in January 2021. Responses were collected through QualtricsXM over a 1-month period. The study was reported according to the Checklist for Reporting Results of Internet E-Surveys (CHERRIES). Surgeons were from North America (the United States and Canada), Latin America, Europe, Asia, Africa, and Oceania. Results: Questionnaires were answered by 208 surgeons (response rate 14%). North American surgeons accounted for 36% of respondents; 29% Europe, 18% Asia, and 14% Latin America. In North America, the most common irrigation method was the pressurized saline bag using a manual inflatable cuff (55%). Saline bag (gravity) with a bulb or syringe injection system was the most common method in Europe (45%). Automated systems were the most common method in Asia (30%). For pressures used during fURS, the majority of respondents used 75-150 mmHg. The clinical scenario which had the greatest issue with adequate irrigation was during biopsy of urothelial tumor. Conclusion: There is variation in irrigation practices and parameter selection during fURS. North American surgeons primarily used a pressurized saline bag, in contrast to European surgeons who preferred a gravity bag with a bulb/syringe system. Overall, automated irrigation systems were not commonly used.
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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) | 0.000 | 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".