Intrarenal Pressure Measured Using a Novel Flexible Ureteroscope with Pressure Sensing Capabilities: A Study of the Effects of Ureteral Access Sheath, Irrigation, and Working Channel Accessories
Bibliographic record
Abstract
Introduction: Intrarenal pressure is emerging as an important monitoring parameter during flexible ureteroscopy (fURS). We measure how intraoperative conditions affect intrarenal pressure using a novel pressure sensing ureteroscope. Methods: The LithoVue Elite (LVE) single-use digital flexible ureteroscope (Boston Scientific) is the first commercial ureteroscope that senses pressure at its tip. LVE was used in a porcine model to measure intrarenal pressure with and without a ureteral access sheath (UAS) with various sizes and placement locations, irrigation methods, and working channel accessories. LVE pressure accuracy was measured in a bench model. This abstract shows the least-square means from multiway analysis of variances used for analysis. Results: Intrarenal pressures were the highest without a UAS (64 mm Hg), followed by the 11/13 UAS (51 mm Hg) and the 12/14 and 13/15, which were not statistically different (39–40 mm Hg). The pressures were highest with UASs placed at the ureteropelvic junction (61 mm Hg), and lowest if placed in the renal pelvis (24 mm Hg). Irrigation methods showed the highest pressures with syringe (57 mm Hg), while irrigation bags (pressurized at 150–300 mm Hg) produced 43 to 46 mm Hg and 25 mm Hg when applied with 80 cm of gravity. Placing a 200 μm laser fiber reduced pressures from 44 to 41 mm Hg. Finally, the bench model showed that LVE was 96% accurate up to 300 mm Hg. Conclusion: Intrarenal pressure significantly varied based on UAS sizes, placement, and irrigation methods. Accordingly, fURS with LVE is poised to be an invaluable tool for clinical decision-making and future studies of intrarenal pressure.
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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".