Retrospective first‐in‐human use of the LithoVue™ Elite ureteroscope to measure intrarenal pressure
Bibliographic record
Abstract
OBJECTIVE: To report on our first-in-human experience using the LithoVue Elite™ ureteroscope (Boston Scientific Corp., Marlborough, MA, USA) to measure intrarenal pressure (IRP) during flexible ureteroscopy. PATIENTS AND METHODS: A single-arm retrospective observational analysis was performed in 50 consecutive patients undergoing ureteroscopic lithotripsy using the LithoVue Elite™ system with pressure sensing capability between April 2022 and February 2023 at two centres. A pressure bag set at 150 mmHg or hand irrigation with a 60-mL syringe was used for irrigation and a ureteric access sheath (UAS) was placed at the physician's discretion. Median and maximum IRPs, and relative cumulative time exceeding 20, 40, 60, 80, 100, 120, 140, 160, and 200 mmHg per total procedure time were analysed. The two-sample Mann-Whitney U-test was used, with statistical significance set at P < 0.05. RESULTS: , respectively. During the median (IQR) total procedure time of 31.9 (17.4-44.9) min, the median and maximum IRPs were 28.5 (20.0-47.5) and 174.0 (133.5-266.0) mmHg, respectively. IRP remained at <60 mmHg during 92% of the procedure times. Patients with Asian ethnicity, and those without pre-stenting or UAS use exhibited longer cumulative/total durations exceeding pre-defined IRP cut-off values. The smaller 10/12-F UAS did not lower pressures as much as the 11/13-F or 12/14-F UAS (P < 0.001). Age, diabetes, hypertension, preoperative α-blockade, stone size, and BMI did not show any statistically significant associations with IRP. CONCLUSIONS: The IRP can now be routinely measured during ureteroscopy. Patients had a median IRP of 28.5 mmHg and a maximum of 174 mmHg. Using a smaller UAS (10/12 F), Asian ethnicity, and tight ureters were found to have higher IRPs.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".