Introduction of 1.9 mm Trilogy lithotripter in miniature percutaneous nephrolithotomy
Bibliographic record
Abstract
Introduction: We aimed to evaluate the novel use of a 1.9 mm Trilogy lithotripter probe with varying locations and composition of renal stones. Methods: We prospectively enrolled patients to undergo mini percutaneous nephrolithotomy (mPCNL) procedures using the 1.9 mm (instead of the standard 1.5 mm) Trilogy probe from August 2021 to April 2022. Several adjunctive irrigation measures compensated for reduced flow with the larger probe. Primary outcome was treatment efficiency. Patient demographics, preoperative demographics, and comorbidities, as well as real-time surgical data were extracted. Statistical analysis was performed using Kruskal-Wallis tests to compare stone type and location. Results: A total of 110 patients were included in this study. The median total treatment time was 6.8 minutes, median lithotripsy time was 3.3 minutes, median stone treatment efficiency was 0.34 mm/min, and treatment efficacy was 50.4 (lithotripter time/treatment time). Overall median lithotripter efficiency was 104.6 mm3/min. Treatment efficiency was similar among stone composition (p=0.245) and location (p=0.263). Lithotripter 3D and 1D efficiency was also similar among stone composition (p=0.637 and p=0.766, respectively). Lithotripter 1D efficiency was nearly twice as fast in the lower pole compared to other stone locations (p=0.010). Overall broken probe rate for this procedure was 12%, mostly at the beginning, suggesting a learning curve. Five patients had minor complications, including one patient that required admission to the hospital for postoperative pain management. Conclusions: The 1.9 mm Trilogy lithotripter can be effective in mPCNL procedures with the use of easily implementable adjunctive irrigation techniques, decreasing the gap between lithotripsy time and total treatment time.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".