Bibliographic record
Abstract
Introduction and Objectives: Ultrasonic intracorporeal lithotripters are used during percutaneous nephrolithotomy for stone fragmentation and removal.We performed standardized bench testing of the new ShockPulse TM stone eliminator against three commercially available systems to determine differences and nuances in performance against both hard and soft stones.Methods: The new ShockPulse (Olympus) intracorporeal lithotripter was tested against the LUS-2 TM (Olympus), Cyberwand TM (ACMI/Olympus) and EMS LithoClast TM in a standardized setting using hard (Utracal 30: U30) or soft (plaster of Paris: POP) stones.Using a rigid nephroscope, irrigation, camera, and video screen, the time to fragment equally sized U30 and POP stones in a rubber kidney model was assessed by three surgeons.The time needed to fragment each stone into pluckable fragments was first recorded, followed by the time to fully eliminate all fragments with the lithotripter.To determine the efficacy of each system at various pressures, a hands-free apparatus was used to transmit 1, 1.5, and 2 lbs of fixed force to both solid cylindrical stones and groups of six smaller stone fragments.The time required to fragment the stones was recorded at each fixed force. Results:The time to create pluckable fragments in the kidney model was similar among all four lithotripters for both POP stones (17-23 seconds) and U30 stones (25-33 seconds).The time to total fragmentation of free stones was similar for three of the lithotripters (45-66 seconds), which were all significantly faster than the Cyberwand system (112 seconds, p=0.046) for both U30 and POP stones (p=0.001).When fixed force testing was applied to solid cylindrical stones, the ShockPulse and Cyberwand were significantly faster at all fixed forces (p<0.0001).The LUS-2 was unable to fragment stones at 1 or 2 lbs of fixed force, and was only able to penetrate at 1.5 lbs of force.When fixed force testing was applied to the six smaller fragments, the ShockPulse was significantly faster than the other models at 1 lb (p<0.001) and 1.5 lbs (p<0.002).At 2 lbs, the Cyberwand was the slowest (p<0.0001), with no observed difference between the other three lithotripters (p=0.09). Conclusions:The ShockPulse lithotripter is equally as effective as current commercially available lithotripters.It was significantly faster at fragmenting stones at lighter fixed forces, which are more in keeping with those pressures applied clinically.The ShockPulse also performed equally well at greater fixed forces.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.230 | 0.079 |
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".