High-Powered Holmium-Laser Ablation: Comparison of Setting Effectiveness Using Tissue-Surrogate Model
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The 100-W holmium laser, in conjunction with a sidefiring 550-microm fiber, can ablate prostate glands as large as 40 g to relieve lower urinary-tract symptoms. We evaluated the effect of various setting combinations on ablation efficiency using beef kidney as a tissue-surrogate model. MATERIALS AND METHODS: Beef kidney specimens (mean weight 44.8 +/- 3.1 g) were secured in a cylinder, which was submerged in a water-filled tank through which a 27F resectoscope and 550-microm sidefiring fiber were positioned. Four energy/frequency combinations were tested, with each used to treat 10 kidney specimens. The difference between the mean pretreatment and post-treatment weights of each treatment group were compared statistically with Student's t-test. RESULTS: The largest mean weight difference after treatment (8.94 +/- 2.38 g) was achieved using 3.2 J and 25 Hz. This mass reduction was significantly greater than that of all other combinations except 2.5 J and 40 Hz. CONCLUSIONS: Use of the 3.2 J and 25 Hz setting combination resulted in the greatest amount of ablation in this tissue-surrogate model, suggesting that maximal energy settings may provide an advantage in tissue vaporization using the 100-W holmium laser. Clinical assessment must be performed to substantiate these findings.
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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 | 0.001 | 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 | 0.001 |
| 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".