Preliminary Outcome Comparison of Flexible Uretero-Renoscopic Lasertripsy Versus PCNL in the Treatment of Staghorn Calculi
Bibliographic record
Abstract
Percutaneous nephrolithotomy (PCNL) is a well-established treatment for staghorn stones. Given the im-provement in technology and techniques of flexible ureterorenoscopic lasertripsy (FURS), we retrospectively compared its treatment outcome against PCNL for staghorn stones at our institution. Materials and Methods All patients with partial and complete staghorn stones treated by FURS or PCNL between December 2014 and December 2017 were included. Outcome measures included the duration of the procedure, length of stay, retreatment rate, auxiliary rate, complications, and clinical success rates (stone or dust-free status). Results Out of 22 staghorns, 10 (1 complete, 9 partial) had FURS and 12 (2 complete and 10 partial) had PCNL. Comparatively, the FURS group were older (mean 70.1 vs. 57.1 years, U-test p<0.001) with higher mean ASA scores (mean 2.3 vs. 1.5, U-test, p=0.04), with a similar body-mass index (mean 29.1 vs. 27.3), maximum stone size (29.7 vs. 34.6mm) and Hounsfield unit (836 vs. 891HU). FURS was quicker to clinical success (102.4min vs. 159.5min, U-test p<0.001) and had shorter hospital stay (1.1d vs. 3.5d, U-test p<0.001). Higher primary procedure success [80% vs. 36%, 95% CI = (-3.0%, 74.5%)], higher overall success [90% vs. 73%, 95% CI = (-22%, 51%)], similar retreatment rate (10%), and higher auxiliary treatment rate (100% vs. 18%) were observed. 1 patient from FURS had a small intrapa-renchymal aspect of staghorn inaccessible to a laser. There were no complications in the FURS group. In the PCNL group, one developed a pseudoaneurysm requiring embolization, and 1 had failed PCNL access (excluded from the statistical calculation). Conclusion Our preliminary data suggest that FURS is efficacious and safe for staghorn stones treatment, and comparable to PCNL. In this context, we highlight FURS potential role as first-line management of staghorn stones.
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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".