Flexible Nephroscopy: A Step Towards Complete Stone Clearance in PCNL
Bibliographic record
Abstract
Objectives To determine the usefulness of flexible nephroscopy after per-cutaneous nephrolithotomy (PCNL) in detecting residual fragments. Materials and Methods A prospective study was conducted between January 2018 and December 2019 on patients undergoing standard PCNL using a flexible nephroscope to inspect all the calyces for residual stones. When residual stones were noted, either they were removed by basketing or by performing additional puncture to ensure complete clearance. Patients were followed up for 6 months and at the end of 1 month a plain CT KUB was done to look for residual fragments. Results The study cohort included 212 patients. Significant RFs were found in 28 patients during flexible nephroscopy and in two patients at 1 month follow up CT scan. All patients were stone free during 6 months follow up. Conclusion Flexible nephroscopy during PCNL decreases the chance of residual fragments and thereby reducing the chance of re-procedure rates.
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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 | 0.005 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".