Percutaneous Nephrolithotomy With One Shot Dilatıon Method: Is It Safe In Patients Who Had Open Surgery Before
Bibliographic record
Abstract
INTRODUCTION: This study aimed to evaluate whether one-shot dilatation technique is as safe in patients with a history of open-stone surgery as it is in patients without previous open-stone surgery. METHODS: Between January 2007 and February 2015, 82 patients who underwent percutaneous nephrolithotomy (PNL) surgery with one-shot dilation technique who previously had open-stone surgery were retrospectively reviewed and evaluated (Group 1). Another 82 patients were selected randomly among patients who had PNL with one-shot dilation technique, but with no history of open renal surgery (Group 2). Age, gender, type of kidney stone, duration of surgery, radiation exposure time, and whether or not there was any bleeding requiring perioperative and postoperative transfusion were noted for each patient. RESULTS: The stone-free rates, operation and fluoroscopy time, and peroperative and postoperative complication rates were similar in both groups (p>0.05). CONCLUSIONS: Our experience indicated that PNL with one-shot dilation technique is a reliable method in patients with a history of open-stone surgery.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".