Transperitoneal laparoscopic heminephroureterectomy in the pediatric population: A single-centre experience using a sealing device
Bibliographic record
Abstract
Introduction: We sought to report the outcomes of transperitoneal laparoscopic heminephroureterectomy (LHNU) in a pediatric population and to describe the technical details of this minimally invasive surgery.Methods: Seventeen pediatric patients (18 renal units), who had consecutive transperitoneal LHNU in our department between January 2012 and July 2017 were included in the study. In all patients, diagnostic cystoscopy and retrograde pyelography were carried out immediately before the operation. A catheter was inserted in the unaffected ureter and fixed. LHNU with a transperitoneal approach was carried out in all patients with the aid of LigaSure®. After removal of the specimen, the intervention was finalized with the insertion of a drain. All intraoperative and postoperative data of the patients were recorded prospectively.Results: The average age of the patients was 55.9±35.8 months (range 8–121). The average duration of the operations was 121.7±24.0 minutes (range 100–200). The average hospitalization time was 1.6±0.4 days (range 1–2). No intraoperative complication occurred in our patients. The average followup period was 29.1±13.4 months (range 4–48). During the followup period, no complications were observed except one patient who had pyelonephritis within the first month of surgery.Conclusions: Transperitoneal LHNU is a minimally invasive method that can be used safely in pediatric patients. Using a standardized technique during the procedure is critical to increase the success and decrease the complication 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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".