Laparoscopic Nephrectomy with Intact Specimen Extraction for Polycystic Kidney Disease
Bibliographic record
Abstract
PURPOSE: We present our technique and evaluate the experience of laparoscopic nephrectomy with intact specimen extraction for patients with autosomal dominant polycystic kidney disease (ADPKD). MATERIALS AND METHODS: We retrospectively reviewed 16 laparoscopic nephrectomies performed by one laparoscopic surgeon in a university hospital between April 2004 and March 2006. Preoperative, intraoperative, and postoperative follow-up data are presented. A 3- to 4-port transperitoneal laparoscopic approach was used to dissect the involved kidney, which was then removed intact through a Pfannenstiel or infraumbilical midline incision. RESULTS: A total of 16 patients were included in this study over a 2-year period. The average patient age was 49 years (range 29-67 years), and the average body mass index was 26.9 kg/m(2) (range 19.1-38.3 kg/m(2)). Eleven (69%) patients were receiving dialysis. The mean preoperative creatinine level was 520 mumol/L (range 108-976 mumol/L). Ten right (63%) and six left (37%) nephrectomies were performed. No patient had preoperative embolization. The mean operative time was 167 minutes (range 95-233 min). The mean blood loss was 76 mL (range 10-200 mL). No patient received a blood transfusion. The mean kidney pathologic size was 23 cm (range 16-35 cm), while the mean extraction size was 10.4 cm (range 8-12 cm). There were no deaths. There was one intraoperative complication (6.25%) and three postoperative ones (19%). No procedure was converted to an open approach. The mean length of hospital stay was 4 days (range 2-11 d). CONCLUSIONS: Laparoscopic nephrectomy for ADPKD is technically feasible and clinically safe. In addition to its low morbidity, other advantages of laparoscopic surgery are the ability to remove the dissected kidney through a small incision, short hospital stay, excellent cosmesis, and fast recovery.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| 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".