The outcome of nephrectomy in peritoneal dialysis patients.
Bibliographic record
Abstract
Data regarding the outcomes of peritoneal dialysis (PD) patients undergoing nephrectomy are limited. In the 20-year retrospective study reported here, we included patients who underwent nephrectomy and then subsequently started PD within 1 year (group A) and those who underwent nephrectomy while already on PD (group B). We examined mechanical complications including incisional hernia, peritoneal leak, and wound infection or dehiscence. Among biochemical outcomes (group B only), we analyzed serum creatinine, albumin, potassium, and phosphate for 1 year pre- and post-nephrectomy. Among the 8 patients identified (4 in group A, 4 in group B), 7 underwent unilateral nephrectomy, and 1, bilateral nephrectomy. Surgery was laparoscopic in 1 patient and open in 7 patients. The approach was transperitoneal in 5 patients, and retroperitoneal in 3 patients. Incisional hernia occurred in 4 patients (2 in each group), and retroperitoneal leak was seen in 1 patient in group B after 2 months. No wound dehiscence or other complications occurred. In group B, 2 patients required hybrid therapy in the form of once-weekly hemodialysis with continuous ambulatory PD. Among the biochemical complications, we noted that serum creatinine increased (as expected), and serum albumin significantly declined and remained lower post-nephrectomy. Our data show that, post-nephrectomy, PD patients have a high incidence of incisional hernia. They also experience a significant decline in serum albumin and a substantial loss in residual kidney function potentially requiring intensified dialysis. The retroperitoneal approach may on occasion predispose to retroperitoneal leak of dialysate.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".