Native nephrectomy prior to pediatric kidney transplantation: biological and clinical aspects
Bibliographic record
Abstract
BACKGROUND: Pre-transplant nephrectomy is performed to reduce risks to graft and recipient. The aims of this study were to evaluate (1) indications, surgical approach, and morbidity of native nephrectomy and (2) the effects of kidney removal on clinical and biological parameters. METHODS: This study was designed as a single-center retrospective cohort study in which 49 consecutive patients with uni- or bilateral native nephrectomies were identified from a total of 126 consecutive graft recipients in our pediatric kidney transplantation database between 1992 and 2011. Demographic, clinical, and laboratory details were extracted from charts and electronic records, including operation reports and pre- and post-operative clinic notes. RESULTS: Of the 49 nephrectomized patients, 47% had anomalies of the kidneys and urinary tract, 22% had cystinosis, 12% had focal segmental glomerulosclerosis, and 6% had congenital nephrotic syndrome. Nephrectomy decisions were based on clinical judgment, taking physiological and psychosocial aspects into consideration. Nephrectomy was performed in patients with polyuria (>2.5 ml/kg/h) and/or large proteinuria (>40 mg/m(2)/h), recurrent urinary tract infection or (rarely) hypertension. Urine output decreased from (median) 3.79 to 2.32 ml/kg/h (-34%), and proteinuria from 157 to 100 mg/m(2)/h (-40%) after unilateral nephrectomy (p=0.005). After bilateral nephrectomy, serum albumin, protein and fibrinogen concentrations normalized in 93, 73, and 55% of nephrectomized patients, respectively. Clinically relevant procedure-related complications (peritoneal laceration, hematoma) occurred in five patients. CONCLUSION: In summary, we demonstrate quantitatively that native nephrectomy prior to transplantation improved serum protein levels and anticipated post-transplant fluid intake needs in select children, reducing the risk of graft hypoperfusion and its postulated consequences for graft outcome.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".