Effects of Parathyroidectomy on Renal Allograft Survival
Bibliographic record
Abstract
BACKGROUND: Hyperparathyroidism is a common problem secondary to renal insufficiency and is often not entirely resolved after renal transplantation (TX). METHODS: In this retrospective analysis, the effects of parathyroidectomy (PTX) on allograft function were evaluated and the risk factors involved in allograft deterioration in patients after PTX will be discussed. RESULTS: The rise in creatinine was steeper 1 year after PTX compared to 2 years before PTX in the majority (13 of 22) of patients. Compared to a cohort without PTX, graft survival was significantly decreased by 60% in 6 years (p < 0.0001). After multivariate adjustment, risk factors attributed to graft function included baseline creatinine (p = 0.02), baseline systolic blood pressure (p = 0.04) and time between TX and PTX, but not PTX itself. The peri-PTX drop in serum calcium was significantly more accentuated in patients exhibiting a worsening of graft function after PTX (p = 0.04). CONCLUSIONS: In patients requiring PTX, graft function is in danger of worsening. Since many factors contribute to this negative correlation and no association with parathyroid hormone (PTH) levels before PTX has been observed, we do not recommend prophylactic PTX on the basis of PTH levels only. However, appropriate management of peri-PTX risk factors is highly important. If the clinical situation, e.g. progressive renal osteodystrophy, requires removal of parathyroid glands, the procedure should be performed, if possible, in the presence of stable graft function.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".