Retrospective Study Looking at Cinacalcet in the Management of Hyperparathyroidism after Kidney Transplantation
Bibliographic record
Abstract
Objectives.The primary objective of this study is to evaluate the use of cinacalcet in the management of hyperparathyroidism in kidney transplant recipients. The secondary objective is to identify baseline factors that predict cinacalcet use after transplantation.Methods.In this single-center retrospective study, we conducted a chart review of all patients having been transplanted from 2003 to 2012 and having received cinacalcet up to kidney transplantation and/or thereafter.Results.Twenty-seven patients were included with a mean follow-up of 2.9±2.4 years. Twenty-one were already taking cinacalcet at the time of transplantation. Cinacalcet was stopped within the first month in 12 of these patients of which 7 had to restart therapy. The main reason for restarting cinacalcet was hypercalcemia. Length of treatment was 23±26 months. There were only 3 cases of mild hypocalcemia. There was no statistically significant association between baseline factors and cinacalcet status a year later.Conclusions.Discontinuing cinacalcet within the first month of kidney transplantation often leads to hypercalcemia. Cinacalcet appears to be an effective treatment of hypercalcemic hyperparathyroidism in kidney transplant recipients. Further studies are needed to evaluate safety and long-term benefits.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".