Use of denosumab to treat refractory hypercalcemia in a peritoneal dialysis patient with immobilization and tertiary hyperparathyroidism
Bibliographic record
Abstract
Hypercalcemia due to excess parathyroid hormone (PTH) production is a common condition among patients with end-stage renal disease (ESRD), often referred to as tertiary hyperparathyroidism. There are limited effective medical treatment options currently available for such patients. Denosumab is a monoclonal antibody that inhibits osteoclast activation, thereby reducing calcium release from bones. Denosumab has been used to treat medically-refractory hypercalcemia in non-ESRD patients with hyperparathyroidism. Denosumab has also been used to treat non-PTH-mediated hypercalcemia in patients with advanced chronic kidney disease and ESRD. In this case report, we describe the use of denosumab to successfully treat a case of medically refractory hypercalcemia due to immobilization in a patient on peritoneal dialysis with severe underlying tertiary hyperparathyroidism. In spite of persistently elevated PTH, hypercalcemia quickly resolved after a single dose of denosumab. The patient subsequently developed temporary hypocalcemia requiring medical intervention. Our case report, which is the first described use of denosumab for treatment of hypercalcemia in the setting of tertiary hyperparathyroidism in a peritoneal dialysis patient, adds to the body of literature suggesting denosumab is a useful therapeutic agent in patients with ESRD. Issues with post-treatment electrolyte management and other therapeutic considerations are also discussed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 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".