Uses and Effectiveness of Pamidronate Disodium for Treatment of Dogs and Cats with Hypercalcemia
Bibliographic record
Abstract
Uncorrected hypercalcemia can cause clinical signs such as polyuria, polydipsia, vomiting, diarrhea, lethargy, and depression and contributes to the development of primary renal failure and soft tissue mineralization. Treatment of hypercalcemia includes diagnosis and treatment of the underlying disease process and some combination of excracellular fluid volume expansion by administration of fluids intravenously and administration of glococorticosteroids, salmon calcitonin, and furosemide. Bisphosphonates such as pamidronate disodium also may be safe and effective in the treatment of hypercalcemia. The purpose of our study was to characterize the efficacy and safety of pamidronate in the treatment of hypercalcemia attritutable to several different disease processes in the dog and cat. Seven dogs and 2 cats were administered pamidronate at a dose of 1.05-2.0 mg/kg IV for a variety of disease processes, including neoplasia (n = 4), calcipotriene toxicity (n = 3), nocardiosis (n = 1), and idiopathic hypercalcemia with chronic renal failure (n = 1). In all the animals, IV pamidronate administration rapidly decreased serum calcium concentrations without evident toxicosis. Two animals received pamidronate several times without obvious toxicosis. On the basis of the findings in our retrospective study, pamidronate may be a safe and effective drug with which to lower both serum total and ionized calcium concentrations in patients with hypercalcemia arising from a wide variety of underlying disease processes.
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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) | 0.000 | 0.000 |
| 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) | 0.000 | 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".