Fibrous osteodystrophy due to secondary renal hyperparathyroidism in a senile dog
Bibliographic record
Abstract
ABSTRACT Renal hyperparathyroidism stands out among the complications of kidney disease in dogs due to phosphorus retention with a predisposition to hypocalcemia, parathyroid hormone stimulation with mobilization of calcium from the bones, characterizing fibrous osteodystrophy, unusual in the elderly. The objective was to report it in 12-year-old Labrador with polyuria, polydipsia, and emesis for five months due to maxillary and mandibular volume increase, followed by loosely fixed teeth, and facial deformity. Blood tests showed anemia, thrombocytosis, azotemia, hypoalbuminemia and hyperphosphatemia and urinalysis showed low density, glycosuria, proteinuria, and moderate caudate and transitional epithelial cells. Oral x-rays showed loss of dental bone support and decreased bone radiopacity. Chest radiographs showed decreased density in the ribs and costochondral junction; on the other hand, organs of the cardiorespiratory system showed no changes. The electrocardiogram and echocardiogram did not show impairment. Abdominal ultrasound revealed kidneys with asymmetry, increased echogenicity of the cortical and poorly preserved cortico-medullary definition. Oral histopathology showed intense fibroplasia associated with bone reabsorption. Support therapy was instituted, but the patient died ten days after consultation. Thus, although uncommon in the elderly, fibrous osteodystrophy should be investigated in dogs with advanced-stage chronic kidney disease and, even with conservative therapies, the prognosis is unfavorable.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".