Necrotizing meningoencephalitis in a large mixed-breed dog
Bibliographic record
Abstract
CASE DESCRIPTION: A 4-year-old 26-kg (57.2-lb) spayed female Staffordshire Bull Terrier mix was evaluated because of a 24-hour history of cluster seizures. CLINICAL FINDINGS: Neurologic examination revealed altered mentation and multifocal intracranial signs; MRI was performed. The MRI findings included multifocal, asymmetric forebrain lesions affecting both the gray and white matter, an area suggestive of focal necrosis, and loss of corticomedullary distinction. A midline shift and caudal transtentorial herniation were noted, suggestive of greater than normal intracranial pressure. TREATMENT AND OUTCOME: Because the dog's clinical signs worsened despite medical treatment and additional evidence of increased intracranial pressure, bilateral craniectomy and durectomy were performed. Histologic evaluation of a brain biopsy specimen revealed bilateral and asymmetric areas of necrosis in the subcortical white matter and adjacent gray matter. At the periphery of the necrotic areas, there was increased expression of glial fibrillary acidic protein and Virchow-Robin spaces were expanded by CD3+ lymphocytes. Results of immunohistochemical analysis of brain tissue were negative for canine distemper virus, Neospora canis, and Toxoplasma gondii. These clinical, imaging, and histopathologic findings were compatible with necrotizing meningoencephalitis. The dog's neurologic status continued to worsen following surgery. Repeated MRI revealed ongoing signs of increased intracranial pressure, despite the bilateral craniectomy. The owners elected euthanasia. CLINICAL RELEVANCE: To the author's knowledge, this is the first report of necrotizing meningoencephalitis in a large mixed-breed dog. Necrotizing meningoencephalitis should be considered as a differential diagnosis in dogs other than small or toy breeds that have signs suggestive of inflammatory disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| 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 | 0.001 |
| 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 teacher head, 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".