Presumptive phenobarbital-induced systemic lupus erythematosus in a domestic dog
Bibliographic record
Abstract
CASE DESCRIPTION: We describe a case of presumptive acquired systemic lupus erythematosus secondary to phenobarbital administration in a dog, which resolved with withdrawal of the drug. CLINICAL FINDINGS: A 3.5 year-old poodle presented to a veterinary teaching hospital for Tier 1 idiopathic epilepsy and was treated with phenobarbital. The dog experienced fever, multiple cytopenias, and proteinuria in conjunction with a positive antinuclear antibody (ANA) titer. DIAGNOSTICS: Serial CBCs, urine protein : creatinine ratios, and sternal bone marrow aspirates were performed to evaluate improvement. TREATMENT AND OUTCOME: Phenobarbital was withdrawn and levetiracetam initiated. All abnormalities resolved with supportive care, without initiation of immunosuppressive drugs. All cytopenias and proteinuria resolved and ANA test results became negative within 3 months. The patient recovered and did well clinically. CLINICAL RELEVANCE: Systemic lupus erythematosus is a disease of multiple autoimmune syndromes occurring concurrently or sequentially in conjunction with the presence of circulating ANA. It has been well described in dogs as an idiopathic condition, but in human medicine may occur secondary to drug reactions (drug-associated lupus) including as a reaction to phenobarbital. The findings in our case are consistent with the criteria for drug-induced lupus in humans and we suggest it as the first report of phenobarbital-induced lupus in a dog.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".