Splenic vasculitis, thrombosis, and infarction in a febrile dog infected with <i>Bartonella henselae</i>
Bibliographic record
Abstract
OBJECTIVE: To describe the clinical course and successful management of a febrile dog with polyarthritis, splenic vasculitis, thrombosis, and infarction that was infected with Bartonella henselae. CASE SUMMARY: An 8-year-old female spayed Labrador Retriever was referred to The Ohio State University Veterinary Medical Center Emergency Service for evaluation of limping, fever, vomiting, and malaise of 4 days' duration. Physical examination abnormalities included generalized weakness, diminished conscious proprioception, bilateral temporalis muscle atrophy, and diarrhea. Peripheral lymph nodes were normal, and there were no signs of abdominal organomegaly, joint effusion, or spinal pain. Abdominal ultrasound identified a nonocclusive splenic vein thrombus. Fine-needle aspirates of the spleen revealed pyogranulomatous inflammation, mild reactive lymphoid hyperplasia, and mild extramedullary hematopoiesis. Splenic histopathology found marked, multifocal to coalescing acute coagulation necrosis (splenic infarctions) and fibrinoid necrotizing vasculitis. Bartonella henselae DNA was amplified by polymerase chain reaction and sequenced from the splenic tissue. The dog responded favorably to antimicrobials and was healthy at the time of follow-up evaluation. NEW AND UNIQUE INFORMATION PROVIDED: Bartonella henselae is an incompletely characterized emerging canine pathogen. This case report establishes a potential role for this bacterium as a cause of vasculitis and thromboembolism, which have not been previously reported in association with B. henselae infection in dogs.
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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) | 0.000 | 0.000 |
| 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".