Imported case of canine viscerocutaneous leishmaniasis in South Korea: clinical presentation and diagnostic approach in a Labrador Retriever
Bibliographic record
Abstract
IMPORTANCE: Leishmaniasis, a sandfly-borne disease, can infect both humans and dogs, with dogs acting as key reservoirs. This report documents the first case of leishmaniasis in South Korea, identified in a dog imported from Spain. It highlights the importance for early detection and careful monitoring of dogs imported from endemic regions to prevent the introduction and spread of leishmaniasis to regions such as South Korea, where the disease is rare. CASE PRESENTATION: A 2-year-old male Labrador Retriever dog, imported from Spain at 12 months old, was presented with a 5-month history of generalized cutaneous lesions and a 1-month history of chronic diarrhea. Microscopic examination of peripheral blood smears revealed amastigote-infected macrophages and whole-blood polymerase chain reaction confirmed a diagnosis of viscerocutaneous leishmaniasis. The dog was treated with allopurinol, the only available treatment for leishmaniasis in South Korea, alongside supportive management. However, the patient showed a poor response to treatment. CONCLUSIONS AND RELEVANCE: This case of canine leishmaniasis in South Korea highlights the growing risk of imported infections in non-endemic areas and underscores the need for greater awareness and understanding of the clinical features of Leishmaniasis for timely diagnosis and management in dogs with a history of travel or adoption from endemic regions.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".