Visceral larva Migrans in a Young Italian Patient: A Diagnostic Dilemma
Bibliographic record
Abstract
BACKGROUND: The association of fever, focal hepatic lesions and peripheral hyper-eosinophilia (FHLH) can be observed in both infectious and non-infectious conditions. Fascioliasis, capillariasis, toxocariasis, all causes of visceral larva migrans (VLM), represent most of the former, whilst lymphomas, eosinophilic leukemias and mastocytosis belong in the non-infectious conditions. METHODS: We prospectively followed a young patient presenting with FHLH in the Tuscany region of Italy. RESULTS: The patient was subject to serological and parasitological examination in an attempt to clarify the origin of the lesions. Serologies for both Fasciola hepatica and Toxocara spp. were positive, with the latter presenting a higher index. We opted for treatment with a prolonged course of albendazole due to the serological results and being toxocariasis more frequent in our setting. The patient was then subject to radiological follow-up. The patient responded to treatment with albendazole as shown by a decrease in eosinophils, seronegativization for Toxocara spp., clinical and radiological improvement. Toxocariasis was hence considered the most likely diagnosis. CONCLUSIONS: Parasitic infections cannot be disregarded in the presence of FHLH. Differential diagnosis between these parasitic infections can be challenging due to the presence of similar clinical presentations and serological cross-reactions, and follow-up of the patient is needed to ensure optimal treatment outcomes.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".