HEPATIC VISCERAL LARVA MIGRANS, AN UNCOMMON DIAGNOSTIC ENTITY, HOW TO OVERCOME THE DIAGNOSTIC CONUNDRUM- A CASE REPORT
Bibliographic record
Abstract
Background: Visceral larve migran (VLM) is the systemic host inflammatory response of the nematods like taxacara canis. It is not a rare entity but due to non-specific radiological features establishment of diagnosis is challenging. The condition is referred to as visceral larva migrans because the lesions move slowly. On imaging appear as single or conglomerated poorly defined lesions with no significant enhancement on the contrast study. Imaging features are mimicking the diagnosis of the metastasis, multifocal HCC and other granulomatous disease. We are presenting the biopsy proven case of visceral larve migran and discussing the key features to establish the diagnosis with confidence. Case Presentation- A 48- year-old female presented with epigastric pain radiating to the back for three weeks, accompanied by fever in the first week. Clinical examination revealed no jaundice or pruritus. Lab tests showed marked eosinophilia (42.9%) but normal liver and renal function. Imaging (USG, CT, MRI) revealed multiple hypodense liver lesions along portal vein branches. Liver biopsy confirmed granulomatous inflammation with eosinophils and Charcot-Leyden crystals, indicating visceral larva migrans (VLM). She was treated with albendazole for three weeks, with plans to extend based on clinical response. Symptoms improved after two weeks, with follow-up imaging scheduled in three months. Conclusion- Hepatic VLM diagnosis is challenging due to nonspecific imaging; eosinophilia and biopsy confirmation are key for timely management.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".