Pediatric Echinococcosis of the Liver in Austria: Clinical and Therapeutical Considerations
Bibliographic record
Abstract
Echinococcosis is considered a neglected disease in most European countries. However, migratory flows of populations, long-term stays in endemic areas, uninterrupted tourism (travel to Echinococcus-endemic countries), traveling dogs and dog translocations from endemic areas, and inappropriate hygiene practices are potential factors that alarm public health officials. Identifying a cyst-like mass in the liver or lung of an individual with a travel history of likely exposure to sheepdogs in an area where the parasite Echinococcus (E.) granulosus (sive cysticus) is endemic advocates for a prompt preliminary diagnosis of cystic echinococcosis (CE), no matter the age of the affected individuals. Routine imaging techniques, including ultrasonography, computed tomography (CT) scans, and magnetic resonance imaging (MRI) scans, are used to detect cysts. After a cyst has been discovered, serologic investigations are used to confirm the diagnosis. Typically, alveolar echinococcosis (AE) is found in older individuals. Yet young people are also affected because frequent oral exploration of the environment is a regular behavior for infants and toddlers. In this review, therapeutic considerations for pediatric echinococcosis—drug-based benzimidazole therapy; AE: atypical liver resection, the resection of individual or multiple segments, a right or left hemi-hepatectomy, or an extended hemi-hepatectomy; CE: PAIR-technique, cyst excision, liver segment(s) resection (laparoscopically or conventionally)—are revised following experience in one of the most affected regions of Europe. In addition, we performed a systematic review using three databases (i.e., PubMed, EMBASE, and Scopus) to evaluate the quality of evidence in published studies on pediatric echinococcosis.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".