Hepatitis E virus in immunocompromised children in Argentina: first report from a high-risk group
Bibliographic record
Abstract
BACKGROUND: Hepatitis E virus (HEV) is an emerging zoonosis that can lead to chronic hepatitis in immunocompromised individuals. While HEV genotype 3 circulates in Argentina, data on pediatric populations, especially those immunosuppressed, are scarce. We hypothesized that immunosuppressed children in a region with known zoonotic HEV circulation would show higher seroprevalence compared to healthy controls. METHODS: This pilot descriptive cross-sectional study was conducted at a pediatric referral center in Rosario, Argentina, from 2018 to 2020. Fifty-eight immunocompromised children (aged 8 months-17 years) were enrolled, alongside 101 age-matched healthy controls. Anti-HEV IgG and IgM antibodies were detected by ELISA; HEV RNA was assessed by RT-qPCR. Statistical analyses included chi-square and logistic regression tests. RESULTS: Anti-HEV IgG was detected in 6.9% (4/58) of immunosuppressed patients, whereas no seropositivity was observed among controls (0/101; p = 0.0075). No cases of active or recent infection (IgM or RNA positive) were found. Anti-HEV IgG prevalence was highest among adolescents (10.0%) and patients with autoimmune diseases (28.6%), though subgroup comparisons lacked statistical significance. One IgG-positive patient had prior intravenous immunoglobulin exposure, suggesting possible passive antibody transfer. CONCLUSIONS: This study provides the first evidence of HEV exposure in immunosuppressed pediatric patients in Argentina, revealing a significantly higher seroprevalence compared to healthy peers. Although no active infections were detected, findings support the need for targeted HEV surveillance in high-risk pediatric groups, particularly in regions with confirmed zoonotic HEV circulation. Future multicenter, longitudinal studies are warranted to evaluate clinical outcomes and guide prevention strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".