A retrospective study of severe acute hepatitis cases of unknown etiology in pediatric patients reveals the presence of adenovirus involvement in central India
Bibliographic record
Abstract
Objectives: Human adenovirus (HAdV) is increasingly identified as a potential cause of pediatric acute hepatitis of unknown etiology. This study aimed to detect HAdV in children with acute hepatitis or jaundice who tested negative for common bacterial and viral causes of hepatitis, including hepatitis viruses (A-E) and other bacterial pathogens, by serological and molecular assays. Methods: A retrospective study was conducted on pediatric patients (aged ≤14 years) with acute hepatitis or jaundice who tested negative for hepatitis A-E. HAdV was detected using real-time polymerase chain reaction, followed by Sanger sequencing for genotype identification. Biochemical markers of liver function were assessed to confirm hepatitis. Results: Of 227 pediatric cases suspected of hepatitis/jaundice, 11 (4.85%) tested positive for HAdV using real-time polymerase chain reaction and Sanger sequencing. Of the 11 sequences, four were identified as HAdV type 41 and seven as HAdV type 7. Elevated liver enzymes were observed in nine HAdV-positive cases, supporting a clinical diagnosis of hepatitis. Conclusions: This study highlights HAdV, particularly, types 7 and 41, as notable causative agents of hepatitis in children who tested negative for common hepatitis viruses. To the best of our knowledge, this is the first study from India to report HAdV as a potential etiological agent associated with hepatitis in a notable number of such cases.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".