High level of persistent liver injury is one of clinical characteristics in treatment‐naïve acute onset autoimmune hepatitis: experience in a community hospital
Bibliographic record
Abstract
BACKGROUND: There is, as yet, no gold standard for making the diagnosis of acute onset autoimmune hepatitis (A-AIH). Novel histological characteristics have been reported, but etiologies other than AIH could show similar histological pattern. We attempted to determine what clinical characteristics we should consider as A-AIH different from other etiologies, and to whom histological characteristics should be applied for the diagnosis. METHODS: Clinical, biochemical, immunological and pathological features of 46 patients (35 women, mean age 55.9 ± 14.2 years) with non-severe A-AIH admitted to a community hospital between 2001 and 2015 were analyzed. RESULTS: Immunoglobulin G level was normal in 28%, and anti-nuclear antibody titer was < × 80 in 28%. Liver histology of 49% showed acute form and 51% chronic one. Centrilobular necrosis/collapse and/or plasma cell accumulation, rosette formation were characteristic for A-AIH. High levels of alanine aminotransferase persisted in 21 patients who could be observed for equal to or more than 4 weeks before the start of treatment. CONCLUSIONS: Long persistence of high levels of alanine aminotransferase would be one of clinical features for considering A-AIH along with conventional features. Histological diagnostic features should be applied for such patients. Guidelines for diagnosing A-AIH should be urgently drawn up.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".