Diagnostic value and utility of the simplified International Autoimmune Hepatitis Group criteria in acute-onset autoimmune hepatitis
Bibliographic record
Abstract
BACKGROUND: The diagnosis of autoimmune hepatitis (AIH) is already difficult, and that of acute-onset AIH with atypical features is even more challenging, even though the revised original diagnostic criteria created by an international AIH group were widely accepted and incorporated into clinical practice. AIMS: Recently, simplified diagnostic criteria were proposed. We compared the performance parameters of the simplified scoring system in patients with acute-onset AIH and examined its usefulness and limitations. METHODS: Fifty-five patients with acute-onset AIH (29 non-severe, 14 severe and 12 fulminant) were assessed according to the simplified scoring system and compared with the revised original one. RESULTS: Of the 55 patients, 22 (40%) were diagnosed as 'definite' AIH, 28 (51%) as 'probable' and five (9%) as 'non-diagnostic' based on the revised original scoring system. By the simplified scoring system, six (11%) were diagnosed as 'definite' AIH, 16 (29%) as 'probable' and 33 (60%) as 'non-diagnostic'. Anti-nuclear antibody titres did not differ among the three groups. The immunoglobulin G level was higher in fulminant than in non-severe patients (P = 0.01). Sixty-five per cent showed acute hepatitis (massive necrosis, submassive necrosis and severe acute hepatitis) and 35% showed chronic hepatitis. CONCLUSIONS: The revised original scoring system performed better in patients with acute-onset AIH than the simplified scoring system.
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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 | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".