Letter: guidelines for the management of autoimmune hepatitis
Bibliographic record
Abstract
In his critique1 of our British Society of Gastroenterology guidelines for management of autoimmune hepatitis (AIH),2 Dr Czaja addresses several issues, which we believe we discussed in more detail than he acknowledges. However, he seems to agree with us on many: (i) Diagnostic scoring systems should not be rigidly applied; they may indeed be unreliable in patients with acute liver failure, although we do not think this is so in non-Caucasian patients. (ii) Centrilobular necrosis and biliary changes are indeed within the histological spectrum of AIH. (iii) Drug-related AIH is managed by drug withdrawal, and corticosteroids, but not by maintenance therapy. (iv) High-dose steroids should be tried in nonresponders to standard doses. (v) Liver biopsy to confirm remission should be considered. We did not recommend this strongly because, whilst providing useful information, re-biopsy has not yet been shown to yield proven patient benefits. Because the published AIH evidence base is inadequate, recommendations are often ‘weak’, opinions differ and decisions must be individualised. The ‘AIH community’ should work towards resolving current uncertainty by formulating questions, which need answering, and devising strategies for doing so. Declaration of personal and funding interests: None.
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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 | 0.005 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.043 | 0.032 |
| Insufficient payload (model declined to judge) | 0.005 | 0.009 |
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".