Natural History and Treatment Outcomes of Severe Autoimmune Hepatitis
Bibliographic record
Abstract
GOALS: The aim of this study was to analyze the natural history and treatment outcomes of autoimmune hepatitis (AIH) variants presenting with severe-AIH. BACKGROUND: Severe acute presentation is an uncommon manifestation of AIH, and it remains poorly characterized. MATERIALS AND METHODS: We included 101 patients with AIH from January 2011 to December 2015. Patients were classified as seropositive-AIH and seronegative-AIH. Patients with acute liver failure, acute-on-chronic liver failure, and severe acute hepatitis were defined as severe-AIH patients. Patient characteristics and treatment outcomes with follow-up until 12 months were analyzed between the different groups. RESULTS: Out of 101 cases, 24 (23.76%) had severe AIH. Of them 9 (37.5%) had severe acute hepatitis, 3 (12.5%) had acute liver failure, and 12 (50%) had acute-on-chronic liver failure. Seronegative-AIH patients presented with severe-AIH significantly more frequently compared with seropositive-AIH patients (50% vs. 20.27%, P=0.022). Severe-AIH had 50% complete responders, 25% partial responders, and 25% treatment failures. Jaundice (88.88% vs. 68.7%, P=0.048), encephalopathy (55.55% vs. 6.66%, P=0.014), and higher international normalized ratio values (2.17±0.60 vs. 1.82±0.14, P=0.038) were factors associated with nonresponse rather than the presence or absence of autoantibodies in severe-AIH. The hazard ratio for predicting remission in the non-severe AIH group as compared with the severe-AIH group was 1.502, which was statistically not significant (95% CI, 0.799-2.827; P=0.205). CONCLUSION: Approximately 24% of patients with AIH have severe-AIH. Conventional autoantibodies are often absent in severe-AIH; however, it does not alter the outcome. Immunosuppressants should be given expediently in patients with severe-AIH.
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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 | 0.000 | 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 | 0.000 |
| 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".