Autoimmune hepatitis overlap syndromes: an evaluation of treatment response, long‐term outcome and survival
Bibliographic record
Abstract
BACKGROUND: Primary sclerosing cholangitis/autoimmune hepatitis (PSC/AIH) and primary biliary cirrhosis/AIH (PBC/AIH) overlap syndromes are poorly defined variants of AIH. Few large patient series exist, and there are little data on long-term outcomes. AIM: To compare presentation, clinical course and outcome of patients with PSC/AIH and PBC/AIH, with patients with definite AIH. Methods Two hundred and thirty-eight AIH patients were compared with 10 PBC/AIH patients and 16 PSC/AIH patients presenting consecutively between 1971 and 2005 at a single centre. RESULTS: Autoimmune hepatitis patients were significantly more likely to present with jaundice (69.4% vs. 25%; P = 0.0145) than PBC/AIH patients. Median serum aspartate aminotransferase activity at presentation was higher in AIH patients compared with PBC/AIH and PSC/AIH patients respectively (620 vs. 94 vs. 224 IU/L; P < 0.05). PBC/AIH patients demonstrated no response to standard AIH therapy more frequently than AIH patients (25% vs. 0.8%; P = 0.0057). Significant reduction in survival was identified between patients with PSC/AIH and those without (hazard ratio: PSC/AIH vs. AIH = 2.08, PSC/AIH vs. PBC/AIH = 2.14; P = 0.039). CONCLUSIONS: Patients with PSC/AIH have severe disease and significantly worse prognosis than patients with AIH or PBC/AIH. Recognition and close follow-up of this cohort are warranted.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".