Importance of computed tomography imaging features for the diagnosis of autoimmune acute liver failure
Bibliographic record
Abstract
AIM: The diagnosis of acute liver failure due to autoimmune hepatitis is often difficult because of atypical clinicopathological features. Patients with autoimmune acute liver failure are sometimes resistant to immunosuppressive therapy and have poor prognosis. Although their survival rates are especially poor (5-20%) without liver transplantation in Japan, their clinicopathological features have remained uncertain. A major problem is that there is no gold standard for making the diagnosis of acute onset autoimmune hepatitis. If there are diagnosing tools supporting clinicopathological features, they are of benefit to the patients. We examined computed tomography (CT) imaging features of autoimmune acute liver failure to clarify the usefulness of imaging for the diagnosis. METHODS: A retrospective analysis of 129 unenhanced CT scans of 68 patients with acute hepatitis, consisting of 23 with autoimmune acute liver failure (ALF) (group 1), 25 with early admission-viral ALF (group 2) and 20 with late admission-viral ALF (group 3), was performed. RESULTS: Autoimmune acute liver failure showed heterogeneous hypoattenuating areas and viral ALF diffuse ones (P < 0.001). The diffuse hypoattenuating areas were present in none of group 1, 15 (60%) of group 2, and 7 (30%) of group 3. The heterogeneous hypoattenuating areas were present in 15 (65%) of group 1, none of group 2 and 1 (5%) of group 3. CONCLUSIONS: Heterogeneous hypoattenuation on unenhanced CT was a characteristic CT imaging feature of autoimmune acute liver failure compared with viral ALF. This finding could be one of the tools for diagnosing autoimmune acute liver failure in combination with clinicopathological features.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".