Noninvasive Prediction of Outcomes in Autoimmune Hepatitis–Related Cirrhosis
Bibliographic record
Abstract
The value of noninvasive tools in the diagnosis of autoimmune hepatitis (AIH)-related cirrhosis and the prediction of clinical outcomes is largely unknown. We sought to evaluate (1) the utility of liver stiffness measurement (LSM) in the diagnosis of cirrhosis and (2) the performance of the Sixth Baveno Consensus on Portal Hypertension (Baveno VI), expanded Baveno VI, and the ANTICIPATE models in predicting the absence of varices needing treatment (VNT). A multicenter cohort of 132 patients with AIH-related cirrhosis was retrospectively analyzed. LSM and endoscopies performed at the time of cirrhosis diagnosis were recorded. Most of the patients were female (66%), with a median age of 54 years. Only 33%-49% of patients had a LSM above the cutoff points described for the diagnosis of AIH-related cirrhosis (12.5, 14, and 16 kPa). Patients with portal hypertension (PHT) had significantly higher LSM than those without PHT (15.7 vs. 11.7 kPa; P = 0.001), but 39%-52% of patients with PHT still had LSM below these limits. The time since AIH diagnosis negatively correlated with LSM, with longer time being significantly associated with a lower proportion of patients with LSM above these cutoffs. VNT was present in 12 endoscopies. The use of the Baveno VI, expanded Baveno VI criteria, and the ANTICIPATE model would have saved 46%-63% of endoscopies, but the latter underpredicted the risk of VNT. Conclusions: LSM cutoff points do not have a good discriminative capacity for the diagnosis of AIH-related cirrhosis, especially long-term after treatment initiation. Noninvasive tools are helpful to triage patients for endoscopy.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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 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".