Non-Invasive Prediction of High-Risk Varices in Patients with Primary Biliary Cholangitis and Primary Sclerosing Cholangitis
Bibliographic record
Abstract
BACKGROUND: Baveno-VI guidelines recommend that patients with compensated cirrhosis with liver stiffness by transient elastography (LSM-TE) <20 kPa and platelets >150,000/mm(3) do not need an esophagogastroduodenoscopy (EGD) to screen for varices, since the risk of having varices needing treatment (VNT) is <5%. It remains uncertain if this tool can be used in patients with cholestatic liver diseases (ChLDs): primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC). These patients may have a pre-sinusoidal component of portal hypertension that could affect the performance of this rule. In this study we evaluated the performance of Baveno-VI, expanded Baveno-VI (LSM-TE <25 kPa and platelets >110,000/mm(3)), and other criteria in predicting the absence of VNT. METHODS: This was a multicenter cross-sectional study in four referral hospitals. We retrospectively analyzed data from 227 patients with compensated advanced chronic liver disease (cACLD) due to PBC (n = 147) and PSC (n = 80) that had paired EGD and LSM-TE. We calculated false negative rate (FNR) and number of saved endoscopies for each prediction rule. RESULTS: Prevalence of VNT was 13%. Baveno-VI criteria had a 0% FNR in PBC and PSC, saving 39 and 30% of EGDs, respectively. In PBC the other LSM-TE-based criteria resulted in FNRs >5%. In PSC the expanded Baveno criteria had an adequate performance. In both conditions LSM-TE-independent criteria resulted in an acceptable FNR but saved less EGDs. CONCLUSIONS: Baveno-VI criteria can be applied in patients with cACLD due to ChLDs, which would result in saving 30-40% of EGDs. Expanded criteria in PBC would lead to FNRs >5%.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".