Expanding the Baveno VI criteria for the screening of varices in patients with compensated advanced chronic liver disease
Bibliographic record
Abstract
Patients with compensated advanced chronic liver disease (cACLD) can safely avoid screening endoscopy with a platelet count >150 × 10 9 cells/L and a liver stiffness measurement (LSM) <20 kPa (Baveno VI criteria). However, the total number of avoided endoscopies using this rule is relatively low. We aimed at expanding the Baveno VI criteria and validating them in additional cohorts. Patients from the Anticipate cohort (499 patients with cACLD of different etiologies) were used to study the performance of different thresholds of platelets and LSM for the identification of patients at very low risk (<5%) of having varices needing treatment (VNT). The new criteria (Expanded‐Baveno VI) were validated in two additional cohorts from London (309 patients) and Barcelona (117 patients). The performance of the new criteria by etiology of cACLD was also assessed. The best new expanded classification rule was platelet count >110 × 10 9 cells/L and LSM <25 kPa. This was validated in the two additional cohorts. Overall, the Expanded‐Baveno VI criteria would potentially spare 367 (40%) endoscopies (21% with Baveno VI criteria) with a risk of missing VNT of 1.6% (95% confidence interval, 0.7%‐3.5%) in patients within the criteria and 0.6% (95% confidence interval, 0.3%‐1.4%) in the overall population of 925 patients evaluated. The Expanded‐Baveno VI criteria performed well in patients with cACLD with hepatitis C virus and alcoholic and nonalcoholic steatohepatitis. Conclusion : The new Expanded‐Baveno VI criteria spare more endoscopies than the original criteria with a minimal risk of missing VNT in most of the main etiologies of cACLD. (H epatology 2017;66:1980–1988)
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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 | 0.004 | 0.010 |
| 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".