Cost-Effectiveness of the Baveno VI Criteria Compared With Endoscopy for High-Risk Varices in Patients With Child-Pugh A Cirrhosis
Bibliographic record
Abstract
BACKGROUND & AIMS: Although upper gastrointestinal endoscopy (EGD) remains the gold standard for detecting varices in cirrhosis, the Baveno VI criteria proposed a combination of transient elastography and platelet count that could rule out high-risk varices, therefore sparing the need for an endoscopy, with significant potential cost savings. We performed a cost-effectiveness analysis of the Baveno VI criteria compared with EGD in the diagnosis of high-risk varices in cirrhosis. METHODS: We built an analytical decision model to estimate the cost and benefits of using the Baveno VI criteria compared with EGD in patients with Child-Pugh A cirrhosis. The analysis was performed from the UK National Health Service perspective, over 1, 5, and 20 years. A Markov model was populated with data from published evidence. Outcomes were measured in terms of quality-adjusted life years (QALYs) and avoided deaths. The analyses were repeated for Canada and Spain, using relevant cost inputs. RESULTS: The Baveno VI criteria were cost effective compared with endoscopy in all analyses. For 1000 patients, they produced 0.16 additional QALYs at an incremental cost of £326 ($443.41) over 5 years, resulting in an incremental cost of £2081 ($2830) per additional QALY gained. The incremental net monetary benefit of Baveno VI compared with EGD was £2808 ($3819) over 5 years per patient. Baveno VI criteria also were cost effective in Canada and Spain. Deterministic and probabilistic sensitivity analysis supported these findings. CONCLUSIONS: The findings demonstrate that the Baveno VI criteria are cost effective, suggesting that they should be considered for widespread implementation on the basis of safety, appropriateness, and economic grounds.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".