Validation of MELD3.0 in 2 centers from different continents
Bibliographic record
Abstract
BACKGROUND: MELD3.0 has been proposed to stratify patients on the liver transplant waiting list (WL) to reduce the historical disadvantage of women in accessing liver transplant. Our aim was to validate MELD3.0 in 2 unique populations. METHODS: This study is a 2-center retrospective cohort study from Toronto, Canada, and Valencia, Spain, of all adults added to the liver transplant WL between 2015 and 2019. Listing indications whose short-term survival outcome is not adequately captured by the MELD score were excluded. All patients analyzed had a minimum follow-up of 3 months after inclusion in the WL. RESULTS: Six hundred nineteen patients were included; 61% were male, with a mean age of 56 years. Mean MELD at inclusion was 18.00 ± 6.88, Model for End-Stage Liver Disease Sodium (MELDNa) 19.78 ± 7.00, and MELD3.0 20.25 ± 7.22. AUC to predict 90-day mortality on the WL was 0.879 (95% CI: 0.820, 0.939) for MELD, 0.921 (95% CI: 0.876, 0.967) for MELDNa, and 0.930 (95% CI: 0.888, 0.973) for MELD3.0. MELDNa and MELD3.0 were better predictors than MELD (p = 0.055 and p = 0.024, respectively), but MELD3.0 was not statistically superior to MELDNa (p = 0.144). The same was true when stratified by sex, although the difference between MELD3.0 and MELD was only significant for women (p = 0.032), while no statistical significance was found in either sex when compared with MELDNa. In women, AUC was 0.835 (95% CI: 0.744, 0.926) for MELD, 0.873 (95% CI: 0.785, 0.961) for MELDNa, and 0.886 (95% CI: 0.803, 0.970) for MELD3.0; differences for the comparison between AUC in women versus men for all 3 scores were nonsignificant. Compared to MELD, MELD3.0 was able to reclassify 146 patients (24%), the majority of whom belonged to the MELD 10-19 interval. Compared to MELDNa, it reclassified 68 patients (11%), most of them in the MELDNa 20-29 category. CONCLUSIONS: MELD3.0 has been validated in centers with significant heterogeneity and offers the highest mortality prediction for women on the WL without disadvantaging men. However, in these cohorts, it was not superior to MELDNa.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".