Performance of fibrosis prediction scores in paediatric non‐alcoholic fatty liver disease
Bibliographic record
Abstract
AIM: Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease in children. The phenotype of NAFLD varies widely, and non-invasive predictors of disease severity are scarce and are needed to tailor clinical management. METHODS: We compared liver fibrosis by histology with proposed non-invasive predictors of fibrosis, including alanine transaminase (ALT), aspartate transaminase (AST), AST/ALT ratio, AST to platelet ratio index, fibrosis-4, paediatric NAFLD fibrosis index and paediatric NAFLD fibrosis score. RESULTS: The area under the curve of scores obtained while predicting fibrosis in children with NAFLD ranged from 0.51 to 0.67. CONCLUSION: The tested non-invasive fibrosis scoring systems, some of which were originally designed for adult populations, did not adequately predict fibrosis in a paediatric cohort. Further development of risk prediction scores in children are needed for the management of paediatric patients and will likely need to be developed within a large paediatric data set in order to improve specificity and sensitivity.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".