Tailored Model of Care for Patients with Metabolic Dysfunction-Associated Steatotic Liver Disease
Bibliographic record
Abstract
Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as nonalcoholic fatty liver disease (NAFLD), is increasing globally, creating a growing public health concern. However, this disease is often not diagnosed, and accurate data on its epidemiology are limited in many geographical regions, making it challenging to provide proper care and implement effective national plans. To combat the increasing disease burden, screening and diagnosis must reach a significant number of high-risk subjects. Addressing MASLD as a health care challenge requires a multidisciplinary approach involving prevention, diagnosis, treatment, and care, with collaboration between multiple stakeholders in the health care system. This approach must be guided by national and global strategies, to be combined with efficient models of care developed through a bottom-up process. This review article highlights the pillars of the MASLD model of care (MoC), including screening, risk stratification, and establishing a clinical care pathway for management, in addition to discussing the impact of nomenclature change on the proposed MoC.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".