Advancing the global public health agenda for NAFLD: a consensus statement
Bibliographic record
Abstract
Non-alcoholic fatty liver disease (NAFLD) is a potentially serious liver disease that affects approximately one-quarter of the global adult population, causing a substantial burden of ill health with wide-ranging social and economic implications. It is a multisystem disease and is considered the hepatic component of metabolic syndrome. Unlike other highly prevalent conditions, NAFLD has received little attention from the global public health community. Health system and public health responses to NAFLD have been weak and fragmented, and, despite its pervasiveness, NAFLD is largely unknown outside hepatology and gastroenterology. There is only a nascent global public health movement addressing NAFLD, and the disease is absent from nearly all national and international strategies and policies for non-communicable diseases, including obesity. In this global Delphi study, a multidisciplinary group of experts developed consensus statements and recommendations, which a larger group of collaborators reviewed over three rounds until consensus was achieved. The resulting consensus statements and recommendations address a broad range of topics — from epidemiology, awareness, care and treatment to public health policies and leadership — that have general relevance for policy-makers, health-care practitioners, civil society groups, research institutions and affected populations. These recommendations should provide a strong foundation for a comprehensive public health response to NAFLD. Non-alcoholic fatty liver disease (NAFLD) is a potentially serious liver disease with a substantial burden worldwide. In this Consensus Statement, a global multidisciplinary group of experts develop consensus statements and recommendations addressing a broad range of topics on NAFLD to raise awareness and spur action.
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 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 | 0.048 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.013 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".