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Record W4411544060 · doi:10.1097/hep.0000000000001440

Call to action—Pediatric MASLD requires immediate attention to curb health crisis

2025· article· en· W4411544060 on OpenAlexaff
Phillipp Hartmann, Marialena Mouzaki, Sara Hassan, Mohit Kehar, Krupa R. Mysore, Erin E. Mauney, Dieudonne Nonga, Sara Karjoo, Shilpa Sood, Andrea Tou, Christine Brichta, Rachel E. Herdes, Nikhil Pai, Donna Garner, Mary E. Rinella, Mazen Noureddin, Zobair M. Younossi, Alina M. Allen, Arun J. Sanyal, Taisa Kohut, Rohit Kohli, Charina M. Ramirez, Stavra A. Xanthakos, Miriam B. Vos, Jeffrey B. Schwimmer, Samar H. Ibrahim, Jennifer Panganiban

Bibliographic record

VenueHepatology · 2025
Typearticle
Languageen
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsChildren's Hospital of Eastern Ontario
FundersNational Center for Advancing Translational SciencesEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsCall to actionAction (physics)MedicineEnvironmental healthBusinessAdvertising

Abstract

fetched live from OpenAlex

Pediatric metabolic dysfunction-associated steatotic liver disease (MASLD) has become more prevalent on a global scale over the last decades and is associated with significant comorbidities in childhood and a 40-fold higher risk of early mortality in young adulthood. MASLD has now become the leading indication for liver transplantation in young adults in the United States. However, pediatric MASLD is still perceived as an indolent condition by many patients, families, and clinicians. In this Call to Action, we aim to raise awareness of pediatric MASLD as a public health crisis. Herein, we describe insufficient screening and disease staging practices, and a lack of accurate non-invasive tests and effective pharmacotherapy, both stemming from a paucity of multicenter clinical trials in pediatric MASLD. We provide clear steps to address this public health emergency by promoting awareness campaigns, educating and empowering patients and families, addressing barriers including access to care, nutritional and exercise support programs, establishing multidisciplinary care, launching community initiatives, and conducting clinical trials in pediatric MASLD for an age-based evaluation of novel diagnostic and therapeutic options. We conclude by highlighting the urgent need for comprehensive public health policies to control the tide of pediatric MASLD and call upon stakeholders to act now.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.030
GPT teacher head0.377
Teacher spread0.347 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2025
Admission routes1
Has abstractyes

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