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Record W2922213148 · doi:10.3390/medicines6010041

The Epidemiology, Risk Profiling and Diagnostic Challenges of Nonalcoholic Fatty Liver Disease

2019· review· en· W2922213148 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMedicines · 2019
Typereview
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNonalcoholic fatty liver diseaseEpidemiologyProfiling (computer programming)DiseaseComputational biologyBiologyMedicineBioinformaticsFatty liverInternal medicineComputer science

Abstract

fetched live from OpenAlex

Nonalcoholic fatty liver disease (NAFLD) encompasses a wide spectrum of liver damage from the more prevalent (75%⁻80%) and nonprogressive nonalcoholic fatty liver (NAFL) category to its less common and more ominous subset, nonalcoholic steatohepatitis (NASH). NAFLD is now the most common cause of chronic liver disease in the developed world and is a leading indication for liver transplantation in United States (US). The global prevalence of NAFLD is estimated to be 25%, with the lowest prevalence in Africa (13.5%) and highest in the Middle East (31.8%) and South America (30.4%). The increasing incidence of NAFLD has been associated with the global obesity epidemic and manifestation of metabolic complications, including hypertension, diabetes, and dyslipidemia. The rapidly rising healthcare and economic burdens of NAFLD warrant institution of preventative and treatment measures in the high-risk sub-populations in an effort to reduce the morbidity and mortality associated with NAFLD. Genetic, demographic, clinical, and environmental factors may play a role in the pathogenesis of NAFLD. While NAFLD has been linked with various genetic variants, including PNPLA-3, TM6SF2, and FDFT1, environmental factors may predispose individuals to NAFLD as well. NAFLD is more common in older age groups and in men. With regards to ethnicity, in the US, Hispanics have the highest prevalence of NAFLD, followed by Caucasians and then African-Americans. NAFLD is frequently associated with the components of metabolic syndrome, such as type 2 diabetes mellitus (T2DM), obesity, hypertension, and dyslipidemia. Several studies have shown that the adoption of a healthy lifestyle, weight loss, and pro-active management of individual components of metabolic syndrome can help to prevent, retard or reverse NAFLD-related liver damage. Independently, NAFLD increases the risk of premature cardiovascular disease and associated mortality. For this reason, a case can be made for screening of NAFLD to facilitate early diagnosis and to prevent the hepatic and extra-hepatic complications in high risk sub-populations with morbid obesity, diabetes, and other metabolic risk factors.

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.

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)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.895
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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)0.0000.000

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.

Opus teacher head0.144
GPT teacher head0.390
Teacher spread0.246 · 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