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Record W4396582962 · doi:10.1111/jgh.16554

Impact of nomenclature as metabolic associated steatotic liver disease on steatotic liver disease prevalence and screening: a prospective population survey in Asians

2024· article· en· W4396582962 on OpenAlexaff
Tingfeng Wu, Junzhao Ye, Sui‐Lin Mo, Miaosheng Ye, Xiaoyi Li, Qing Li, Wengeng Wang, Qiaocong Zheng, Ke Luo, Yi Zhang, Shouwei Tu, Daituan Che, Rulong Gong, Xing Chen, Rong Miu, Congxiang Shao, Yanhong Sun, Bihui Zhong

Bibliographic record

VenueJournal of Gastroenterology and Hepatology · 2024
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsHealth Care Foundation
FundersBasic and Applied Basic Research Foundation of Guangdong ProvinceChina Postdoctoral Science FoundationSun Yat-sen UniversityNational Natural Science Foundation of China
KeywordsMedicineDiseaseMetabolic syndromeFatty liverLiver diseaseInternal medicinePopulationProspective cohort studyEnvironmental healthObesity

Abstract

fetched live from OpenAlex

BACKGROUND AND AIM: The introduction of the latest nomenclature, metabolic associated steatotic liver disease (MASLD), proposed by the multi-society without Asian society consensus statement, aims to redefine the diagnostic criteria for metabolic associated fatty liver disease (MAFLD). However, its effect on the epidemiology in Asia remains unclear. METHOD: We conducted a population-based cross-sectional survey on fatty liver disease using multistage stratified random sampling of participants from Guangzhou, a representative area in China (ChiCTR2000033376). Demographic, socioeconomic, lifestyle, and laboratory data were collected. Hepatic steatosis and the severity of fibrosis were assessed using FibroScan. RESULTS: A total of 7388 individuals were recruited, the proportion of which meeting the definitions for nonalcoholic fatty liver disease (NAFLD), MAFLD, and MASLD were 2359 (31.9%), 2666 (36.1%), and 2240 (30.3%), respectively. One hundred and twenty (1.6%) patients had cryptogenic SLD, and 537 (7.3%) patients were diagnosed with MetALD. MASLD did not significantly differ from NAFLD and MAFLD, except that MAFLD patients had a lower proportion of males, hypertension, and diabetes and were less likely to consume tea (P < 0.05). Both cryptogenic SLD and MASLD non-MAFLD patients exhibited milder hepatic steatosis and a lower frequency of liver injury than NAFLD, MAFLD, or MASLD patients (all P < 0.05). An increased HOMA-IR (adjusted OR: 1.33, 95% CI: 1.10-2.03) was associated with higher risk of moderate-to-severe steatosis for MASLD non-MAFLD patients, while consuming more cups of tea (P for trend = 0.015) showed inverse associations. CONCLUSION: Irrespective of terminology used is that fatty liver disease is highly prevalent in the Han Chinese population. Differences in insulin resistance and lifestyle risk factors are associated with redefinition disparities.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.296
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2024
Admission routes1
Has abstractyes

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