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Record W4391188810 · doi:10.1016/j.aohep.2024.101288

Lean non-alcoholic fatty liver disease and the risk of all-cause mortality: An updated meta-analysis

2024· article· en· W4391188810 on OpenAlexaboutno aff
Wasit Wongtrakul, Natthinee Charatcharoenwitthaya, Phunchai Charatcharoenwitthaya

Bibliographic record

VenueAnnals of Hepatology · 2024
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineHazard ratioFatty liverOverweightMeta-analysisPublication biasCohort studyBody mass indexCirrhosisLiver diseaseDiseaseConfidence interval

Abstract

fetched live from OpenAlex

INTRODUCTION AND OBJECTIVES: Cohort studies reported controversial results regarding the long-term prognosis of patients with lean non-alcoholic fatty liver disease (NAFLD) compared to non-lean NAFLD patients. This updated meta-analysis aimed to estimate the magnitude of the association between lean body mass index and all-cause mortality risk in NAFLD patients. MATERIALS AND METHODS: We systematically searched the EMBASE and MEDLINE databases from inception to March 2023 to identify observational studies that reported hazard ratio (HR) for all-cause mortality of patients with lean NAFLD versus those with non-lean, overweight, or obese NAFLD. Multivariable-adjusted hazard ratios (HRs) for all-cause mortality were pooled using a random effects model. RESULTS: =77 %). The magnitude of this risk remained unchanged even after stratified analysis by measures of NAFLD diagnosis, study country, cohort setting, length of follow-up, adjustment with fibrosis stage/cirrhosis, and the Newcastle-Ottawa Scale. The risk was independent of age, sex, and cardiometabolic risk factors. Sensitivity analyses did not alter these findings. The funnel plot and Egger's test revealed no significant publication bias. CONCLUSIONS: This meta-analysis revealed that lean NAFLD is associated with an approximately 1.6-fold increased mortality risk. Further studies are needed to unravel the existing but complex link between lean NAFLD and an increased risk of death.

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: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0010.000

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 head0.186
GPT teacher head0.399
Teacher spread0.213 · 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 designMeta-analysis
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

Citations27
Published2024
Admission routes1
Has abstractyes

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