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Risk factor analysis for cognitive impairment in non-alcoholic fatty liver disease

2025· article· it· W4413084200 on OpenAlexaboutno aff
R.T. Barsah, Wasis UDAYA, Nu’man AS Daud, Syakib BAKRI, Haerani RASYID, Arifin SEWENG

Bibliographic record

VenueGazzetta Medica Italiana Archivio per le Scienze Mediche · 2025
Typearticle
Languageit
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsFatty liverCognitive impairmentAlcoholic liver diseaseDiseaseRisk factorCognitionMedicineFactor (programming language)PsychologyInternal medicinePsychiatryComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Hepatic lipid accumulation is a defining feature of liver diseases, referred to as non-alcoholic fatty liver disease (NAFLD). According to recent studies, there may be a connection between NAFLD and cognitive impairment, namely concerning memory and attention. This study aimed to define the forms of cognitive deficits associated with these risk variables and determine the factors contributing to cognitive impairment in NAFLD patients.METHODS: An analytical observational study was conducted at Wahidin Sudirohusodo Teaching Hospital in Indonesia from 2023 to 2024. A total of 126 NAFLD patients were included, and cognitive function was assessed using the Montreal Cognitive Assessment Indonesia (MoCA-INA) instrument. Statistical analysis was performed using SPSS version 25 (SPSS Inc., Chicago, IL, USA).RESULTS: Among the 126 NAFLD patients analyzed, 63 (50%) exhibited cognitive impairment, primarily as memory deficits. Obesity and dyslipidemia were significantly associated with cognitive impairment, with obesity presenting a 4.5-fold increased risk and dyslipidemia a 2.5-fold increased risk. However, hypertension and diabetes mellitus did not show significant associations with cognitive impairment.CONCLUSIONS: This study underscores the prevalence of cognitive impairment in NAFLD patients and highlights obesity and dyslipidemia as significant risk factors for cognitive decline in this population. Further longitudinal studies are needed to explore the relationship between NAFLD and cognitive impairment.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.003
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.301
Teacher spread0.281 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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