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Record W3044891542 · doi:10.4254/wjh.v12.i7.378

Non-alcoholic steatohepatitis and the risk of myocardial infarction: A population-based national study

2020· article· en· W3044891542 on OpenAlexaff
Sara Ghoneim, Aneesh Dhorepatil, Aun R. Shah, Ganesh Ram, Subhan Ahmad, Chang H. Kim, Imad Asaad

Bibliographic record

VenueWorld Journal of Hepatology · 2020
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineSteatohepatitisOdds ratioInternal medicineMyocardial infarctionFatty liverDiabetes mellitusPopulationHyperlipidemiaDiseaseEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is a systemic disease with bidirectional relationships with cardiovascular disease (CVD). Non-alcoholic steatohepatitis (NASH) is a more severe subtype of NAFLD. Patients with NASH exhibit more intra and extrahepatic inflammation, procoagulant imbalances and proatherogenic lipid profiles. Whether NASH increases the risk of ischemic heart disease is currently unclear. AIM: To investigate the relationship between acute myocardial infarction (MI) and NASH in a large cohort of subjects in the United States. METHODS: We reviewed data from a large commercial database (Explorys IBM) that aggregates electronic health records from 26 large nationwide healthcare systems. Using systemized nomenclature of clinical medical terms (SNOMED CT), we identified adult with the diagnosis of NASH from 1999-2019. We included patients with the diagnosis of acute MI from 2018-2019. Comorbidities known to be associated with NASH and MI such as obesity, diabetes mellitus, hyperlipidemia, smoking, male gender, and hypertension were collected. Univariable and multivariable analyses were performed to investigate whether NASH is independently associated with the risk of MI. RESULTS: Out of 55099280 patients, 43170 were diagnosed with NASH (0.08%) and 107000 (0.194%) had a MI within 2018-2019. After adjusting for traditional risk factors, NASH conferred greater odds of MI odds ratio (OR) 1.5 [95% confidence interval (CI): 1.40-1.62]. Hyperlipidemia had the strongest association with MI OR 8.39 (95%CI: 8.21-8.58) followed by hypertension OR 3.11 (95%CI: 3.05-3.17) and smoking OR 2.83 (95%CI: 2.79-2.87). NASH had a similar association with MI as the following traditional risk factors like age above 65 years OR 1.47 (95%CI: 1.45-1.49), male gender OR 1.53 (95%CI: 1.51-1.55) diabetes mellitus OR 1.89 (95%CI: 1.86-1.91). CONCLUSION: MI appears to be a prevalent disease in NASH. Patients with NASH may need early identification and aggressive cardiovascular risk modification.

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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.015
GPT teacher head0.272
Teacher spread0.256 · 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

Citations20
Published2020
Admission routes1
Has abstractyes

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