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Record W4288707393 · doi:10.1111/liv.15381

Changing trends in aetiology‐based hospitalizations with end‐stage liver disease in the United States from 2016 to 2019

2022· article· en· W4288707393 on OpenAlexaff
Donghee Kim, Brandon J. Perumpail, Omar Alshuwaykh, Brittany B. Dennis, George Cholankeril, Aijaz Ahmed

Bibliographic record

VenueLiver International · 2022
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineLiver diseaseHepatocellular carcinomaCirrhosisAlcoholic liver diseaseAlcoholic hepatitisInternal medicineEtiologyChronic liver diseaseFatty liverGastroenterologyHepatitis CDiseaseIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUNDS AND AIMS: A potent and safe antiviral agent may impact chronic hepatitis C (HCV)-related end-stage liver disease (ESLD). We assess aetiology-based hospitalizations for ESLD in the United States, 2016-2019. METHODS: We utilized the National Inpatient Sample (NIS) from 2016 to 2019. We defined ESLD as either decompensated cirrhosis or hepatocellular carcinoma, criteria obtained from the International Classification of Diseases, Tenth Revision. RESULTS: National hospitalization rates for non-alcoholic fatty liver disease (NAFLD) increased significantly from 67.1/100 000 persons in 2016 to 93.6 in 2019 with an average annual percentage change (AAPC) of 12.1%, while chronic hepatitis C (HCV) decreased significantly from 71.2/100 000 persons in 2016 to 58.5 in 2019 (-6.5% AAPC). Hospitalizations for ESLD in alcohol-related liver disease (ALD) increased as well. CONCLUSIONS: Hospitalization rates for NAFLD- and ALD-related ESLD increased steadily, while those for HCV-related ESLD decreased during the direct-acting antivirals era.

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 categoriesInsufficient 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 score0.130
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.026
GPT teacher head0.314
Teacher spread0.288 · 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

Citations12
Published2022
Admission routes1
Has abstractyes

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