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Hepatic Steatosis Is Highly Prevalent but Is Not Correlated With Advanced Fibrosis in Autoimmune Hepatitis: Results Obtained at the Autoimmune Hepatitis Association National Meeting

2018· article· en· W2921030946 on OpenAlexaff
Sai Chalasani, Vahin Vuppalanchi, Regina Weber, Naga Chalasani, Craig Lammert

Bibliographic record

VenueThe American Journal of Gastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsCollège Jean-de-Brébeuf
Fundersnot available
KeywordsSteatosisMedicineAutoimmune hepatitisTransient elastographyInternal medicineGastroenterologyFatty liverHepatitisHepatitis CLiver diseaseFibrosisDiseaseLiver fibrosis

Abstract

fetched live from OpenAlex

Introduction: Obesity and associated steatosis are unfavorable prognostic factors in viral hepatitis. A recent report suggested that coexisting fatty liver disease may adversely affect the natural history of patients with autoimmune hepatitis in a similar fashion. We conducted a study to examine the prevalence of hepatic steatosis in individuals with autoimmune hepatitis. Methods: Vibration-controlled transient elastography (Fibroscan) was offered to patients with autoimmune hepatitis (AIH) at the Autoimmune Hepatitis Association (AIHA) national meeting in June 2017 in Indianapolis. All participants were fasting for 3 hours prior to examination. Based on the NASH CRN criteria for 90% sensitivity, presence of hepatic steatosis was defined as Continuous Attenuation Parameter (CAP) ≥ 263 dB/m and severe hepatic steatosis as CAP score ≥ 274 dB/m. The presence of compensated advanced chronic liver disease (cACLD) was defined as: liver stiffness measurement (LSM) > 15 kPa as highly suggestive, 10-15 kPa) as suggestive and < 10 kPa as unlikely. Results: 221 participants attended the AIHA conference in which 148 (67%) carried the diagnosis of AIH and 73 (33%) were caregivers. In total, 74 (50%) participants with AIH (8% male and 92% female) completed Fibroscan examination. This group had a median age of 48 years (yrs) and BMI 29 kg/m2. The median liver stiffness and CAP scores of all participants was 6.8 kPa and 236 dB/m, respectively. 22 (30%) patients had steatosis whereas 19 (26%) severe steatosis. Individuals with both steatosis and severe steatosis had higher BMI (32.6 kg/m2, 32.9 kg/m2) compared to those without steatosis (26.8 kg/m2, p=0.01). Patients with steatosis (50 yrs) also tended to be older compared to those without steatosis (47 yrs, p=0.09). According to the parameters of cACLD, 11 (15%) individuals were highly suggestive, 12 (16%) were suggestive, and 51 (69%) had no evidence of cACLD. Advanced fibrosis was more likely in participants that were male (67% vs 28%, p=0.07) and had higher BMI (31 kg/m2 vs 27.1 kg/m2, p=0.02). There was no significant correlation between advanced fibrosis and the presence of steatosis (r=0.17, p=0.3) or severe steatosis (r=0.18, p=0.3). Conclusion: In patients with AIH there is high prevalence of any steatosis or severe steatosis, but lack of their correlation with advanced fibrosis argues against a role for steatosis in worsening fibrosis in patients with AIH.946_C Figure 3. Liver Cancer Death Rate946_B Figure 2. GI Fellowships

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)0.003
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.007
GPT teacher head0.243
Teacher spread0.236 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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