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Record W4323351266 · doi:10.1093/jcag/gwac036.191

A191 NONALCOHOLIC FATTY LIVER DISEASE AND LIVER FIBROSIS INCREASE CARDIOVASCULAR RISK IN PATIENTS WITH INFLAMMATORY BOWEL DISEASES

2023· article· en· W4323351266 on OpenAlexaff
D Kablawi, F Aljohani, Chiara Saroli Palumbo, Sophie Restellini, A Bitton, G Wild, W Afif, Péter L. Lakatos, T Bessissow, G Sebastiani

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2023
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsJewish General HospitalMcGill University Health Centre
Fundersnot available
KeywordsMedicineTransient elastographyInternal medicineNonalcoholic fatty liver diseaseGastroenterologyFatty liverDiabetes mellitusFibrosisPopulationMetabolic syndromeUlcerative colitisInflammatory bowel diseaseLiver diseaseDiseaseEndocrinologyObesityLiver fibrosis

Abstract

fetched live from OpenAlex

Abstract Background Non-alcoholic fatty liver disease (NAFLD) is strongly associated with cardiovascular disease in the general population. Both NAFLD and cardiovascular diseases seem more frequent in patients with inflammatory bowel disease (IBD). Purpose We aimed to assess the effect of NAFLD and associated liver fibrosis on the cardiovascular risk in people with IBD. Method We prospectively included IBD patients undergoing a routine screening program for NAFLD by transient elastography (TE) with associated controlled attenuation parameter (CAP). NAFLD and significant liver fibrosis were defined as CAP >275 dB/m and liver stiffness measurement (LSM) by TE ≥8 kPa, respectively. Nonalcoholic steatohepatitis (NASH) with liver fibrosis was defined as Fibroscan-aspartate aminotransferase (AST) score (FAST) >0.35. Cardiovascular risk was assessed with the atherosclerotic cardiovascular disease (ASCVD) risk estimator proposed by the American Heart Association and computed from age, sex, race, lipid pattern, blood pressure, diabetes treatment and smoking. Based on the American Heart Association guidelines, the 10-year cardiovascular risk by ASCVD was categorized as low if <5%, borderline if 5%–7.4%, intermediate if 7.5%–19.9% and high if ≥20% or if previous cardiovascular event.Predictors of intermediate-high cardiovascular risk were investigated by multivariable logistic regression analysis. Result(s) We included 405 patients with IBD (54% female; mean age 45+15 years; mean BMI 26+5 Kg/m; 31% with ulcerative colitis; 7% with diabetes; 14% with hypertension). Overall, 278 (68%), 23 (6%), 47 (12%) and 57 (14%) were categorized as at low, borderline, intermediate and high ASCVD risk, respectively. NAFLD and significant liver fibrosis were found in 129 (32%) and 35 (9%) patients, respectively. NASH with fibrosis was found in 11 (3%) patients. Patients with NAFLD and with significant liver fibrosis diagnosed by TE with CAP had higher proportion of intermediate-high ASCVD risk category (see Figure). These findings were confirmed also in young IBD patients <55 years old with NAFLD. No difference in ASCVD risk was detected for FAST score. After adjusting for IBD disease activity, significant liver fibrosis and BMI, predictors of intermediate-high ASCVD risk were NAFLD (adjusted odds ratio [aOR] 2.97, 95% confidence interval [CI] 1.56–5.68), IBD duration (aOR 1.55 per 10 years, 95% CI 1.22–1.97), and ulcerative colitis (aOR 2.32, 95% CI 1.35–3.98). Only 30% of IBD patients classified as intermediate-high ASCVD risk were on statin treatment, with no difference between patients with and without NAFLD. Image Conclusion(s) NAFLD increases cardiovascular risk, independently of age, IBD-related factors and BMI. A potential implication of our finding is the targeted cardiovascular assessment in IBD patients with NAFLD and appropriate initiation of statin, particularly if they have longer IBD duration and ulcerative colitis. Please acknowledge all funding agencies by checking the applicable boxes below CAG Disclosure of Interest None Declared

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)0.000
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.004
GPT teacher head0.185
Teacher spread0.181 · 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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Citations1
Published2023
Admission routes1
Has abstractyes

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