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Record W4323351289 · doi:10.1093/jcag/gwac036.079

A79 THE RELATIONSHIP BETWEEN VISCERAL ADIPOSITY AND NONALCOHOLIC FATTY LIVER DISEASE DIAGNOSED BY CONTROLLED ATTENUATION PARAMETER IN PEOPLE WITH HIV: A PILOT STUDY

2023· article· en· W4323351289 on OpenAlexaff
Wesal Elgretli, N Paisible, C Costiniuk, J Cox, Dana Kablawi, M Klein, N Kronfli, J -P Routy, J Falutz, Bertrand Lebouché, Giovanni Guaraldi, Giovanna Sebastiani

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2023
Typearticle
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsMedicineWaistNonalcoholic fatty liver diseaseInternal medicineAdipose tissueOverweightGastroenterologyFatty liverObesityInsulin resistanceEndocrinologyMetabolic syndromeBody mass indexProspective cohort studyDisease

Abstract

fetched live from OpenAlex

Abstract Background Aging people with HIV (PWH) on antiretroviral therapy face high rates of metabolic dysfunction and nonalcoholic fatty liver disease (NAFLD). Fat alterations are frequent in PWH and predict worse cardiometabolic outcomes. Visceral adipose tissue (VAT) is an important compartment of body fat tissue releasing bioactive molecules. As a hormonally active tissue, VAT critically contributes to obesity-related disorders and is associated with ectopic fat accumulation in the liver. Purpose We aimed to investigate NAFLD diagnosed by controlled attenuation parameter (CAP) as a marker of visceral adiposity in PWH. Method We conducted a prospective pilot study (ClinicalTrials.gov 2021-6656) of HIV mono-infected patients undergoing metabolic characterization and paired CAP by transient elastography with dual-energy X-ray absorptiometry (DEXA) scan. NAFLD was defined as CAP ≥285 dB/m, in absence of alcohol abuse. Excess visceral adiposity was defined as VAT>1.32 Kg. Pairwise correlation, area under the curve (AUC) and logistic regression analysis were employed to study the association between VAT and CAP. Result(s) 30 patients (90% male, mean age 48.5, mean BMI 29.9, mean waist circumference 100.9, 50% with NAFLD) were included. When compared to those without excess VAT, PWH with excess VAT were older (53+12 vs 43+13 years, p=0.035), had longer duration of HIV infection (20+13 vs. 9+9 years, p=0.021), had higher BMI (32+4 vs 27+4 Kg/m2, p=0.002) and waist circumference (107+11 vs. 93+12 cm, p=0.004). They also had more history of cardiovascular events (29% vs. 0, p=0.032) and higher lipid accumulation product, a marker of lipid accumulation based on waist circumference and triglycerides (112+53 vs. 38+27, p<0.001). CAP was higher in PWH with excess VAT (319+52 vs. 213+52 dB/m, p<0.001). CAP positively correlated with all visceral fat measurements by DEXA, including VAT (r=0.650, p<0.001), VAT/body weight ratio (r=0.565, p=0.001) and fat mass (r=0.390, p=0.033). Both BMI and waist circumference showed correlation with VAT and fat mass, but not with VAT/body weight ratio (see Figure). After adjusting for duration of HIV infection (aOR 1.01 per year, 95% CI 0.91-1.12; p=0.921), BMI (aOR 1.77, 95% CI 0.74-4.23; p=0.202) and waist circumference (aOR 0.91 per cm, 95% 0.68-1.21; p=0.509), CAP remained the only independent predictor of excess VAT (aOR 1.05 per dB/m, 95% CI 1.01-1.10; p=0.036). The AUC analysis determined CAP had excellent performance to diagnose excess VAT (AUC 0.92, 95% CI 0.81-1.00), higher than BMI (AUC 0.83, 95% CI 0.68-0.99) and waist circumference (AUC 0.81, 95% CI 0.65-0.97). The optimized CAP cut-off to diagnose excess VAT was 266 dB/m, with a sensitivity of 88.3% and a specificity of 84.6%. Image Conclusion(s) NAFLD diagnosed by CAP is associated with VAT in PWH independently of anthropometric measures of obesity. CAP could be used as a diagnostic marker of visceral adiposity in the practice of HIV medicine Please acknowledge all funding agencies by checking the applicable boxes below Other Please indicate your source of funding; CanHepC Disclosure of Interest W. Elgretli Grant / Research support from: CanHepC, N. Paisible: None Declared, C. Costiniuk: None Declared, J. Cox: None Declared, D. Kablawi: None Declared, M. Klein: None Declared, N. Kronfli: None Declared, J.-P. Routy: None Declared, J. Falutz: None Declared, B. Lebouche: None Declared, G. Guaraldi: None Declared, G. Sebastiani: 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)0.001
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.027
GPT teacher head0.281
Teacher spread0.254 · 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
Published2023
Admission routes1
Has abstractyes

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