NONALCOHOLIC FATTY LIVER DISEASE IN SYSTEMIC LUPUS ERYTHEMATOSUS: ASSOCIATIONS WITH CARDIOVASCULAR RISK FACTOR GOAL ACHIEVEMENT AND ATHEROSCLEROTIC PLAQUE PROGRESSION OVER THE PAST 10 YEARS
Notice bibliographique
Résumé
PV057 / #707 Poster Topic: AS06 - Comorbidities Background/Purpose Nonalcoholic fatty liver disease (NAFLD) is a broad term including different stages of liver steatosis and fibrosis, and is the most common liver disease worldwide. It has been identified as an independent predictor of cardiovascular disease in the general population,[1] and has been associated with multiple cardiovascular risk factors (CVRFs) and atherosclerosis. However, evidence on the prevalence and predictors of NAFLD in Systemic Lupus Erythematosus (SLE) is limited. We compared the prevalence of NAFLD in patients with SLE vs healthy controls (HCs) and examined associations with sustained CVRF goal achievement, progression of atherosclerotic plaques over the past 10 years, and potential disease-related CVRFs. Methods Patients with SLE and age and sex-matched HCs who had a 10-year carotid and femoral ultrasound follow-up examination in our department were contacted to participate in the study. Liver transient elastography was performed to assess liver steatosis and fibrosis presence in 77 patients with SLE and 45 age- and sex-matched HCs. Liver steatosis was graded based on Control Attenuation Parameter (CAP) values, as follows: S0 (absent): 100–238 decibels/meter (dB/m), S1 (mild): 238–260 dB/m, S2 (moderate): 260–290 dB/m, and S3 (severe): > 290 dB/m. Liver steatosis presence was defined as grade ≥ S1. Liver stiffness was graded as F0–F1: 2–7 kilopascals (kPa), F2: 7–10 kPa, F3: 10–14 kPa, and F4: > 14 kPa. Liver fibrosis was defined as grade ≥ F2. Logistic regression analysis assessed potential predictors of NAFLD in patients with SLE, including alcohol consumption defined as drinks per week, Mediterranean Diet score (tool for the assessment of mediterranean diet adherence), CVRFs (blood pressure, total cholesterol, Low-Density Lipoprotein, High-Density Lipoprotein, triglycerides, smoking status, physical activity, BMI, waist circumference, family history of coronary artery disease), Systemic Coronary Risk Evaluation (SCORE) prediction score, sustained CVRF target attainment for blood pressure, lipids, smoking, physical activity, and body weight, as defined by the 2016 European Society of Cardiology guidelines, and atherosclerotic carotid and femoral plaque progression. Among disease-related potential predictors, we examined the persistent achievement of Lupus Low Disease Activity State (LLDAS) and Definition of Remission in SLE (DORIS) clinical remission, and persistent antiphospholipid antibody positivity during the 10-year follow-up period. Cardiovascular disease-related (antihypertensives, lipid-lowering agents and antiplatelets) and SLE-related medications (cumulative glucocorticoid exposure, consistent hydroxychloroquine use during the 10-year follow-up, immunosuppressives) were also assessed. Results Liver steatosis presence did not differ significantly between SLE and HC individuals (40,25% vs 44,44% respectively, p = 0.651). No liver fibrosis was detected in either group. In the SLE group, multivariate analysis showed that atherosclerotic femoral plaque progression over the past 10 years was associated with a 3.6-fold higher risk for NAFLD (Odds Ratio [OR]: 3.62, 95% CI 1.018-12.93, p = 0.021). NAFLD was also independently associated with persistent positivity of IgG anti-beta2 glycoprotein I antibodies (OR: 6.58, 95% CI 1.33-32.566, p = 0.021) during the 10-year follow-up. Each cardiovascular risk factor (including blood pressure, lipids, smoking, physical activity, and body weight) persistently on target during the 10-year follow-up period reduced NAFLD risk by 55% (OR: 0.45, 95% CI 0.231-0.889, p = 0.021). Conclusions Atherosclerotic femoral plaque progression and persistent IgG anti-beta2 glycoprotein I antibodies positivity were independent predictors of liver steatosis in patients with SLE, which can be drastically mitigated by sustained CVRF goal achievement. References: [1.] Stahl EP. J Am Coll Cardiol 2019;73:948-63.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».