POS0162 THE INFLUENCE OF BODY MASS INDEX ON CARDIOVASCULAR RISK IN RHEUMATOID ARTHRITIS VARIES ACROSS ANTICITRULLINATED PROTEIN ANTIBODY STATUS AND BIOLOGIC USE
Notice bibliographique
Résumé
Background: The impact of body mass index (BMI) as a surrogate of body fat content on cardiovascular risk in rheumatoid arthritis (RA) is unclear. Obesity associated with higher RA activity among anticitrullinated antibody (ACPA) positive but not negative patients. Since RA activity predicts cardiovascular risk, we hypothesized that obesity may associate with risk differently in ACPA positive versus negative patients. Biologic disease modifying antirheumatic drugs (bDMARDs) control inflammation, mitigate cardiovascular risk and may alter body composition in RA. Therefore BMI may relate to cardiovascular risk differently in bDMARD users versus nonusers. Lastly, ACPA status influenced effectiveness of certain bDMARDs. Objectives: We hence explored the association of BMI with cardiovascular risk and whether this varied across ACPA status and bDMARD use. Methods: We evaluated 3982 patients free of cardiovascular disease upon registration in An InTernation A l Consortium for Cardiovascular disease in RA (ATACC-RA). Outcomes included: (a) first major adverse cardiovascular event (MACE) encompassing non-fatal myocardial infarction, non-fatal stroke, or cardiovascular death and (b) all events additionally comprising angina, revascularization, transient ischemic attack, peripheral arterial disease and heart failure. Missing data were imputed using multiple imputation with 10 repetitions. Multivariable Cox models stratified by center risk evaluated the impact of BMI, ACPA positivity, bDMARD use, and their two- and three-way interactions on prespecified outcomes after adjusting for age, gender, diabetes, hypertension, family history of CV disease, smoking, total cholesterol to high-density lipoprotein cholesterol ratio, 28-joint disease activity score with ESR, and RA duration. A sensitivity analysis using inverse probability of treatment weighting to balance the differences across bDMARD treatment groups and ACPA status was undertaken to support the robustness of our findings. Results: We recorded 192 MACE and 319 total events. No main effects of BMI, bDMARDs or ACPA were observed on either MACE (HR 1.02, 95% CI 0.99-1.05, 1.47, 95% CI 0.74-2.92 and 1.37, 95% CI 0.99-1.90 respectively) or any cardiovascular events (HR 1.02, 95% CI 0.99-1.04, 1.35, 95% CI 0.79-2.28 and 1.07, 95% CI 0.84-1.36 correspondingly). Notably, a three-way interaction between them on MACE (p-interaction<0.001) and all-events (p-interaction=0.028) was noted. Among ACPA negative patients (Figure 1A and B), BMI inversely associated with MACE (HR 0.38, 95%CI 0.25-0.57) and all-event risk (HR 0.67, 95%CI 0.49-0.92) in bDMARD users but not nonusers (p-for-interaction<0.001 and 0.012). Results of the inverse probability weighted analysis were similar. Among ACPA positive patients, while the bDMARD × BMI interaction and bDMARD main effect were not significant for either outcome, BMI directly associated with MACE (HR 1.04, 95%CI 1.01-1.07) and all event risk (HR 1.03, 95%CI 1.00-1.06) independently of biologic use (Figure 2A and B). Conclusion: Among ACPA negative patients, BMI inversely associated with cardiovascular risk only among bDMARD users. In contrast, BMI directly associated with risk in ACPA positive patients. REFERENCES: NIL . Acknowledgements: NIL . Disclosure of Interests: George Karpouzas Scipher, Janssen, Pfizer, Elena Myasoedova: None declared, Miguel Ángel González-Gay: None declared, Alfonso Corrales Martinez: None declared, Solbritt Rantapää Dahlqvist: None declared, Petros P. Sfikakis: None declared, Patrick Dessein: None declared, Carol Hitchon: None declared, Virginia Pascual: None declared, Irazú Contreras-Yáñez: None declared, Iris J. Colunga-Pedraza: None declared, Dionicio A. Galarza-Delgado: None declared, Jose R. Azpiri-Lopez: None declared, Anne Grete Semb: None declared, Piet van Riel: None declared, Durga Prasanna Misra: None declared, Patrick Durez: None declared, Brian Bridal-Logstrup: None declared, Ellen-Margrethe Hauge: None declared, George Kitas: None declared, Sarah Ormseth: None declared. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,002 |
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 ».