ARTERIAL STIFFNESS IN DIFFERENT AGE AND CARDIOVASCULAR RISK GROUPS OF PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS
Notice bibliographique
Résumé
PV056 / #703 Poster Topic: AS06 - Comorbidities Background/Purpose Systemic Lupus Erythematosus (SLE) is associated with increased cardiovascular morbidity and mortality. Arterial stiffness (ArS) is a marker of vascular aging and atherosclerosis and is a well-recognized predictor of cardiovascular risk in the general population; however, data in SLE is scarce. We compared ArS in SLE vs healthy controls (HC) and assessed potential predictors. Methods ArS was assessed in 194 SLE patients vs 1:1 age/sex/mean arterial pressure (MAP)-matched HC using the carotid-femoral pulse wave velocity (PWV) and augmentation index at 75 beats/min (AIx@75). ArS was examined in different age groups (18-37, 38-57, 58-75 years) and cardiovascular risk groups (low-moderate, high-very high) classified by the Systematic Coronary Risk Evaluation (SCORE). Carotid and femoral ultrasounds were performed to detect atherosclerotic plaque presence. Linear regression models were used to examine potential predictors of ArS, including patient demographic characteristics, Systemic Coronary Risk Evaluation (SCORE), the sum of modifiable cardiovascular risk factors (CVRFs) (among hypertension, dyslipidemia, smoking, exercise, and body weight), the achievement of Lupus Low Disease Activity State (LLDAS) and Definition of Remission in SLE (DORIS) clinical remission, Systemic Lupus International Collaborating Clinics/American College of Rheumatology (SLICC/ACR) damage index, cumulative glucocorticoid exposure, consistent hydroxychloroquine use, cardiovascular disease (CVD)-related medications, and antiphospholipid antibody (aPL) positivity at the time of the assessment. Results SLE patients had increased AIx@75 vs HC (β = 3.353, 95% CI 1.964-6.526, p = 0.019) (Table 1, model A), but not PWV (β = 0.102, 95% CI -0.117, 0.321, p = 0.361). Patients aged 18-37 had higher PWV (β = 0.409, 95% CI 0.095-0.722, p = 0.011) and AIx@75 (β = 10.115, 95% CI 6.111-14.119, p < 0.001) than HC (Table 1, models B and C). Low-moderate CVD risk patients had higher AIx@75 than HC (β = 3.387, 95% CI 0.735-6.039, p = 0.012) (Table 1, model D). PWV and AIx@75 were independently associated with atherosclerotic plaque presence (carotid or femoral) (β = 0.297, 95% CI 0.005-0.589, p = 0.046 and β = 4.867, 95% CI 1.989-7.746, p = 0.001, respectively). In SLE, PWV and AIx@75 were independently associated with age (β = 0.061, 95% CI 0.040-0.082, p < 0.001 and β = 0.426, 95% CI 0.278-0.574, p < 0.001, respectively), MAP (β = 0.051, 95% CI 0.031-0.070, p < 0.001 and β = 0.328, 95% CI 0.189-0.466, p < 0.001, respectively), and the sum of modifiable CVRFs (β = 0.258, 95% CI 0.055-0.461, p = 0.013 and β = 2.035, 95% CI 0.587-3.483, p = 0.006, respectively) (Table 1, models E and G). PWV was additionally associated with SCORE (β = 0.607, 95% CI 0.414-0.800, p < 0.001) (Table 1, model F). Among disease-related factors, AIx@75 was associated with disease duration (β = 0.274, 95% CI 0.081-0,467, p < 0.001) (Table 1, model H), and PWV correlated with past use of corticosteroids in patients aged 58-75 years (β = 1.660, 95% CI 0.185-3.135, p = 0.029). Table 1 Multivariate linear regression models of pulse wave velocity and augmentation index in SLE versus HC (models A, B, C, D), and within SLE (models E, F, G, H) Conclusions Increased ArS in SLE compared to HC is associated with traditional CVRF burden, emphasizing the need for early CVRF evaluation and treatment in SLE, particularly in young low CVD risk patients. ArS screening may help detect high CVD risk in low-moderate risk patients with SLE.
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 | 0,000 | 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 | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».