PO.1.15 Lupus brain fog: cognitive impairment and depression in systemic lupus erythematosus
Notice bibliographique
Résumé
Purpose To investigate the prevalence and main determinants of cognitive dysfunction, anxiety and depression in a cohort of patients with Systemic Lupus Erythematosus (SLE); to explore the coping strategies and impact of these disorders on quality of life and function. Methods This observational cross-sectional study recruited patients of the University of Campania ‘Luigi Vanvitelli’, from February 4th to April 4h, 2022, who were diagnosed with SLE according to the Systemic Lupus International Collaborating Clinics (SLICC) Criteria. Demographic and clinical data, disease activity (SLEDAI-2k), damage (SDI) and concomitant therapies were analyzed. The definitions for remission (DORIS) and ‘Lupus Low Disease Activity State’ (LLDAS) were applied. At enrollment, each patient underwent a psychiatric evaluation completing the following questionnaires: Hamilton Depression and Anxiety Rating Scales (HAM-D, HAM-A), Montreal Cognitive Assessment (MoCA) and Coping Orientation to Problems Experienced (COPE) Inventory. Health Assessment Questionnaire-Disability Index (HAQ-DI) was also performed. The Spearman test was used for linear correlation. Multivariate analysis was performed by multiple linear and logistic regression. Results 61 consecutive patients with SLE were enrolled, the majority female (88%) and Caucasian with a mean age of 46 years. 70% were in remission or in LDA. The prevalence of cognitive dysfunction was 65%, executive function and memory were the most affected domains. We found isolated anxiety in 3% and isolated depression in 50.7% of patients, even if mild. Regarding coping strategies, SLE patients reported higher scores on emotion-focused coping, with respect to the other two coping strategies (p< 0,001). Pearson’s correlation analysis highlighted a relationship between higher levels of cognitive impairment and worse quality of life (r = -0.38, p = 0.002) and between hypocomplementemia and depression (r=-0,25; P=0,04). AntidsDNA antibody positivity was slightly significant (r=0,22; P=0,08). Our analysis also highlighted a positive correlation between emotion-focused and avoidance-focused strategies (0.43;P=0.0005). In the multivariate analysis, higher scores on the HAM-D questionnaire (higher levels of depression) were found to be independently associated with higher HAQ score (OR:1.2; p=0.03). Moreover, patients with active disease tend to be more depressed compared to patients in LDA or in remission (p : 0.04). Fibromyalgia was independently associated with depression (OR: 3.85 p : 0.03). Depression was found to be significantly linked to patients’ worse quality of life, irrespective of disease activity (OR:1.19; p=0.01). Depression, anxiety and fibromyalgia were not associated with objective cognitive dysfunction. Conclusion Our study confirms the high prevalence of cognitive dysfunction and depressive symptoms in SLE patients and determine a strong negative impact on function and quality of life. In the context of a multidisciplinary management, collaboration with clinical psychologists should be considered, to improve both coping strategies, patients’ perception of health status and quality of life.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 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) | 0,024 | 0,003 |
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 ».