PO:14:206 | Factors impacting subjective cognitive impairment in systemic lupus erythematosus patients: clearing away the lupus brain fog
Notice bibliographique
Résumé
Background. Systemic lupus erythematosus (SLE) patients (pts) often suffered from an impairment in cognitive functions, but a universal definition of “brain fog” does not exist. The objective of the study was to evaluate the prevalence of subjective impairment and objective mental alterations (depression, cognition, fatigue) adopting screening tools validated in SLE; also we aimed to investigate which factors were associated with brain fog. Methods. A Cross-sectional study was conducted enrolling adult SLE pts. Brain fog referred to the presence of mental alterations (i.e.; memory, concentration, attention...) as reported by SLE participants. To minimize contribution of type B symptoms, we made a subanalysis of brain fog involving pts with active disease, namely lupus fog. Demographic, clinical, therapeutic data were collected (Table). Serum anti-ribosomal P antibodies (anti-RibP) were quantified using ELISA kits. Cognitive deficits were assessed by a neuropsychologist exploring deficits in 8 cognitive domains with a battery of neuropsychological tests and screened using the Montreal Cognitive Assessment (MoCA) test performed by certified personnel (cut-off<26/30). Depressive symptoms were evaluated using the Center for Epidemiologic Studies Depression Scale (CES-D) (>15). Fatigue was measured using FACIT-F (<34). Chi-squared test and the Mann-Whitney test were used for univariate analysis (UV-A); multivariate analysis (MV-A) was performed building logistic regression models including variables showing p <0.10. Results. 114 SLE pts were enrolled (Table), 105 female (92.1%), mean age 43.7 years (+-12.2). Brain fog was found in 54% pts, with memory deficit reported in 49.1%, attention in 38.6%, concentration in 10.5% and afasia nominum in 5.3%. CES-D>15 was altered in 53.3%, MoCA<26 in 45% and FACIT<34 in 52.9%. At UV-A, an association emerged between the presence of brain fog and CES-D (Fig1A, score p<0.001), FACIT (Fig1A, score p=0.012), fibromyalgia (p<0.001), the neuropsychiatric involvement (p=0.015), anti-RNP (p=0.014), anti Rib-P (p=0.018) and disease duration (p=0.045). No association was found with MoCA test, the battery of neuropsychological test, disease activity scores or treatment. At MV-A, an independent association between brain fog and fibromyalgia (OR=34.6; 95%CI 2.3-523.1, p=0.011), CES-D score (OR=1.1 per unit, 95%CI 1.0-1.2, p=0.033) and disease duration (OR=1.1 per year, 95%CI 1.0-1.2, p=0.038) emerged. Out of 46 pts with clinically active disease, 21 were classified as lupus fog, resulting associated at UV-A with CES-D (Fig2A, score p=0.034), FACIT (Fig2A, score p=0.024) , fibromyalgia (p=0.017). MV-A showed independent association between lupus fog and FACIT score (OR=-0.146; 95%CI -0.275 to -0.017). Conclusion. Brain fog is frequent in SLE pts, but did not correlate with cognitive dysfunction, but with longer disease duration, depressive symptoms, fibromyalgia and in active pts with fatigue. Our findings suggest that SLE pts may have a negative perception about proper cognitive performances, without having a real impairment, supporting the need for assessing depressive and fatigue symptoms during clinical visits.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».