FACTORS INFLUENCING SUBJECTIVE MENTAL ALTERATIONS: UNRAVELING THE LUPUS BRAIN FOG
Bibliographic record
Abstract
PV043 / #685 Poster Topic: AS05 - CNS Lupus Background/Purpose Brain fog is a common symptom in systemic lupus erythematosus (SLE) patients that refers to a “clouding of mental functions.” Its prevalence is probably underestimated due to the fact that a universal definition of “lupus fog” does not exist. The aim of the study was to evaluate in a cohort of SLE patients the prevalence of subjective mental alterations, named “lupus fog” (LF) and objective mental alterations (depression, cognition, fatigue) adopting screening tools validated in SLE. The second objective was to investigate which factors are associated with LF. Methods A cross-sectional study was conducted enrolling adult SLE patients (ACR/EULAR 2019 criteria). LF referred to the presence of mental alterations (ie, memory, concentration, attention impairment) as reported by participants. Demographic, clinical, clinimetrics, therapeutic data were collected (Table). Serum anti-ribosomal P antibodies (anti-Rib-P) were quantified using ELISA kits. Cognitive deficits were screened using the Montreal Cognitive Assessment (MoCA) test performed by certified personnel (using the standard cut-off of <26/30 and a more sensitive cut-off <28/30)[1] and assessed by a neuropsychologist exploring deficits in 8 cognitive domains with a battery of neuropsychological tests. Depressive symptoms were evaluated using the Center for Epidemiologic Studies Depression Scale (CES-D) and adopting a more sensitive cut-off (>15) and the cut-off suggested by Kwan et al (>25).[2] Fatigue was measured using the the Functional Assessment of Chronic Illness Therapy (FACIT-F) (cut-off <30 and a more sensitive cut-off <34).[3] Chi-squared and the Mann-Whitney test were used for univariate analysis; multivariate analysis was performed building logistic regression models including variables showing p values of <0.10. Table. Results 114 SLE patients were enrolled (Table), 105 female (92.1%), mean age 43.7 years (+-12.2). LF was found in 54/100 patients (54%). CES-D >15 was altered in 56/105 pts (53.3%), CES-D >25 in 26 (24.7%), MoCA <26 in 45/100 pts (45%), MoCA <28 in 75 (75%), FACIT <30 in 31/69 (44.9%) and FACIT <34 in 36 (52.9%). At univariate analysis, an association emerged between the presence of LF and CES-D alterations (CES-D >15 p=0.014; CES-D >25 p=0.010, CES-D score p<0.001), FACIT (FACIT <30 p=0.039, FACIT <34 p=0.042, FACIT score p=0.012), fibromyalgia (p<0.001), the neuropsychiatric involvement (NPSLE) (p=0.015), anti-Ribonucleoprotein 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. Two different models of logistic regression were built. Model 1 including fibromyalgia, showed independent association between LF 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). Model 2 excluding fibromyalgia showed independent association between LF and FACIT score (OR=0.93 per unit, 95% CI 0.88-0.99, p=0.013), anti-Rib-P (OR=5.2 per unit, 95% CI 1.0-1.2, p=0.033). Conclusions Lupus fog is frequent. Our study also confirms the high prevalence of cognitive impairment, depressive symptoms and fatigue in SLE. A longer disease duration, depressive symptoms and the diagnosis of fibromyalgia were factors independently associated with lupus fog. Our findings suggest that SLE patients frequently have a negative perception about proper cognitive performances, without having a real impairment, supporting the multifactorial etiology of clinical issues in SLE, related to direct and indirect factors. References: [1.] Raghunath S. Lupus Sci Med 2021;8(1):e000580. [2.] Kwan A. Semin Arthritis Rheum 2019;49(2):260-6. [3.] Kawka L. RMD Open 2023;9:e003476.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".