PO:14:206 | Factors impacting subjective cognitive impairment in systemic lupus erythematosus patients: clearing away the lupus brain fog
Bibliographic record
Abstract
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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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".