Behçet Disease and Cognitive Impairment: A Case Study of an Overlooked Symptom
Bibliographic record
Abstract
BACKGROUND Behçet disease (BD) is a rare systemic vasculitis with diverse clinical manifestations, most commonly oral ulcers. Neurological involvement occurs in 5% to 15% of cases, often presenting as brainstem and myelopathic syndromes. However, cognitive impairment can develop even in the absence of overt neurological signs. A case-control study using the Brief Repeatable Battery of Neuropsychological Tests reported cognitive dysfunction in 38% of BD patients lacking overt neurological symptoms, suggesting that the cognitive dysfunction was immune-mediated. This case report points to the importance of heightened clinical vigilance in patients with BD presenting with subtle cognitive changes, even in the absence of neurological involvement. Routine neuropsychological screening could enable earlier detection and timely intervention, thereby reducing the risk of irreversible cognitive decline. CASE REPORT A 59-year-old woman with BD presented with progressive cognitive impairment 1 year after diagnosis. She had no prior cognitive problems or focal neurological signs. Her comorbid thymoma and hyperthyroidism remained clinically stable. Cognitive screening (MoCA-INA 27/30) revealed deficits in memory and attention, supported by suboptimal performance on the Digit Span and Trail-Making tests. Brain magnetic resonance imaging (MRI) ruled out stroke or neurodegeneration but demonstrated bilateral parietal atrophy and mild white-matter hyperintensities in the temporal and occipital lobes. She received donepezil, folic acid, cognitive stimulation, and immunosuppressive therapy. At 1-year follow-up, the Montreal Cognitive Assessment (MoCA-INA) score had normalized (30/30), with improved neurocognitive performance and stable daily functioning. CONCLUSIONS This case shows that cognitive impairment can present as an isolated manifestation of BD, even in the absence of overt neurological symptoms. Early neuropsychological screening and timely intervention can prevent progression and preserve quality of life.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".